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Author SHA1 Message Date
sinohqb
160332665e refactor(exploration): absorb settlement.py into ExplorationSessionRepository
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将 settlement.py 的 settle_campaign_sessions 函数吸收为
ExplorationSessionRepository.expire_running_sessions 方法。删除浅模块
settlement.py(30 行,接口宽如实现),会话生命周期操作集中在 repository。

- 新增 ExplorationSessionRepository.expire_running_sessions(campaign_id)
- 更新 campaigns.py 和 campaign_runner.py 两个调用点
- 删除 backend/agenteval/exploration/settlement.py
- 所有测试通过,行为不变
2026-08-04 13:28:23 +08:00
sinohqb
0aa3ef81c5 refactor(repository): extract AsyncJobRepository base class for analysis/comparison
提取 AsyncJobRepository 泛型基类,消除 CampaignAnalysisRepository 和
CampaignPeriodComparisonRepository 的重复代码。基类提供 get_by_campaign
和 mark_orphans_failed 通用逻辑,子类只需指定 _table 类型和实现 upsert。

- 新增 AsyncJobRepository[DB] 泛型基类
- mark_orphans_failed 接受 error_message 参数,子类传入特定错误信息
- 删除约 60 行重复代码(两个 __init__、两个 get_by_campaign、两个 mark_orphans_failed 实现)
- 所有测试通过,行为不变
2026-08-04 13:25:42 +08:00
sinohqb
cbfdf86b36 refactor(frontend): extract useCampaignReport hook from Campaigns.tsx
将活动报告抽屉的数据获取逻辑从 Campaigns.tsx 抽离到 useCampaignReport hook。
消除 5 个独立状态变量(report/reportRuns/reportTimeline/analysis/comparison)
和 fetchReport 函数的 25 行样板代码。hook 封装 5 个并行 API 调用和状态管理,
组件只负责渲染和交互。

- 新增 useCampaignReport(campaignId) hook
- 返回 {report, runs, timeline, analysis, comparison, loading, refetch, setAnalysis, setComparison}
- Campaigns.tsx 从 1122 行缩减状态管理复杂度
- TypeScript 类型检查通过,后端测试全绿
2026-08-04 11:45:15 +08:00
sinohqb
c24998c762 refactor(metrics): extract dashboard aggregation to compute_dashboard
仪表盘聚合逻辑从 stats.py router 下沉到 metrics.py 的 compute_dashboard
纯函数。_settled 重命名为 settled_runs 并公开,_ts 重命名为 _sortable_ts。
router 从 40 行聚合逻辑缩到 5 行,只负责数据获取和序列化。

- 新增 compute_dashboard(runs, scenario_names, target_names) -> dict
- 新增 settled_runs(runs) 公开接口(原 _settled)
- trend 端点同步迁移到 settled_runs
- 5 个新测试覆盖 dashboard 聚合逻辑
2026-08-04 11:36:55 +08:00
sinohqb
42be31dd1f feat(report): add load_campaign_view as unified campaign read model
活动级读模型单一出口:一次取齐报告 / 探索 / 分析 / 对比四大数据源。
markdown handler 从 30 行拼装逻辑缩到 3 行;分析执行器同步迁移。
comparison.py 内部的 8 次 load_campaign_report 调用暂不动(跨请求冗余,
缓存收益有限,改动风险高)。

- 新增 load_campaign_view(session, campaign) -> dict[str, Any]
- 返回 {report, exploration, analysis, comparison} 四键
- 迁移 markdown handler 和分析执行器两个调用点
- 4 个新测试覆盖 view 的组装逻辑
2026-08-04 11:33:45 +08:00
sinohqb
2fddce8c92 refactor(case-verdict): extract build_case_evidence as single evidence-construction seam
用例判定证据构建收敛到 case_verdict.py 的 build_case_evidence 纯函数,
report.py 和 runs.py 各删 ~15 行重复逻辑,换一行调用。locality 回归:
证据构建改一处,全局生效。

- 新增 build_case_evidence(turns, results) -> dict[str, CaseEvidence]
- report.py:76-83 证据构建替换为一行调用
- runs.py:175-201 证据构建替换为一行调用
- 5 个新测试覆盖 build_case_evidence(纯函数,无 DB 依赖)
2026-08-04 11:23:56 +08:00
sinohqb
2b6cab6cb2 feat(comparison): unify read model and validation for period comparison
周期对比读模型升位为单一出口(load_comparison_view),GET/POST/markdown
三处调用点统一走同一 view 投影,消除「取数三件套」重复。校验逻辑收敛到
validate_comparison_request,router 捕获映射 400,执行器捕获落 failed 行,
校验顺序权威不再漂移。

- 新增 load_comparison_view:无行返回 status=none + auto_baseline,有行
  返回完整 comparison dict(含 model_name 标签)+ metric_diff
- 新增 validate_comparison_request:活动终态 → 模型 → 基线 → 分析,违
  规抛 ComparisonError
- execute_campaign_comparison 内联校验替换为 validate_comparison_request
  调用,catch ComparisonError 落 failed 行
- router 三处迁移:GET /comparison、POST /comparison、markdown 导出
- 删除 build_comparison_payload(已吸收进 load_comparison_view)
- 8 个新测试覆盖读模型三态 + 校验五错
2026-08-04 10:49:14 +08:00
sinohqb
f3a528611e refactor(tasks): route LLM background tasks through TaskRegistry
架构保养第二轮候选 1:分析 / 周期对比 / judge 复核三条 LLM 任务链
收进各自的模块级 TaskRegistry(强引用防 GC、按 id 幂等、shutdown
统一收敛),删除 judge 的 _BACKGROUND_TASKS 私货,start_* 不再返回
无人消费的 Task。启动清理块补两笔 orphan 清扫:滞留的 generating
分析与对比行标记为 failed,与僵尸运行清扫同构。新增 7 个单测。
2026-08-04 09:58:20 +08:00
133 changed files with 6822 additions and 381 deletions

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---
name: ask-matt
description: Ask which skill or flow fits your situation. A router over the skills in this repo.
disable-model-invocation: true
---
# Ask Matt
You don't remember every skill, so ask.
A **flow** is a path through the skills. Most paths run along one **main flow**, and two **on-ramps** merge onto it. Everything else is standalone, or a vocabulary layer that runs underneath.
## The main flow: idea → ship
The route most work travels. You have an idea and want it built.
1. **`/grill-with-docs`** — sharpen the idea by interview. Start here when you **have a codebase**: it's stateful, retaining what it learns in `CONTEXT.md` and ADRs. (No codebase? Use `/grill-me` — see Standalone. Both run the same `/grilling` primitive; `grill-with-docs` is the one that leaves a paper trail.)
2. **Branch — can you settle every question in conversation?** If a question needs a runnable answer (state, business logic, a UI you have to see), detour through a prototype, bridged by **`/handoff`** in both directions (see Crossing sessions):
- **`/handoff`** out, then open a fresh session against that file,
- **`/prototype`** to answer the question with throwaway code,
- **`/handoff`** back what you learned, and reference it from the original idea thread.
3. **Branch — is this a multi-session build?**
- **Yes****`/to-spec`** (turn the thread into a spec), then **`/to-tickets`** to split it into tracer-bullet tickets, each declaring its **blocking edges**. On a local tracker that's one file per ticket under `.scratch/<feature>/issues/`, worked blockers-first by hand; on a real tracker the edges become native blocking links, so any ticket whose blockers are done can be grabbed — kick off **`/implement`** per ticket, **clearing context between each one**.
- **No****`/implement`** right here, in the same context window.
Either way, **`/implement`** builds each issue by driving **`/tdd`** internally — one red-green slice at a time — then closes out by running **`/code-review`**, a two-axis review (Standards + Spec) of the diff, before committing. Reach for **`/tdd`** on its own when you just want to build a concrete behaviour test-first without a full spec, and **`/code-review`** on its own whenever you want to review a branch or PR against a fixed point.
### Context hygiene
Keep steps 13 in **one unbroken context window** — don't compact or clear until after `/to-tickets` — so the grilling, spec, and tickets all build on the same thinking. Each `/implement` then starts fresh, working from the ticket.
The limit on this is the **[smart zone](https://www.aihero.dev/ai-coding-dictionary/smart-zone)**: the window (~120k tokens on state-of-the-art models) within which the model still reasons sharply. If a session approaches it before `/to-tickets`, don't push on degraded — `/handoff` and continue in a fresh thread.
## On-ramps
A starting situation that generates work, then merges onto the main flow.
- **Bugs and requests piling up****`/triage`**. It moves issues through triage roles and produces agent-ready issues, which **`/implement`** later picks up.
Triage is only for issues **you didn't create** — bug reports, incoming feature requests, anything that arrives raw. Tickets that `/to-tickets` produced are already agent-ready, so **don't triage them**.
- **Something's broken****`/diagnosing-bugs`**. For the hard ones: the bug that resists a first glance, the intermittent flake, the regression that crept in between two known-good states. It refuses to theorise until it has a **tight feedback loop** — one command that already goes red on *this* bug — then fixes with a regression test. Its post-mortem hands off to **`/improve-codebase-architecture`** when the real finding is that there's no good seam to lock the bug down.
- **A huge, foggy effort — a greenfield project or a huge feature build, too big for one session****`/wayfinder`**, the most cognitively demanding flow here. When the way from here to the destination isn't visible yet, it charts a **shared map** of **decision tickets** on the issue tracker and resolves them one at a time — producing **decisions, not deliverables** — until the fog is pushed back and the way is clear. Where **`/grill-with-docs`** sharpens an idea you can hold in one session, wayfinder is for the idea you can't — and it's slower and denser, so save it for exactly that, never a well-scoped feature.
When the map clears, **it hands off, it doesn't build**: merge onto the main flow at **`/to-spec`**, which collapses the map's linked decisions into a buildable plan, then `/to-tickets` and `/implement` as usual. Looping the map straight into `/implement` skips that collapse and throws the linked detail away — go straight to `/implement` only when the effort turned out genuinely small.
## Codebase health
Not feature work — upkeep.
- **`/improve-codebase-architecture`** — run whenever you have a spare moment to keep the codebase good for agents to operate in. It surfaces **deepening opportunities**; picking one _generates an idea_ you can take into the main flow at `/grill-with-docs`. It's the survey that finds the candidates; **`/codebase-design`** (below) is the bench you design the chosen one on.
## Vocabulary underneath
Two model-invoked references that run *beneath* the other skills — each the single source of truth for its vocabulary. Reach for them directly when the **words**, not the process, are the problem; or let the skills above pull them in.
- **`/domain-modeling`** — sharpen the project's *domain* language: challenge a fuzzy term, resolve an overloaded word ("account" doing three jobs), record a hard-to-reverse decision as an ADR. It's the active discipline `/grill-with-docs` drives to keep `CONTEXT.md` a clean glossary.
- **`/codebase-design`** — the deep-module vocabulary (module, interface, depth, seam, adapter, leverage, locality) for designing a module's *shape*: a lot of behaviour behind a small interface at a clean seam. `/tdd` and `/improve-codebase-architecture` both speak it.
## Crossing sessions
- **`/handoff`** — when a thread is full or you need to branch off (e.g. into a `/prototype` session), this compacts the conversation into a markdown file. You don't continue in place — you **open a new session and reference that file** to carry the context across. It's the bridge between context windows, in either direction. Use it when you want a **fresh session** but need the **current conversation preserved**.
- **`/compact`** (built-in) — stay in the **same conversation**, letting the earlier turns be summarized. Use it at **intentional breaks between phases**, when you don't mind losing the verbatim history. Don't compact mid-phase — the agent can lose its way. `/handoff` forks; `/compact` continues.
## Standalone
Off the main flow entirely.
- **`/grill-me`** — the same relentless interview as `/grill-with-docs`, but for when you have **no codebase**. Stateless: it saves nothing locally, builds no `CONTEXT.md`. Reach for it to sharpen any plan or design that doesn't live in a repo.
- **`/prototype`** — a small, throwaway program that answers one design question: does this state model feel right, or what should this UI look like. Throwaway from day one — keep the answer, delete the code. It's the detour in step 2 of the main flow, but reach for it any time a design question is hard to settle on paper.
- **`/research`** — delegate reading legwork to a **background agent**: it investigates a question against **primary sources**, then leaves a cited Markdown file in the repo. Keep working while it reads. The file it produces is something to take *into* the main flow at `/grill-with-docs` — research feeds the thinking, it doesn't replace it.
- **`/teach`** — learn a concept over multiple sessions, using the current directory as a stateful workspace.
- **`/writing-great-skills`** — reference for writing and editing skills well.
## Precondition
**`/setup-matt-pocock-skills`** — run before your first engineering flow to configure the issue tracker, triage labels, and doc layout the other skills assume. Custom issue trackers also work.

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interface:
display_name: "Ask Matt"
short_description: "Find the right skill or workflow"
policy:
allow_implicit_invocation: false

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---
name: batch-grill-me
description: A relentless interview that asks every frontier question at once, round by round.
disable-model-invocation: true
---
Interview the user relentlessly until you reach a shared understanding. Map this as a **design tree**: every decision branches into the decisions that hang off it.
Work the tree in **rounds**. The **frontier** is every decision whose prerequisites are already settled — the questions you can ask *now* without guessing at answers you haven't heard yet. Ask the whole frontier in one round: number each question and give your recommended answer. Then wait for the user's answers before the next round.
Each round the user answers reshapes the tree — settled decisions push the frontier outward and unblock questions that depended on them. Recompute the frontier and ask the next round. A question whose answer depends on another question still open in this round belongs to a *later* round, not this one.
Finding *facts* is your job, never the user's. When a frontier question needs a fact from the environment (filesystem, tools, etc.), dispatch a sub-agent to find it — don't ask the user for anything you could look up yourself. Don't block on it: a running exploration is an unsettled prerequisite, so only the questions downstream of it wait for the sub-agent to report — ask the rest of the frontier now. The *decisions* are the user's — put each to them and wait.
The session is done when the frontier is empty: every branch of the design tree visited, nothing left silently assumed. Do not act on it until the user confirms you have reached a shared understanding.

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interface:
display_name: "Batch Grill Me"
short_description: "Sharpen a plan a round of questions at a time"
policy:
allow_implicit_invocation: false

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---
name: claude-handoff
description: Hand the current conversation off to a fresh background agent that picks up the work immediately.
argument-hint: "What will the next session be used for?"
disable-model-invocation: true
---
Write a handoff summary of the current conversation so a fresh agent can continue the work. Instead of saving it, launch a background agent seeded with the summary as its prompt: `claude --bg --name "<descriptive name>" "<handoff summary>"`. It starts in the current working directory and returns immediately; the user manages it with `claude agents`.
Always pass `-n`/`--name` with a descriptive name (e.g. `--name "Fix login bug"`) — it sets the display name shown in the job list, session picker, and terminal title.
Include a "suggested skills" section in the summary, which suggests skills that the agent should invoke.
Do not duplicate content already captured in other artifacts (PRDs, plans, ADRs, issues, commits, diffs). Reference them by path or URL instead.
Redact any sensitive information, such as API keys, passwords, or personally identifiable information — the summary becomes the agent's prompt.
If the user passed arguments, treat them as a description of what the next session will focus on and tailor the summary accordingly.

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interface:
display_name: "Claude Handoff"
short_description: "Hand off to a background agent"
policy:
allow_implicit_invocation: false

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---
name: code-review
description: Review the changes since a fixed point (commit, branch, tag, or merge-base) along two axes — Standards (does the code follow this repo's documented coding standards?) and Spec (does the code match what the originating issue/PRD asked for?). Runs both reviews in parallel sub-agents and reports them side by side. Use when the user wants to review a branch, a PR, work-in-progress changes, or asks to "review since X".
---
Two-axis review of the diff between `HEAD` and a fixed point the user supplies:
- **Standards** — does the code conform to this repo's documented coding standards?
- **Spec** — does the code faithfully implement the originating issue / PRD / spec?
Both axes run as **parallel sub-agents** so they don't pollute each other's context, then this skill aggregates their findings.
The issue tracker should have been provided to you — run `/setup-matt-pocock-skills` if `docs/agents/issue-tracker.md` is missing.
## Process
### 1. Pin the fixed point
Whatever the user said is the fixed point — a commit SHA, branch name, tag, `main`, `HEAD~5`, etc. If they didn't specify one, ask for it.
Capture the diff command once: `git diff <fixed-point>...HEAD` (three-dot, so the comparison is against the merge-base). Also note the list of commits via `git log <fixed-point>..HEAD --oneline`.
Before going further, confirm the fixed point resolves (`git rev-parse <fixed-point>`) and the diff is non-empty. A bad ref or empty diff should fail here — not inside two parallel sub-agents.
### 2. Identify the spec source
Look for the originating spec, in this order:
1. Issue references in the commit messages (`#123`, `Closes #45`, GitLab `!67`, etc.) — fetch via the workflow in `docs/agents/issue-tracker.md`.
2. A path the user passed as an argument.
3. A PRD/spec file under `docs/`, `specs/`, or `.scratch/` matching the branch name or feature.
4. If nothing is found, ask the user where the spec is. If they say there isn't one, the **Spec** sub-agent will skip and report "no spec available".
### 3. Identify the standards sources
Anything in the repo that documents how code should be written, such as `CODING_STANDARDS.md` or `CONTRIBUTING.md`.
On top of whatever the repo documents, the Standards axis always carries the **smell baseline** below — a fixed set of Fowler code smells (_Refactoring_, ch.3) that applies even when a repo documents nothing. Two rules bind it:
- **The repo overrides.** A documented repo standard always wins; where it endorses something the baseline would flag, suppress the smell.
- **Always a judgement call.** Each smell is a labelled heuristic ("possible Feature Envy"), never a hard violation — and, like any standard here, skip anything tooling already enforces.
Each smell reads *what it is**how to fix*; match it against the diff:
- **Mysterious Name** — a function, variable, or type whose name doesn't reveal what it does or holds. → rename it; if no honest name comes, the design's murky.
- **Duplicated Code** — the same logic shape appears in more than one hunk or file in the change. → extract the shared shape, call it from both.
- **Feature Envy** — a method that reaches into another object's data more than its own. → move the method onto the data it envies.
- **Data Clumps** — the same few fields or params keep travelling together (a type wanting to be born). → bundle them into one type, pass that.
- **Primitive Obsession** — a primitive or string standing in for a domain concept that deserves its own type. → give the concept its own small type.
- **Repeated Switches** — the same `switch`/`if`-cascade on the same type recurs across the change. → replace with polymorphism, or one map both sites share.
- **Shotgun Surgery** — one logical change forces scattered edits across many files in the diff. → gather what changes together into one module.
- **Divergent Change** — one file or module is edited for several unrelated reasons. → split so each module changes for one reason.
- **Speculative Generality** — abstraction, parameters, or hooks added for needs the spec doesn't have. → delete it; inline back until a real need shows.
- **Message Chains** — long `a.b().c().d()` navigation the caller shouldn't depend on. → hide the walk behind one method on the first object.
- **Middle Man** — a class or function that mostly just delegates onward. → cut it, call the real target direct.
- **Refused Bequest** — a subclass or implementer that ignores or overrides most of what it inherits. → drop the inheritance, use composition.
### 4. Spawn both sub-agents in parallel
Send a single message with two `Agent` tool calls. Use the `general-purpose` subagent for both.
**Standards sub-agent prompt** — include:
- The full diff command and commit list.
- The list of standards-source files you found in step 3, **plus the smell baseline from step 3** pasted in full — the sub-agent has no other access to it.
- The brief: "Report — per file/hunk where relevant — (a) every place the diff violates a documented standard: cite the standard (file + the rule); and (b) any baseline smell you spot: name it and quote the hunk. Distinguish hard violations from judgement calls — documented-standard breaches can be hard, but baseline smells are always judgement calls, and a documented repo standard overrides the baseline. Skip anything tooling enforces. Under 400 words."
**Spec sub-agent prompt** — include:
- The diff command and commit list.
- The path or fetched contents of the spec.
- The brief: "Report: (a) requirements the spec asked for that are missing or partial; (b) behaviour in the diff that wasn't asked for (scope creep); (c) requirements that look implemented but where the implementation looks wrong. Quote the spec line for each finding. Under 400 words."
If the spec is missing, skip the Spec sub-agent and note this in the final report.
### 5. Aggregate
Present the two reports under `## Standards` and `## Spec` headings, verbatim or lightly cleaned. Do **not** merge or rerank findings — the two axes are deliberately separate (see _Why two axes_).
End with a one-line summary: total findings per axis, and the worst issue _within each axis_ (if any). Don't pick a single winner across axes — that's the reranking the separation exists to prevent.
## Why two axes
A change can pass one axis and fail the other:
- Code that follows every standard but implements the wrong thing → **Standards pass, Spec fail.**
- Code that does exactly what the issue asked but breaks the project's conventions → **Spec pass, Standards fail.**
Reporting them separately stops one axis from masking the other.

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interface:
display_name: "Code Review"
short_description: "Review a diff on standards and spec"

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# Deepening
How to deepen a cluster of shallow modules safely, given its dependencies. Assumes the vocabulary in [SKILL.md](SKILL.md) — **module**, **interface**, **seam**, **adapter**.
## Dependency categories
When assessing a candidate for deepening, classify its dependencies. The category determines how the deepened module is tested across its seam.
### 1. In-process
Pure computation, in-memory state, no I/O. Always deepenable — merge the modules and test through the new interface directly. No adapter needed.
### 2. Local-substitutable
Dependencies that have local test stand-ins (PGLite for Postgres, in-memory filesystem). Deepenable if the stand-in exists. The deepened module is tested with the stand-in running in the test suite. The seam is internal; no port at the module's external interface.
### 3. Remote but owned (Ports & Adapters)
Your own services across a network boundary (microservices, internal APIs). Define a **port** (interface) at the seam. The deep module owns the logic; the transport is injected as an **adapter**. Tests use an in-memory adapter. Production uses an HTTP/gRPC/queue adapter.
Recommendation shape: *"Define a port at the seam, implement an HTTP adapter for production and an in-memory adapter for testing, so the logic sits in one deep module even though it's deployed across a network."*
### 4. True external (Mock)
Third-party services (Stripe, Twilio, etc.) you don't control. The deepened module takes the external dependency as an injected port; tests provide a mock adapter.
## Seam discipline
- **One adapter means a hypothetical seam. Two adapters means a real one.** Don't introduce a port unless at least two adapters are justified (typically production + test). A single-adapter seam is just indirection.
- **Internal seams vs external seams.** A deep module can have internal seams (private to its implementation, used by its own tests) as well as the external seam at its interface. Don't expose internal seams through the interface just because tests use them.
## Testing strategy: replace, don't layer
- Old unit tests on shallow modules become waste once tests at the deepened module's interface exist — delete them.
- Write new tests at the deepened module's interface. The **interface is the test surface**.
- Tests assert on observable outcomes through the interface, not internal state.
- Tests should survive internal refactors — they describe behaviour, not implementation. If a test has to change when the implementation changes, it's testing past the interface.

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# Design It Twice
When the user wants to explore alternative interfaces for a chosen deepening candidate, use this parallel sub-agent pattern. Based on "Design It Twice" (Ousterhout) — your first idea is unlikely to be the best.
Uses the vocabulary in [SKILL.md](SKILL.md) — **module**, **interface**, **seam**, **adapter**, **leverage**.
## Process
### 1. Frame the problem space
Before spawning sub-agents, write a user-facing explanation of the problem space for the chosen candidate:
- The constraints any new interface would need to satisfy
- The dependencies it would rely on, and which category they fall into (see [DEEPENING.md](DEEPENING.md))
- A rough illustrative code sketch to ground the constraints — not a proposal, just a way to make the constraints concrete
Show this to the user, then immediately proceed to Step 2. The user reads and thinks while the sub-agents work in parallel.
### 2. Spawn sub-agents
Spawn 3+ sub-agents in parallel using the Agent tool. Each must produce a **radically different** interface for the deepened module.
Prompt each sub-agent with a separate technical brief (file paths, coupling details, dependency category from [DEEPENING.md](DEEPENING.md), what sits behind the seam). The brief is independent of the user-facing problem-space explanation in Step 1. Give each agent a different design constraint:
- Agent 1: "Minimize the interface — aim for 13 entry points max. Maximise leverage per entry point."
- Agent 2: "Maximise flexibility — support many use cases and extension."
- Agent 3: "Optimise for the most common caller — make the default case trivial."
- Agent 4 (if applicable): "Design around ports & adapters for cross-seam dependencies."
Include both [SKILL.md](SKILL.md) vocabulary and CONTEXT.md vocabulary in the brief so each sub-agent names things consistently with the architecture language and the project's domain language.
Each sub-agent outputs:
1. Interface (types, methods, params — plus invariants, ordering, error modes)
2. Usage example showing how callers use it
3. What the implementation hides behind the seam
4. Dependency strategy and adapters (see [DEEPENING.md](DEEPENING.md))
5. Trade-offs — where leverage is high, where it's thin
### 3. Present and compare
Present designs sequentially so the user can absorb each one, then compare them in prose. Contrast by **depth** (leverage at the interface), **locality** (where change concentrates), and **seam placement**.
After comparing, give your own recommendation: which design you think is strongest and why. If elements from different designs would combine well, propose a hybrid. Be opinionated — the user wants a strong read, not a menu.

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---
name: codebase-design
description: Shared vocabulary for designing deep modules. Use when the user wants to design or improve a module's interface, find deepening opportunities, decide where a seam goes, make code more testable or AI-navigable, or when another skill needs the deep-module vocabulary.
---
# Codebase Design
Design **deep modules**: a lot of behaviour behind a small interface, placed at a clean seam, testable through that interface. Use this language and these principles wherever code is being designed or restructured. The aim is leverage for callers, locality for maintainers, and testability for everyone.
## Glossary
Use these terms exactly — don't substitute "component," "service," "API," or "boundary." Consistent language is the whole point.
**Module** — anything with an interface and an implementation. Deliberately scale-agnostic: a function, class, package, or tier-spanning slice. _Avoid_: unit, component, service.
**Interface** — everything a caller must know to use the module correctly: the type signature, but also invariants, ordering constraints, error modes, required configuration, and performance characteristics. _Avoid_: API, signature (too narrow — they refer only to the type-level surface).
**Implementation** — what's inside a module, its body of code. Distinct from **Adapter**: a thing can be a small adapter with a large implementation (a Postgres repo) or a large adapter with a small implementation (an in-memory fake). Reach for "adapter" when the seam is the topic; "implementation" otherwise.
**Depth** — leverage at the interface: the amount of behaviour a caller (or test) can exercise per unit of interface they have to learn. A module is **deep** when a large amount of behaviour sits behind a small interface, **shallow** when the interface is nearly as complex as the implementation.
**Seam** _(Michael Feathers)_ — a place where you can alter behaviour without editing in that place; the *location* at which a module's interface lives. Where to put the seam is its own design decision, distinct from what goes behind it. _Avoid_: boundary (overloaded with DDD's bounded context).
**Adapter** — a concrete thing that satisfies an interface at a seam. Describes *role* (what slot it fills), not substance (what's inside).
**Leverage** — what callers get from depth: more capability per unit of interface they learn. One implementation pays back across N call sites and M tests.
**Locality** — what maintainers get from depth: change, bugs, knowledge, and verification concentrate in one place rather than spreading across callers. Fix once, fixed everywhere.
## Deep vs shallow
**Deep module** = small interface + lots of implementation:
```
┌─────────────────────┐
│ Small Interface │ ← Few methods, simple params
├─────────────────────┤
│ │
│ Deep Implementation│ ← Complex logic hidden
│ │
└─────────────────────┘
```
**Shallow module** = large interface + little implementation (avoid):
```
┌─────────────────────────────────┐
│ Large Interface │ ← Many methods, complex params
├─────────────────────────────────┤
│ Thin Implementation │ ← Just passes through
└─────────────────────────────────┘
```
When designing an interface, ask:
- Can I reduce the number of methods?
- Can I simplify the parameters?
- Can I hide more complexity inside?
## Principles
- **Depth is a property of the interface, not the implementation.** A deep module can be internally composed of small, mockable, swappable parts — they just aren't part of the interface. A module can have **internal seams** (private to its implementation, used by its own tests) as well as the **external seam** at its interface.
- **The deletion test.** Imagine deleting the module. If complexity vanishes, it was a pass-through. If complexity reappears across N callers, it was earning its keep.
- **The interface is the test surface.** Callers and tests cross the same seam. If you want to test *past* the interface, the module is probably the wrong shape.
- **One adapter means a hypothetical seam. Two adapters means a real one.** Don't introduce a seam unless something actually varies across it.
## Designing for testability
Good interfaces make testing natural:
1. **Accept dependencies, don't create them.**
```typescript
// Testable
function processOrder(order, paymentGateway) {}
// Hard to test
function processOrder(order) {
const gateway = new StripeGateway();
}
```
2. **Return results, don't produce side effects.**
```typescript
// Testable
function calculateDiscount(cart): Discount {}
// Hard to test
function applyDiscount(cart): void {
cart.total -= discount;
}
```
3. **Small surface area.** Fewer methods = fewer tests needed. Fewer params = simpler test setup.
## Relationships
- A **Module** has exactly one **Interface** (the surface it presents to callers and tests).
- **Depth** is a property of a **Module**, measured against its **Interface**.
- A **Seam** is where a **Module**'s **Interface** lives.
- An **Adapter** sits at a **Seam** and satisfies the **Interface**.
- **Depth** produces **Leverage** for callers and **Locality** for maintainers.
## Rejected framings
- **Depth as ratio of implementation-lines to interface-lines** (Ousterhout): rewards padding the implementation. We use depth-as-leverage instead.
- **"Interface" as the TypeScript `interface` keyword or a class's public methods**: too narrow — interface here includes every fact a caller must know.
- **"Boundary"**: overloaded with DDD's bounded context. Say **seam** or **interface**.
## Going deeper
- **Deepening a cluster given its dependencies** — see [DEEPENING.md](DEEPENING.md): dependency categories, seam discipline, and replace-don't-layer testing.
- **Exploring alternative interfaces** — see [DESIGN-IT-TWICE.md](DESIGN-IT-TWICE.md): spin up parallel sub-agents to design the interface several radically different ways, then compare on depth, locality, and seam placement.

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interface:
display_name: "Codebase Design"
short_description: "Vocabulary for deep-module design"

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---
name: design-an-interface
description: Generate multiple radically different interface designs for a module using parallel sub-agents. Use when user wants to design an API, explore interface options, compare module shapes, or mentions "design it twice".
---
# Design an Interface
Based on "Design It Twice" from "A Philosophy of Software Design": your first idea is unlikely to be the best. Generate multiple radically different designs, then compare.
## Workflow
### 1. Gather Requirements
Before designing, understand:
- [ ] What problem does this module solve?
- [ ] Who are the callers? (other modules, external users, tests)
- [ ] What are the key operations?
- [ ] Any constraints? (performance, compatibility, existing patterns)
- [ ] What should be hidden inside vs exposed?
Ask: "What does this module need to do? Who will use it?"
### 2. Generate Designs (Parallel Sub-Agents)
Spawn 3+ sub-agents simultaneously using Task tool. Each must produce a **radically different** approach.
```
Prompt template for each sub-agent:
Design an interface for: [module description]
Requirements: [gathered requirements]
Constraints for this design: [assign a different constraint to each agent]
- Agent 1: "Minimize method count - aim for 1-3 methods max"
- Agent 2: "Maximize flexibility - support many use cases"
- Agent 3: "Optimize for the most common case"
- Agent 4: "Take inspiration from [specific paradigm/library]"
Output format:
1. Interface signature (types/methods)
2. Usage example (how caller uses it)
3. What this design hides internally
4. Trade-offs of this approach
```
### 3. Present Designs
Show each design with:
1. **Interface signature** - types, methods, params
2. **Usage examples** - how callers actually use it in practice
3. **What it hides** - complexity kept internal
Present designs sequentially so user can absorb each approach before comparison.
### 4. Compare Designs
After showing all designs, compare them on:
- **Interface simplicity**: fewer methods, simpler params
- **General-purpose vs specialized**: flexibility vs focus
- **Implementation efficiency**: does shape allow efficient internals?
- **Depth**: small interface hiding significant complexity (good) vs large interface with thin implementation (bad)
- **Ease of correct use** vs **ease of misuse**
Discuss trade-offs in prose, not tables. Highlight where designs diverge most.
### 5. Synthesize
Often the best design combines insights from multiple options. Ask:
- "Which design best fits your primary use case?"
- "Any elements from other designs worth incorporating?"
## Evaluation Criteria
From "A Philosophy of Software Design":
**Interface simplicity**: Fewer methods, simpler params = easier to learn and use correctly.
**General-purpose**: Can handle future use cases without changes. But beware over-generalization.
**Implementation efficiency**: Does interface shape allow efficient implementation? Or force awkward internals?
**Depth**: Small interface hiding significant complexity = deep module (good). Large interface with thin implementation = shallow module (avoid).
## Anti-Patterns
- Don't let sub-agents produce similar designs - enforce radical difference
- Don't skip comparison - the value is in contrast
- Don't implement - this is purely about interface shape
- Don't evaluate based on implementation effort

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interface:
display_name: "Design an Interface"
short_description: "Explore alternative module interfaces"

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---
name: diagnosing-bugs
description: Diagnosis loop for hard bugs and performance regressions. Use when the user says "diagnose"/"debug this", or reports something broken/throwing/failing/slow.
---
# Diagnosing Bugs
A discipline for hard bugs. Skip phases only when explicitly justified.
When exploring the codebase, read `CONTEXT.md` (if it exists) to get a clear mental model of the relevant modules, and check ADRs in the area you're touching.
## Phase 1 — Build a feedback loop
**This is the skill.** Everything else is mechanical. If you have a **tight** pass/fail signal for the bug — one that goes red on _this_ bug — you will find the cause; bisection, hypothesis-testing, and instrumentation all just consume it. If you don't have one, no amount of staring at code will save you.
Spend disproportionate effort here. **Be aggressive. Be creative. Refuse to give up.**
### Ways to construct one — try them in roughly this order
1. **Failing test** at whatever seam reaches the bug — unit, integration, e2e.
2. **Curl / HTTP script** against a running dev server.
3. **CLI invocation** with a fixture input, diffing stdout against a known-good snapshot.
4. **Headless browser script** (Playwright / Puppeteer) — drives the UI, asserts on DOM/console/network.
5. **Replay a captured trace.** Save a real network request / payload / event log to disk; replay it through the code path in isolation.
6. **Throwaway harness.** Spin up a minimal subset of the system (one service, mocked deps) that exercises the bug code path with a single function call.
7. **Property / fuzz loop.** If the bug is "sometimes wrong output", run 1000 random inputs and look for the failure mode.
8. **Bisection harness.** If the bug appeared between two known states (commit, dataset, version), automate "boot at state X, check, repeat" so you can `git bisect run` it.
9. **Differential loop.** Run the same input through old-version vs new-version (or two configs) and diff outputs.
10. **HITL bash script.** Last resort. If a human must click, drive _them_ with `scripts/hitl-loop.template.sh` so the loop is still structured. Captured output feeds back to you.
Build the right feedback loop, and the bug is 90% fixed.
### Tighten the loop
Treat the loop as a product. Once you have _a_ loop, **tighten** it:
- Can I make it faster? (Cache setup, skip unrelated init, narrow the test scope.)
- Can I make the signal sharper? (Assert on the specific symptom, not "didn't crash".)
- Can I make it more deterministic? (Pin time, seed RNG, isolate filesystem, freeze network.)
A 30-second flaky loop is barely better than no loop; a 2-second deterministic one is tight — a debugging superpower.
### Non-deterministic bugs
The goal is not a clean repro but a **higher reproduction rate**. Loop the trigger 100×, parallelise, add stress, narrow timing windows, inject sleeps. A 50%-flake bug is debuggable; 1% is not — keep raising the rate until it's debuggable.
### When you genuinely cannot build a loop
Stop and say so explicitly. List what you tried. Ask the user for: (a) access to whatever environment reproduces it, (b) a captured artifact (HAR file, log dump, core dump, screen recording with timestamps), or (c) permission to add temporary production instrumentation. Do **not** proceed to hypothesise without a loop.
### Completion criterion — a tight loop that goes red
Phase 1 is done when the loop is **tight** and **red-capable**: you can name **one command** — a script path, a test invocation, a curl — that you have **already run at least once** (paste the invocation and its output), and that is:
- [ ] **Red-capable** — it drives the actual bug code path and asserts the **user's exact symptom**, so it can go red on this bug and green once fixed. Not "runs without erroring" — it must be able to _catch this specific bug_.
- [ ] **Deterministic** — same verdict every run (flaky bugs: a pinned, high reproduction rate, per above).
- [ ] **Fast** — seconds, not minutes.
- [ ] **Agent-runnable** — you can run it unattended; a human in the loop only via `scripts/hitl-loop.template.sh`.
If you catch yourself reading code to build a theory before this command exists, **stop — jumping straight to a hypothesis is the exact failure this skill prevents.** No red-capable command, no Phase 2.
## Phase 2 — Reproduce + minimise
Run the loop. Watch it go red — the bug appears.
Confirm:
- [ ] The loop produces the failure mode the **user** described — not a different failure that happens to be nearby. Wrong bug = wrong fix.
- [ ] The failure is reproducible across multiple runs (or, for non-deterministic bugs, reproducible at a high enough rate to debug against).
- [ ] You have captured the exact symptom (error message, wrong output, slow timing) so later phases can verify the fix actually addresses it.
### Minimise
Once it's red, shrink the repro to the **smallest scenario that still goes red**. Cut inputs, callers, config, data, and steps **one at a time**, re-running the loop after each cut — keep only what's load-bearing for the failure.
Why bother: a minimal repro shrinks the hypothesis space in Phase 3 (fewer moving parts left to suspect) and becomes the clean regression test in Phase 5.
Done when **every remaining element is load-bearing** — removing any one of them makes the loop go green.
Do not proceed until you have reproduced **and** minimised.
## Phase 3 — Hypothesise
Generate **35 ranked hypotheses** before testing any of them. Single-hypothesis generation anchors on the first plausible idea.
Each hypothesis must be **falsifiable**: state the prediction it makes.
> Format: "If <X> is the cause, then <changing Y> will make the bug disappear / <changing Z> will make it worse."
If you cannot state the prediction, the hypothesis is a vibe — discard or sharpen it.
**Show the ranked list to the user before testing.** They often have domain knowledge that re-ranks instantly ("we just deployed a change to #3"), or know hypotheses they've already ruled out. Cheap checkpoint, big time saver. Don't block on it — proceed with your ranking if the user is AFK.
## Phase 4 — Instrument
Each probe must map to a specific prediction from Phase 3. **Change one variable at a time.**
Tool preference:
1. **Debugger / REPL inspection** if the env supports it. One breakpoint beats ten logs.
2. **Targeted logs** at the boundaries that distinguish hypotheses.
3. Never "log everything and grep".
**Tag every debug log** with a unique prefix, e.g. `[DEBUG-a4f2]`. Cleanup at the end becomes a single grep. Untagged logs survive; tagged logs die.
**Perf branch.** For performance regressions, logs are usually wrong. Instead: establish a baseline measurement (timing harness, `performance.now()`, profiler, query plan), then bisect. Measure first, fix second.
## Phase 5 — Fix + regression test
Write the regression test **before the fix** — but only if there is a **correct seam** for it.
A correct seam is one where the test exercises the **real bug pattern** as it occurs at the call site. If the only available seam is too shallow (single-caller test when the bug needs multiple callers, unit test that can't replicate the chain that triggered the bug), a regression test there gives false confidence.
**If no correct seam exists, that itself is the finding.** Note it. The codebase architecture is preventing the bug from being locked down. Flag this for the next phase.
If a correct seam exists:
1. Turn the minimised repro into a failing test at that seam.
2. Watch it fail.
3. Apply the fix.
4. Watch it pass.
5. Re-run the Phase 1 feedback loop against the original (un-minimised) scenario.
## Phase 6 — Cleanup + post-mortem
Required before declaring done:
- [ ] Original repro no longer reproduces (re-run the Phase 1 loop)
- [ ] Regression test passes (or absence of seam is documented)
- [ ] All `[DEBUG-...]` instrumentation removed (`grep` the prefix)
- [ ] Throwaway prototypes deleted (or moved to a clearly-marked debug location)
- [ ] The hypothesis that turned out correct is stated in the commit / PR message — so the next debugger learns
**Then ask: what would have prevented this bug?** If the answer involves architectural change (no good test seam, tangled callers, hidden coupling) hand off to the `/improve-codebase-architecture` skill with the specifics. Make the recommendation **after** the fix is in, not before — you have more information now than when you started.

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interface:
display_name: "Diagnosing Bugs"
short_description: "Diagnose hard bugs and regressions"

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#!/usr/bin/env bash
# Human-in-the-loop reproduction loop.
# Copy this file, edit the steps below, and run it.
# The agent runs the script; the user follows prompts in their terminal.
#
# Usage:
# bash hitl-loop.template.sh
#
# Two helpers:
# step "<instruction>" → show instruction, wait for Enter
# capture VAR "<question>" → show question, read response into VAR
#
# At the end, captured values are printed as KEY=VALUE for the agent to parse.
set -euo pipefail
step() {
printf '\n>>> %s\n' "$1"
read -r -p " [Enter when done] " _
}
capture() {
local var="$1" question="$2" answer
printf '\n>>> %s\n' "$question"
read -r -p " > " answer
printf -v "$var" '%s' "$answer"
}
# --- edit below ---------------------------------------------------------
step "Open the app at http://localhost:3000 and sign in."
capture ERRORED "Click the 'Export' button. Did it throw an error? (y/n)"
capture ERROR_MSG "Paste the error message (or 'none'):"
# --- edit above ---------------------------------------------------------
printf '\n--- Captured ---\n'
printf 'ERRORED=%s\n' "$ERRORED"
printf 'ERROR_MSG=%s\n' "$ERROR_MSG"

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# ADR Format
ADRs live in `docs/adr/` and use sequential numbering: `0001-slug.md`, `0002-slug.md`, etc.
Create the `docs/adr/` directory lazily — only when the first ADR is needed.
## Template
```md
# {Short title of the decision}
{1-3 sentences: what's the context, what did we decide, and why.}
```
That's it. An ADR can be a single paragraph. The value is in recording *that* a decision was made and *why* — not in filling out sections.
## Optional sections
Only include these when they add genuine value. Most ADRs won't need them.
- **Status** frontmatter (`proposed | accepted | deprecated | superseded by ADR-NNNN`) — useful when decisions are revisited
- **Considered Options** — only when the rejected alternatives are worth remembering
- **Consequences** — only when non-obvious downstream effects need to be called out
## Numbering
Scan `docs/adr/` for the highest existing number and increment by one.
## When to offer an ADR
All three of these must be true:
1. **Hard to reverse** — the cost of changing your mind later is meaningful
2. **Surprising without context** — a future reader will look at the code and wonder "why on earth did they do it this way?"
3. **The result of a real trade-off** — there were genuine alternatives and you picked one for specific reasons
If a decision is easy to reverse, skip it — you'll just reverse it. If it's not surprising, nobody will wonder why. If there was no real alternative, there's nothing to record beyond "we did the obvious thing."
### What qualifies
- **Architectural shape.** "We're using a monorepo." "The write model is event-sourced, the read model is projected into Postgres."
- **Integration patterns between contexts.** "Ordering and Billing communicate via domain events, not synchronous HTTP."
- **Technology choices that carry lock-in.** Database, message bus, auth provider, deployment target. Not every library — just the ones that would take a quarter to swap out.
- **Boundary and scope decisions.** "Customer data is owned by the Customer context; other contexts reference it by ID only." The explicit no-s are as valuable as the yes-s.
- **Deliberate deviations from the obvious path.** "We're using manual SQL instead of an ORM because X." Anything where a reasonable reader would assume the opposite. These stop the next engineer from "fixing" something that was deliberate.
- **Constraints not visible in the code.** "We can't use AWS because of compliance requirements." "Response times must be under 200ms because of the partner API contract."
- **Rejected alternatives when the rejection is non-obvious.** If you considered GraphQL and picked REST for subtle reasons, record it — otherwise someone will suggest GraphQL again in six months.

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# CONTEXT.md Format
## Structure
```md
# {Context Name}
{One or two sentence description of what this context is and why it exists.}
## Language
**Order**:
{A one or two sentence description of the term}
_Avoid_: Purchase, transaction
**Invoice**:
A request for payment sent to a customer after delivery.
_Avoid_: Bill, payment request
**Customer**:
A person or organization that places orders.
_Avoid_: Client, buyer, account
```
## Rules
- **Be opinionated.** When multiple words exist for the same concept, pick the best one and list the others under `_Avoid_`.
- **Keep definitions tight.** One or two sentences max. Define what it IS, not what it does.
- **Only include terms specific to this project's context.** General programming concepts (timeouts, error types, utility patterns) don't belong even if the project uses them extensively. Before adding a term, ask: is this a concept unique to this context, or a general programming concept? Only the former belongs.
- **Group terms under subheadings** when natural clusters emerge. If all terms belong to a single cohesive area, a flat list is fine.
## Single vs multi-context repos
**Single context (most repos):** One `CONTEXT.md` at the repo root.
**Multiple contexts:** A `CONTEXT-MAP.md` at the repo root lists the contexts, where they live, and how they relate to each other:
```md
# Context Map
## Contexts
- [Ordering](./src/ordering/CONTEXT.md) — receives and tracks customer orders
- [Billing](./src/billing/CONTEXT.md) — generates invoices and processes payments
- [Fulfillment](./src/fulfillment/CONTEXT.md) — manages warehouse picking and shipping
## Relationships
- **Ordering → Fulfillment**: Ordering emits `OrderPlaced` events; Fulfillment consumes them to start picking
- **Fulfillment → Billing**: Fulfillment emits `ShipmentDispatched` events; Billing consumes them to generate invoices
- **Ordering ↔ Billing**: Shared types for `CustomerId` and `Money`
```
The skill infers which structure applies:
- If `CONTEXT-MAP.md` exists, read it to find contexts
- If only a root `CONTEXT.md` exists, single context
- If neither exists, create a root `CONTEXT.md` lazily when the first term is resolved
When multiple contexts exist, infer which one the current topic relates to. If unclear, ask.

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---
name: domain-modeling
description: Build and sharpen a project's domain model. Use when the user wants to pin down domain terminology or a ubiquitous language, record an architectural decision, or when another skill needs to maintain the domain model.
---
# Domain Modeling
Actively build and sharpen the project's domain model as you design. This is the *active* discipline — challenging terms, inventing edge-case scenarios, and writing the glossary and decisions down the moment they crystallise. (Merely *reading* `CONTEXT.md` for vocabulary is not this skill — that's a one-line habit any skill can do. This skill is for when you're changing the model, not just consuming it.)
## File structure
Most repos have a single context:
```
/
├── CONTEXT.md
├── docs/
│ └── adr/
│ ├── 0001-event-sourced-orders.md
│ └── 0002-postgres-for-write-model.md
└── src/
```
If a `CONTEXT-MAP.md` exists at the root, the repo has multiple contexts. The map points to where each one lives:
```
/
├── CONTEXT-MAP.md
├── docs/
│ └── adr/ ← system-wide decisions
├── src/
│ ├── ordering/
│ │ ├── CONTEXT.md
│ │ └── docs/adr/ ← context-specific decisions
│ └── billing/
│ ├── CONTEXT.md
│ └── docs/adr/
```
Create files lazily — only when you have something to write. If no `CONTEXT.md` exists, create one when the first term is resolved. If no `docs/adr/` exists, create it when the first ADR is needed.
## During the session
### Challenge against the glossary
When the user uses a term that conflicts with the existing language in `CONTEXT.md`, call it out immediately. "Your glossary defines 'cancellation' as X, but you seem to mean Y — which is it?"
### Sharpen fuzzy language
When the user uses vague or overloaded terms, propose a precise canonical term. "You're saying 'account' — do you mean the Customer or the User? Those are different things."
### Discuss concrete scenarios
When domain relationships are being discussed, stress-test them with specific scenarios. Invent scenarios that probe edge cases and force the user to be precise about the boundaries between concepts.
### Cross-reference with code
When the user states how something works, check whether the code agrees. If you find a contradiction, surface it: "Your code cancels entire Orders, but you just said partial cancellation is possible — which is right?"
### Update CONTEXT.md inline
When a term is resolved, update `CONTEXT.md` right there. Don't batch these up — capture them as they happen. Use the format in [CONTEXT-FORMAT.md](./CONTEXT-FORMAT.md).
`CONTEXT.md` should be totally devoid of implementation details. Do not treat `CONTEXT.md` as a spec, a scratch pad, or a repository for implementation decisions. It is a glossary and nothing else.
### Offer ADRs sparingly
Only offer to create an ADR when all three are true:
1. **Hard to reverse** — the cost of changing your mind later is meaningful
2. **Surprising without context** — a future reader will wonder "why did they do it this way?"
3. **The result of a real trade-off** — there were genuine alternatives and you picked one for specific reasons
If any of the three is missing, skip the ADR. Use the format in [ADR-FORMAT.md](./ADR-FORMAT.md).

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interface:
display_name: "Domain Modeling"
short_description: "Build and sharpen a domain model"

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---
name: edit-article
description: Edit and improve articles by restructuring sections, improving clarity, and tightening prose. Use when user wants to edit, revise, or improve an article draft.
disable-model-invocation: true
---
1. First, divide the article into sections based on its headings. Think about the main points you want to make during those sections.
Consider that information is a directed acyclic graph, and that pieces of information can depend on other pieces of information. Make sure that the order of the sections and their contents respects these dependencies.
Confirm the sections with the user.
2. For each section:
2a. Rewrite the section to improve clarity, coherence, and flow. Use maximum 240 characters per paragraph.

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interface:
display_name: "Edit Article"
short_description: "Restructure and tighten a draft"
policy:
allow_implicit_invocation: false

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---
name: git-guardrails-claude-code
description: Set up Claude Code hooks to block dangerous git commands (push, reset --hard, clean, branch -D, etc.) before they execute. Use when user wants to prevent destructive git operations, add git safety hooks, or block git push/reset in Claude Code.
---
# Setup Git Guardrails
Sets up a PreToolUse hook that intercepts and blocks dangerous git commands before Claude executes them.
## What Gets Blocked
- `git push` (all variants including `--force`)
- `git reset --hard`
- `git clean -f` / `git clean -fd`
- `git branch -D`
- `git checkout .` / `git restore .`
When blocked, Claude sees a message telling it that it does not have authority to access these commands.
## Steps
### 1. Ask scope
Ask the user: install for **this project only** (`.claude/settings.json`) or **all projects** (`~/.claude/settings.json`)?
### 2. Copy the hook script
The bundled script is at: [scripts/block-dangerous-git.sh](scripts/block-dangerous-git.sh)
Copy it to the target location based on scope:
- **Project**: `.claude/hooks/block-dangerous-git.sh`
- **Global**: `~/.claude/hooks/block-dangerous-git.sh`
Make it executable with `chmod +x`.
### 3. Add hook to settings
Add to the appropriate settings file:
**Project** (`.claude/settings.json`):
```json
{
"hooks": {
"PreToolUse": [
{
"matcher": "Bash",
"hooks": [
{
"type": "command",
"command": "\"$CLAUDE_PROJECT_DIR\"/.claude/hooks/block-dangerous-git.sh"
}
]
}
]
}
}
```
**Global** (`~/.claude/settings.json`):
```json
{
"hooks": {
"PreToolUse": [
{
"matcher": "Bash",
"hooks": [
{
"type": "command",
"command": "~/.claude/hooks/block-dangerous-git.sh"
}
]
}
]
}
}
```
If the settings file already exists, merge the hook into existing `hooks.PreToolUse` array — don't overwrite other settings.
### 4. Ask about customization
Ask if user wants to add or remove any patterns from the blocked list. Edit the copied script accordingly.
### 5. Verify
Run a quick test:
```bash
echo '{"tool_input":{"command":"git push origin main"}}' | <path-to-script>
```
Should exit with code 2 and print a BLOCKED message to stderr.

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interface:
display_name: "Git Guardrails for Claude Code"
short_description: "Block dangerous git commands"

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#!/bin/bash
INPUT=$(cat)
COMMAND=$(echo "$INPUT" | jq -r '.tool_input.command')
DANGEROUS_PATTERNS=(
"git push"
"git reset --hard"
"git clean -fd"
"git clean -f"
"git branch -D"
"git checkout \."
"git restore \."
"push --force"
"reset --hard"
)
for pattern in "${DANGEROUS_PATTERNS[@]}"; do
if echo "$COMMAND" | grep -qE "$pattern"; then
echo "BLOCKED: '$COMMAND' matches dangerous pattern '$pattern'. The user has prevented you from doing this." >&2
exit 2
fi
done
exit 0

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---
name: grill-me
description: A relentless interview to sharpen a plan or design.
disable-model-invocation: true
---
Run a `/grilling` session.

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interface:
display_name: "Grill Me"
short_description: "Sharpen a plan through interview"
policy:
allow_implicit_invocation: false

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---
name: grill-with-docs
description: A relentless interview to sharpen a plan or design, which also creates docs (ADR's and glossary) as we go.
disable-model-invocation: true
---
Run a `/grilling` session, using the `/domain-modeling` skill.

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interface:
display_name: "Grill with Docs"
short_description: "Grill a design and write its docs"
policy:
allow_implicit_invocation: false

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---
name: grilling
description: Grill the user relentlessly about a plan, decision, or idea. Use when the user wants to stress-test their thinking, or uses any 'grill' trigger phrases.
---
Interview me relentlessly about every aspect of this until we reach a shared understanding. Walk down each branch of the decision tree, resolving dependencies between decisions one-by-one. For each question, provide your recommended answer.
Ask the questions one at a time, waiting for feedback on each question before continuing. Asking multiple questions at once is bewildering.
If a *fact* can be found by exploring the environment (filesystem, tools, etc.), look it up rather than asking me. The *decisions*, though, are mine — put each one to me and wait for my answer.
Do not act on it until I confirm we have reached a shared understanding.

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interface:
display_name: "Grilling"
short_description: "Stress-test thinking one question at a time"

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---
name: handoff
description: Compact the current conversation into a handoff document for another agent to pick up.
argument-hint: "What will the next session be used for?"
disable-model-invocation: true
---
Write a handoff document summarising the current conversation so a fresh agent can continue the work. Save to the temporary directory of the user's OS - not the current workspace.
Include a "suggested skills" section in the document, which suggests skills that the agent should invoke.
Do not duplicate content already captured in other artifacts (specs, plans, ADRs, issues, commits, diffs). Reference them by path or URL instead.
Redact any sensitive information, such as API keys, passwords, or personally identifiable information.
If the user passed arguments, treat them as a description of what the next session will focus on and tailor the doc accordingly.

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interface:
display_name: "Handoff"
short_description: "Compact a conversation into a handoff"
policy:
allow_implicit_invocation: false

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---
name: implement
description: "Implement a piece of work based on a spec or set of tickets."
disable-model-invocation: true
---
Implement the work described by the user in the spec or tickets.
Use /tdd where possible, at pre-agreed seams.
Run typechecking regularly, single test files regularly, and the full test suite once at the end.
Once done, use /code-review to review the work.
Commit your work to the current branch.

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interface:
display_name: "Implement"
short_description: "Build work from a spec or tickets"
policy:
allow_implicit_invocation: false

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# HTML Report Format
The architectural review is rendered as a single self-contained HTML file in the OS temp directory. Tailwind and Mermaid both come from CDNs. Mermaid handles graph-shaped diagrams reliably; hand-built divs and inline SVG handle the more editorial visuals (mass diagrams, cross-sections). Mix the two — don't lean on Mermaid for everything, it'll start to look generic.
## Scaffold
```html
<!doctype html>
<html lang="en">
<head>
<meta charset="utf-8" />
<title>Architecture review — {{repo name}}</title>
<script src="https://cdn.tailwindcss.com"></script>
<script type="module">
import mermaid from "https://cdn.jsdelivr.net/npm/mermaid@11/dist/mermaid.esm.min.mjs";
mermaid.initialize({ startOnLoad: true, theme: "neutral", securityLevel: "loose" });
</script>
<style>
/* small custom layer for things Tailwind doesn't cover cleanly:
dashed seam lines, hand-drawn-feeling arrow heads, etc. */
.seam { stroke-dasharray: 4 4; }
.leak { stroke: #dc2626; }
.deep { background: linear-gradient(135deg, #0f172a, #1e293b); }
</style>
</head>
<body class="bg-stone-50 text-slate-900 font-sans">
<main class="max-w-5xl mx-auto px-6 py-12 space-y-12">
<header>...</header>
<section id="candidates" class="space-y-10">...</section>
<section id="top-recommendation">...</section>
</main>
</body>
</html>
```
## Header
Repo name, date, and a compact legend: solid box = module, dashed line = seam, red arrow = leakage, thick dark box = deep module. No introduction paragraph — straight into the candidates.
## Candidate card
The diagrams carry the weight. Prose is sparse, plain, and uses the glossary terms (from the `/codebase-design` skill) without ceremony.
Each candidate is one `<article>`:
- **Title** — short, names the deepening (e.g. "Collapse the Order intake pipeline").
- **Badge row** — recommendation strength (`Strong` = emerald, `Worth exploring` = amber, `Speculative` = slate), plus a tag for the dependency category (`in-process`, `local-substitutable`, `ports & adapters`, `mock`).
- **Files** — monospaced list, `font-mono text-sm`.
- **Before / After diagram** — the centrepiece. Two columns, side by side. See patterns below.
- **Problem** — one sentence. What hurts.
- **Solution** — one sentence. What changes.
- **Wins** — bullets, ≤6 words each. e.g. "Tests hit one interface", "Pricing logic stops leaking", "Delete 4 shallow wrappers".
- **ADR callout** (if applicable) — one line in an amber-tinted box.
No paragraphs of explanation. If the diagram needs a paragraph to be understood, redraw the diagram.
## Diagram patterns
Pick the pattern that fits the candidate. Mix them. Don't make every diagram look the same — variety is part of the point.
### Mermaid graph (the workhorse for dependencies / call flow)
Use a Mermaid `flowchart` or `graph` when the point is "X calls Y calls Z, and look at the mess." Wrap it in a Tailwind-styled card so it doesn't feel parachuted in. Style with classDef to colour leakage edges red and the deep module dark. Sequence diagrams work well for "before: 6 round-trips; after: 1."
```html
<div class="rounded-lg border border-slate-200 bg-white p-4">
<pre class="mermaid">
flowchart LR
A[OrderHandler] --> B[OrderValidator]
B --> C[OrderRepo]
C -.leak.-> D[PricingClient]
classDef leak stroke:#dc2626,stroke-width:2px;
class C,D leak
</pre>
</div>
```
### Hand-built boxes-and-arrows (when Mermaid's layout fights you)
Modules as `<div>`s with borders and labels. Arrows as inline SVG `<line>` or `<path>` elements positioned absolutely over a relative container. Reach for this when you want the "after" diagram to feel like one thick-bordered deep module with greyed-out internals — Mermaid won't render that with the right weight.
### Cross-section (good for layered shallowness)
Stack horizontal bands (`h-12 border-l-4`) to show layers a call passes through. Before: 6 thin layers each doing nothing. After: 1 thick band labelled with the consolidated responsibility.
### Mass diagram (good for "interface as wide as implementation")
Two rectangles per module — one for interface surface area, one for implementation. Before: interface rectangle is nearly as tall as the implementation rectangle (shallow). After: interface rectangle is short, implementation rectangle is tall (deep).
### Call-graph collapse
Before: a tree of function calls rendered as nested boxes. After: the same tree collapsed into one box, with the now-internal calls shown faded inside it.
## Style guidance
- Lean editorial, not corporate-dashboard. Generous whitespace. Serif optional for headings (`font-serif` works well with stone/slate).
- Colour sparingly: one accent (emerald or indigo) plus red for leakage and amber for warnings.
- Keep diagrams ~320px tall so before/after sits comfortably side by side without scrolling.
- Use `text-xs uppercase tracking-wider` for module labels inside diagrams — they should read as schematic, not as UI.
- The only scripts are the Tailwind CDN and the Mermaid ESM import. The report is otherwise static — no app code, no interactivity beyond Mermaid's own rendering.
## Top recommendation section
One larger card. Candidate name, one sentence on why, anchor link to its card. That's it.
## Tone
Plain English, concise — but the architectural nouns and verbs come straight from the `/codebase-design` skill. Concision is not an excuse to drift.
**Use exactly:** module, interface, implementation, depth, deep, shallow, seam, adapter, leverage, locality.
**Never substitute:** component, service, unit (for module) · API, signature (for interface) · boundary (for seam) · layer, wrapper (for module, when you mean module).
**Phrasings that fit the style:**
- "Order intake module is shallow — interface nearly matches the implementation."
- "Pricing leaks across the seam."
- "Deepen: one interface, one place to test."
- "Two adapters justify the seam: HTTP in prod, in-memory in tests."
**Wins bullets** name the gain in glossary terms: *"locality: bugs concentrate in one module"*, *"leverage: one interface, N call sites"*, *"interface shrinks; implementation absorbs the wrappers"*. Don't write *"easier to maintain"* or *"cleaner code"* — those terms aren't in the glossary and don't earn their place.
No hedging, no throat-clearing, no "it's worth noting that…". If a sentence could be a bullet, make it a bullet. If a bullet could be cut, cut it. If a term isn't in the `/codebase-design` glossary, reach for one that is before inventing a new one.

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---
name: improve-codebase-architecture
description: Scan a codebase for deepening opportunities, present them as a visual HTML report, then grill through whichever one you pick.
disable-model-invocation: true
---
# Improve Codebase Architecture
Surface architectural friction and propose **deepening opportunities** — refactors that turn shallow modules into deep ones. The aim is testability and AI-navigability.
This command is _informed_ by the project's domain model and built on a shared design vocabulary:
- Run the `/codebase-design` skill for the architecture vocabulary (**module**, **interface**, **depth**, **seam**, **adapter**, **leverage**, **locality**) and its principles (the deletion test, "the interface is the test surface", "one adapter = hypothetical seam, two = real"). Use these terms exactly in every suggestion — don't drift into "component," "service," "API," or "boundary."
- The domain language in `CONTEXT.md` gives names to good seams; ADRs in `docs/adr/` record decisions this command should not re-litigate.
## Process
### 1. Explore
**Scope before you scan — YAGNI.** Deepening a module pays off by making future changes to it easier, so put extra weight on the parts of the codebase that have recently changed. Decide *where* to look before you look:
- If the user named a direction — a module, a subsystem, a pain point — take it, and skip the inference below.
- Otherwise, walk back a good stretch of the commit history (`git log --oneline`) to find the codebase's hot spots — the files and areas that keep coming up — and let those paths pull your attention first. If the changes are scattered with no clear hot spot, widen the net.
Read the project's domain glossary (`CONTEXT.md`) and any ADRs in the area you're touching first.
Then use the Agent tool with `subagent_type=Explore` to walk the codebase. Don't follow rigid heuristics — explore organically and note where you experience friction:
- Where does understanding one concept require bouncing between many small modules?
- Where are modules **shallow** — interface nearly as complex as the implementation?
- Where have pure functions been extracted just for testability, but the real bugs hide in how they're called (no **locality**)?
- Where do tightly-coupled modules leak across their seams?
- Which parts of the codebase are untested, or hard to test through their current interface?
Apply the **deletion test** to anything you suspect is shallow: would deleting it concentrate complexity, or just move it? A "yes, concentrates" is the signal you want.
### 2. Present candidates as an HTML report
Write a self-contained HTML file to the OS temp directory so nothing lands in the repo. Resolve the temp dir from `$TMPDIR`, falling back to `/tmp` (or `%TEMP%` on Windows), and write to `<tmpdir>/architecture-review-<timestamp>.html` so each run gets a fresh file. Open it for the user — `xdg-open <path>` on Linux, `open <path>` on macOS, `start <path>` on Windows — and tell them the absolute path.
The report uses **Tailwind via CDN** for layout and styling, and **Mermaid via CDN** for diagrams where a graph/flow/sequence reliably communicates the structure. Mix Mermaid with hand-crafted CSS/SVG visuals — use Mermaid when relationships are graph-shaped (call graphs, dependencies, sequences), and hand-built divs/SVG when you want something more editorial (mass diagrams, cross-sections, collapse animations). Each candidate gets a **before/after visualisation**. Be visual.
For each candidate, render a card with:
- **Files** — which files/modules are involved
- **Problem** — why the current architecture is causing friction
- **Solution** — plain English description of what would change
- **Benefits** — explained in terms of locality and leverage, and how tests would improve
- **Before / After diagram** — side-by-side, custom-drawn, illustrating the shallowness and the deepening
- **Recommendation strength** — one of `Strong`, `Worth exploring`, `Speculative`, rendered as a badge
End the report with a **Top recommendation** section: which candidate you'd tackle first and why.
**Use CONTEXT.md vocabulary for the domain, and the `/codebase-design` vocabulary for the architecture.** If `CONTEXT.md` defines "Order," talk about "the Order intake module" — not "the FooBarHandler," and not "the Order service."
**ADR conflicts**: if a candidate contradicts an existing ADR, only surface it when the friction is real enough to warrant revisiting the ADR. Mark it clearly in the card (e.g. a warning callout: _"contradicts ADR-0007 — but worth reopening because…"_). Don't list every theoretical refactor an ADR forbids.
See [HTML-REPORT.md](HTML-REPORT.md) for the full HTML scaffold, diagram patterns, and styling guidance.
Do NOT propose interfaces yet. After the file is written, ask the user: "Which of these would you like to explore?"
### 3. Grilling loop
Once the user picks a candidate, run the `/grilling` skill to walk the decision tree with them — constraints, dependencies, the shape of the deepened module, what sits behind the seam, what tests survive.
Side effects happen inline as decisions crystallize — run the `/domain-modeling` skill to keep the domain model current as you go:
- **Naming a deepened module after a concept not in `CONTEXT.md`?** Add the term to `CONTEXT.md`. Create the file lazily if it doesn't exist.
- **Sharpening a fuzzy term during the conversation?** Update `CONTEXT.md` right there.
- **User rejects the candidate with a load-bearing reason?** Offer an ADR, framed as: _"Want me to record this as an ADR so future architecture reviews don't re-suggest it?"_ Only offer when the reason would actually be needed by a future explorer to avoid re-suggesting the same thing — skip ephemeral reasons ("not worth it right now") and self-evident ones.
- **Want to explore alternative interfaces for the deepened module?** Run the `/codebase-design` skill and use its design-it-twice parallel sub-agent pattern.

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interface:
display_name: "Improve Codebase Architecture"
short_description: "Find and grill architecture improvements"
policy:
allow_implicit_invocation: false

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---
name: loop-me
description: Grill me about specs for the workflows I want to build, within this workspace.
disable-model-invocation: true
argument-hint: "A workflow to design, or nothing to go find one"
---
Run a stateful `/grilling` session whose only output is **workflow** specs. Use the grilling discipline — relentless, one question at a time, a recommended answer attached to each — aimed at the vocabulary and goal below. Create, edit, and delete specs as the grilling resolves things.
## The loop lens
A **loop** is a recurring pattern in the user's life: their career, their week, their morning, a single repeated activity. Picturing a life as loops within loops reveals how predictable its activities really are — which is what makes them worth **delegating**. Use the lens to find loops worth specifying, and propose ones the user hasn't noticed.
A **workflow** is the spec of one loop, made real. You run a workflow on a loop — the loop is its running instantiation. Workflows live in `workflows/*.md` and are the source of truth.
## Vocabulary
A shared language, reached for only when a workflow calls for it — never a checklist. **Mandate nothing structural**: a workflow needs no AI, no checkpoint, and no schedule unless the grilling shows it does.
- **Trigger** — what fires each run: an **event** (a new email, a new issue) or a **schedule** (every morning). Event-triggering is usually the more efficient.
- **Checkpoint** — a human-in-the-loop point where the user is asked to verify or decide. Some workflows have none and run autonomously; some use no AI at all.
- **Push right** — defer the checkpoint as far as it will go. Do maximal work before involving the human, so they are asked once, late, with everything prepared.
- **Brief** — what a checkpoint presents: a tight, decision-ready summary — what was produced, why, and a link down to the asset itself — never the raw output. The user reads a brief, not a draft. Speed of review is imperative.
## Definition of done
A workflow spec is done when an implementer agent could build it without asking a single question. Grill until then; nothing is done while a question remains.
## The workspace
- `workflows/*.md` — one spec per workflow.
- `NOTES.md` — raw notes on the user's world: the tools they use, the channels they process, and their own terminology for both. When it is empty or thin, interview them about their world before specifying anything. Sharpen fuzzy terms into canonical ones as they surface, and record them here.

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interface:
display_name: "Loop Me"
short_description: "Spec the workflows you want to build"
policy:
allow_implicit_invocation: false

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---
name: migrate-to-shoehorn
description: Migrate test files from `as` type assertions to @total-typescript/shoehorn. Use when user mentions shoehorn, wants to replace `as` in tests, or needs partial test data.
---
# Migrate to Shoehorn
## Why shoehorn?
`shoehorn` lets you pass partial data in tests while keeping TypeScript happy. It replaces `as` assertions with type-safe alternatives.
**Test code only.** Never use shoehorn in production code.
Problems with `as` in tests:
- Trained not to use it
- Must manually specify target type
- Double-as (`as unknown as Type`) for intentionally wrong data
## Install
```bash
npm i @total-typescript/shoehorn
```
## Migration patterns
### Large objects with few needed properties
Before:
```ts
type Request = {
body: { id: string };
headers: Record<string, string>;
cookies: Record<string, string>;
// ...20 more properties
};
it("gets user by id", () => {
// Only care about body.id but must fake entire Request
getUser({
body: { id: "123" },
headers: {},
cookies: {},
// ...fake all 20 properties
});
});
```
After:
```ts
import { fromPartial } from "@total-typescript/shoehorn";
it("gets user by id", () => {
getUser(
fromPartial({
body: { id: "123" },
}),
);
});
```
### `as Type``fromPartial()`
Before:
```ts
getUser({ body: { id: "123" } } as Request);
```
After:
```ts
import { fromPartial } from "@total-typescript/shoehorn";
getUser(fromPartial({ body: { id: "123" } }));
```
### `as unknown as Type``fromAny()`
Before:
```ts
getUser({ body: { id: 123 } } as unknown as Request); // wrong type on purpose
```
After:
```ts
import { fromAny } from "@total-typescript/shoehorn";
getUser(fromAny({ body: { id: 123 } }));
```
## When to use each
| Function | Use case |
| --------------- | -------------------------------------------------- |
| `fromPartial()` | Pass partial data that still type-checks |
| `fromAny()` | Pass intentionally wrong data (keeps autocomplete) |
| `fromExact()` | Force full object (swap with fromPartial later) |
## Workflow
1. **Gather requirements** - ask user:
- What test files have `as` assertions causing problems?
- Are they dealing with large objects where only some properties matter?
- Do they need to pass intentionally wrong data for error testing?
2. **Install and migrate**:
- [ ] Install: `npm i @total-typescript/shoehorn`
- [ ] Find test files with `as` assertions: `grep -r " as [A-Z]" --include="*.test.ts" --include="*.spec.ts"`
- [ ] Replace `as Type` with `fromPartial()`
- [ ] Replace `as unknown as Type` with `fromAny()`
- [ ] Add imports from `@total-typescript/shoehorn`
- [ ] Run type check to verify

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interface:
display_name: "Migrate to Shoehorn"
short_description: "Replace test assertions with shoehorn"

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---
name: obsidian-vault
description: Search, create, and manage notes in the Obsidian vault with wikilinks and index notes. Use when user wants to find, create, or organize notes in Obsidian.
---
# Obsidian Vault
## Vault location
`/mnt/d/Obsidian Vault/AI Research/`
Mostly flat at root level.
## Naming conventions
- **Index notes**: aggregate related topics (e.g., `Ralph Wiggum Index.md`, `Skills Index.md`, `RAG Index.md`)
- **Title case** for all note names
- No folders for organization - use links and index notes instead
## Linking
- Use Obsidian `[[wikilinks]]` syntax: `[[Note Title]]`
- Notes link to dependencies/related notes at the bottom
- Index notes are just lists of `[[wikilinks]]`
## Workflows
### Search for notes
```bash
# Search by filename
find "/mnt/d/Obsidian Vault/AI Research/" -name "*.md" | grep -i "keyword"
# Search by content
grep -rl "keyword" "/mnt/d/Obsidian Vault/AI Research/" --include="*.md"
```
Or use Grep/Glob tools directly on the vault path.
### Create a new note
1. Use **Title Case** for filename
2. Write content as a unit of learning (per vault rules)
3. Add `[[wikilinks]]` to related notes at the bottom
4. If part of a numbered sequence, use the hierarchical numbering scheme
### Find related notes
Search for `[[Note Title]]` across the vault to find backlinks:
```bash
grep -rl "\\[\\[Note Title\\]\\]" "/mnt/d/Obsidian Vault/AI Research/"
```
### Find index notes
```bash
find "/mnt/d/Obsidian Vault/AI Research/" -name "*Index*"
```

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interface:
display_name: "Obsidian Vault"
short_description: "Manage linked notes in Obsidian"

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# Logic Prototype
A tiny interactive terminal app that lets the user drive a state model by hand. Use this when the question is about **business logic, state transitions, or data shape** — the kind of thing that looks reasonable on paper but only feels wrong once you push it through real cases.
## When this is the right shape
- "I'm not sure if this state machine handles the edge case where X then Y."
- "Does this data model actually let me represent the case where..."
- "I want to feel out what the API should look like before writing it."
- Anything where the user wants to **press buttons and watch state change**.
If the question is "what should this look like" — wrong branch. Use [UI.md](UI.md).
## Process
### 1. State the question
Before writing code, write down what state model and what question you're prototyping. One paragraph, in the prototype's README or a comment at the top of the file. A logic prototype that answers the wrong question is pure waste — make the question explicit so it can be checked later, whether the user is watching now or returning to it AFK.
### 2. Pick the language
Use whatever the host project uses. If the project has no obvious runtime (e.g. a docs repo), ask.
Match the project's existing conventions for tooling — don't add a new package manager or runtime just for the prototype.
### 3. Isolate the logic in a portable module
Put the actual logic — the bit that's answering the question — behind a small, pure interface that could be lifted out and dropped into the real codebase later. The TUI around it is throwaway; the logic module shouldn't be.
The right shape depends on the question:
- **A pure reducer**`(state, action) => state`. Good when actions are discrete events and state is a single value.
- **A state machine** — explicit states and transitions. Good when "which actions are even legal right now" is part of the question.
- **A small set of pure functions** over a plain data type. Good when there's no implicit current state — just transformations.
- **A class or module with a clear method surface** when the logic genuinely owns ongoing internal state.
Pick whichever shape best fits the question being asked, *not* whichever is easiest to wire to a TUI. Keep it pure: no I/O, no terminal code, no `console.log` for control flow. The TUI imports it and calls into it; nothing flows the other direction.
This is what makes the prototype useful past its own lifetime: when the question's been answered, the validated reducer / machine / function set can be lifted into the real module on its own.
### 4. Build the smallest TUI that exposes the state
Build it as a **lightweight TUI** — on every tick, clear the screen (`console.clear()` / `print("\033[2J\033[H")` / equivalent) and re-render the whole frame. The user should always see one stable view, not an ever-growing scrollback.
Each frame has two parts, in this order:
1. **Current state**, pretty-printed and diff-friendly (one field per line, or formatted JSON). Use **bold** for field names or section headers and **dim** for less important context (timestamps, IDs, derived values). Native ANSI escape codes are fine — `\x1b[1m` bold, `\x1b[2m` dim, `\x1b[0m` reset. No need to pull in a styling library unless one is already in the project.
2. **Keyboard shortcuts**, listed at the bottom: `[a] add user [d] delete user [t] tick clock [q] quit`. Bold the key, dim the description, or vice-versa — whatever reads cleanly.
Behaviour:
1. **Initialise state** — a single in-memory object/struct. Render the first frame on start.
2. **Read one keystroke (or one line)** at a time, dispatch to a handler that mutates state.
3. **Re-render** the full frame after every action — don't append, replace.
4. **Loop until quit.**
The whole frame should fit on one screen.
### 5. Make it runnable in one command
Add a script to the project's existing task runner (`package.json` scripts, `Makefile`, `justfile`, `pyproject.toml`). The user should run `pnpm run <prototype-name>` or equivalent — never need to remember a path.
If the host project has no task runner, just put the command at the top of the prototype's README.
### 6. Hand it over
Give the user the run command. They'll drive it themselves; the interesting moments are when they say "wait, that shouldn't be possible" or "huh, I assumed X would be different" — those are the bugs in the _idea_, which is the whole point. If they want new actions added, add them. Prototypes evolve.
### 7. Capture the answer and the prototype
Once the prototype has answered its question, capture the answer, then capture the prototype the way the [SKILL](SKILL.md) describes. The logic-specific mapping: the validated reducer / machine / function set lifts into the real module (the decision, absorbed); the TUI shell rides along to the throwaway branch that keeps the prototype as a primary source.
## Anti-patterns
- **Don't add tests.** A prototype that needs tests is no longer a prototype.
- **Don't wire it to the real database.** Use an in-memory store unless the question is specifically about persistence.
- **Don't generalise.** No "what if we wanted to support X later." The prototype answers one question.
- **Don't blur the logic and the TUI together.** If the reducer / state machine references `console.log`, prompts, or terminal escape codes, it's no longer portable. Keep the TUI as a thin shell over a pure module.
- **Don't ship the TUI shell into production.** The shell is optimised for being driven by hand from a terminal. The logic module behind it is the bit worth keeping.

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---
name: prototype
description: Build a throwaway prototype to answer a design question. Use when the user wants to sanity-check whether a state model or logic feels right, or explore what a UI should look like.
---
# Prototype
A prototype is **throwaway code that answers a question**. The question decides the shape.
## Pick a branch
Identify which question is being answered — from the user's prompt, the surrounding code, or by asking if the user is around:
- **"Does this logic / state model feel right?"** → [LOGIC.md](LOGIC.md). Build a tiny interactive terminal app that pushes the state machine through cases that are hard to reason about on paper.
- **"What should this look like?"** → [UI.md](UI.md). Generate several radically different UI variations on a single route, switchable via a URL search param and a floating bottom bar.
The two branches produce very different artifacts — getting this wrong wastes the whole prototype. If the question is genuinely ambiguous and the user isn't reachable, default to whichever branch better matches the surrounding code (a backend module → logic; a page or component → UI) and state the assumption at the top of the prototype.
## Rules that apply to both
1. **Throwaway from day one, and clearly marked as such.** Locate the prototype code close to where it will actually be used (next to the module or page it's prototyping for) so context is obvious — but name it so a casual reader can see it's a prototype, not production. For throwaway UI routes, obey whatever routing convention the project already uses; don't invent a new top-level structure.
2. **One command to run.** Whatever the project's existing task runner supports — `pnpm <name>`, `python <path>`, `bun <path>`, etc. The user must be able to start it without thinking.
3. **No persistence by default.** State lives in memory. Persistence is the thing the prototype is _checking_, not something it should depend on. If the question explicitly involves a database, hit a scratch DB or a local file with a clear "PROTOTYPE — wipe me" name.
4. **Skip the polish.** No tests, no error handling beyond what makes the prototype _runnable_, no abstractions. The point is to learn something fast.
5. **Surface the state.** After every action (logic) or on every variant switch (UI), print or render the full relevant state so the user can see what changed.
6. **Capture it when done.** Fold any validated decision into the real code, then capture the prototype itself as a **primary source**: commit it to a throwaway branch, out of main, and leave a context pointer to that branch on the implementation issue. Capture the answer too — the verdict and the question it settled — in the issue or a commit. The main branch keeps only the validated decision.

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# UI Prototype
Generate **several radically different UI variations** on a single route, switchable from a floating bottom bar. The user flips between variants in the browser, picks one (or steals bits from each), then throws the rest away.
If the question is about logic/state rather than what something looks like — wrong branch. Use [LOGIC.md](LOGIC.md).
## When this is the right shape
- "What should this page look like?"
- "I want to see a few options for this dashboard before committing."
- "Try a different layout for the settings screen."
- Any time the user would otherwise spend a day picking between three vague mockups in their head.
## Two sub-shapes — strongly prefer sub-shape A
A UI prototype is much easier to judge when it's **butting up against the rest of the app** — real header, real sidebar, real data, real density. A throwaway route on its own is a vacuum: every variant looks fine in isolation. Default to sub-shape A whenever there's a plausible existing page to host the variants. Only reach for sub-shape B if the prototype genuinely has no nearby home.
### Sub-shape A — adjustment to an existing page (preferred)
The route already exists. Variants are rendered **on the same route**, gated by a `?variant=` URL search param. The existing data fetching, params, and auth all stay — only the rendering swaps. This is the default; pick it unless there's a specific reason not to.
If the prototype is for something that doesn't yet have a page but *would naturally live inside one* (a new section of the dashboard, a new card on the settings screen, a new step in an existing flow) — that's still sub-shape A. Mount the variants inside the host page.
### Sub-shape B — a new page (last resort)
Only use this when the thing being prototyped genuinely has no existing page to live inside — e.g. an entirely new top-level surface, or a flow that can't be embedded anywhere sensible.
Create a **throwaway route** following whatever routing convention the project already uses — don't invent a new top-level structure. Name it so it's obviously a prototype (e.g. include the word `prototype` in the path or filename). Same `?variant=` pattern.
Before committing to sub-shape B, sanity-check: is there really no existing page this could be embedded in? An empty route hides design problems that a populated one would expose.
In both sub-shapes the floating bottom bar is identical.
## Process
### 1. State the question and pick N
Default to **3 variants**. More than 5 stops being radically different and starts being noise — cap there.
Write down the plan in one line, in the prototype's location or a top-of-file comment:
> "Three variants of the settings page, switchable via `?variant=`, on the existing `/settings` route."
This works whether the user is here to push back or not.
### 2. Generate radically different variants
Draft each variant. Hold each one to:
- The page's purpose and the data it has access to.
- The project's component library / styling system (TailwindCSS, shadcn, MUI, plain CSS, whatever).
- A clear exported component name, e.g. `VariantA`, `VariantB`, `VariantC`.
Variants must be **structurally different** — different layout, different information hierarchy, different primary affordance, not just different colours. Three slightly-tweaked card grids isn't a UI prototype, it's wallpaper. If two drafts come out too similar, redo one with explicit "do not use a card grid" guidance.
### 3. Wire them together
Create a single switcher component on the route:
```tsx
// pseudo-code — adapt to the project's framework
const variant = searchParams.get('variant') ?? 'A';
return (
<>
{variant === 'A' && <VariantA {...data} />}
{variant === 'B' && <VariantB {...data} />}
{variant === 'C' && <VariantC {...data} />}
<PrototypeSwitcher variants={['A','B','C']} current={variant} />
</>
);
```
For sub-shape A (existing page): keep all the existing data fetching above the switcher; only the rendered subtree changes per variant.
For sub-shape B (new page): the throwaway route under `/prototype/<name>` mounts the same switcher.
### 4. Build the floating switcher
A small fixed-position bar at the bottom-centre of the screen with three pieces:
- **Left arrow** — cycles to the previous variant (wraps around).
- **Variant label** — shows the current variant key and, if the variant exports a name, that name too. e.g. `B — Sidebar layout`.
- **Right arrow** — cycles forward (wraps around).
Behaviour:
- Clicking an arrow updates the URL search param (use the framework's router — `router.replace` on Next, `navigate` on React Router, etc) so the variant is shareable and reload-stable.
- Keyboard: `←` and `→` arrow keys also cycle. Don't intercept arrow keys when an `<input>`, `<textarea>`, or `[contenteditable]` is focused.
- Visually distinct from the page (e.g. high-contrast pill, subtle shadow) so it's obviously not part of the design being evaluated.
- Hidden in production builds — gate on `process.env.NODE_ENV !== 'production'` or an equivalent check, so a stray prototype merge can't ship the bar to users.
Put the switcher in a single shared component so both sub-shapes can reuse it. Locate it wherever shared UI lives in the project.
### 5. Hand it over
Surface the URL (and the `?variant=` keys). The user will flip through whenever they get to it. The interesting feedback is usually **"I want the header from B with the sidebar from C"** — that's the actual design they want.
### 6. Capture the answer and clean up
Once a variant has won, capture the answer — which variant and why — then capture the prototype the way the [SKILL](SKILL.md) describes. Fold the winner into the real code and move the rest onto the throwaway branch, not into main:
- **Sub-shape A** — fold the winner into the existing page; drop the losing variants and the switcher from main.
- **Sub-shape B** — promote the winning variant to a real route; drop the throwaway route and the switcher from main.
The full set of variants is the primary source, so it lands on the throwaway branch, not the bin — variant components and the switcher left in the main branch rot fast and confuse the next reader.
## Anti-patterns
- **Variants that differ only in colour or copy.** That's a tweak, not a prototype. Real variants disagree about structure.
- **Sharing too much code between variants.** A shared `<Header>` is fine; a shared `<Layout>` defeats the point. Each variant should be free to throw out the layout.
- **Wiring variants to real mutations.** Read-only prototypes are fine. If a variant needs to mutate, point it at a stub — the question is "what should this look like", not "does the backend work".
- **Promoting the prototype directly to production.** The variant code was written under prototype constraints (no tests, minimal error handling). Rewrite it properly when you fold it in.

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interface:
display_name: "Prototype"
short_description: "Prototype to answer a design question"

130
.agents/skills/qa/SKILL.md Normal file
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---
name: qa
description: Interactive QA session where user reports bugs or issues conversationally, and the agent files GitHub issues. Explores the codebase in the background for context and domain language. Use when user wants to report bugs, do QA, file issues conversationally, or mentions "QA session".
---
# QA Session
Run an interactive QA session. The user describes problems they're encountering. You clarify, explore the codebase for context, and file GitHub issues that are durable, user-focused, and use the project's domain language.
## For each issue the user raises
### 1. Listen and lightly clarify
Let the user describe the problem in their own words. Ask **at most 2-3 short clarifying questions** focused on:
- What they expected vs what actually happened
- Steps to reproduce (if not obvious)
- Whether it's consistent or intermittent
Do NOT over-interview. If the description is clear enough to file, move on.
### 2. Explore the codebase in the background
While talking to the user, kick off an Agent (subagent_type=Explore) in the background to understand the relevant area. The goal is NOT to find a fix — it's to:
- Learn the domain language used in that area (check UBIQUITOUS_LANGUAGE.md)
- Understand what the feature is supposed to do
- Identify the user-facing behavior boundary
This context helps you write a better issue — but the issue itself should NOT reference specific files, line numbers, or internal implementation details.
### 3. Assess scope: single issue or breakdown?
Before filing, decide whether this is a **single issue** or needs to be **broken down** into multiple issues.
Break down when:
- The fix spans multiple independent areas (e.g. "the form validation is wrong AND the success message is missing AND the redirect is broken")
- There are clearly separable concerns that different people could work on in parallel
- The user describes something that has multiple distinct failure modes or symptoms
Keep as a single issue when:
- It's one behavior that's wrong in one place
- The symptoms are all caused by the same root behavior
### 4. File the GitHub issue(s)
Create issues with `gh issue create`. Do NOT ask the user to review first — just file and share URLs.
Issues must be **durable** — they should still make sense after major refactors. Write from the user's perspective.
#### For a single issue
Use this template:
```
## What happened
[Describe the actual behavior the user experienced, in plain language]
## What I expected
[Describe the expected behavior]
## Steps to reproduce
1. [Concrete, numbered steps a developer can follow]
2. [Use domain terms from the codebase, not internal module names]
3. [Include relevant inputs, flags, or configuration]
## Additional context
[Any extra observations from the user or from codebase exploration that help frame the issue — e.g. "this only happens when using the Docker layer, not the filesystem layer" — use domain language but don't cite files]
```
#### For a breakdown (multiple issues)
Create issues in dependency order (blockers first) so you can reference real issue numbers.
Use this template for each sub-issue:
```
## Parent issue
#<parent-issue-number> (if you created a tracking issue) or "Reported during QA session"
## What's wrong
[Describe this specific behavior problem — just this slice, not the whole report]
## What I expected
[Expected behavior for this specific slice]
## Steps to reproduce
1. [Steps specific to THIS issue]
## Blocked by
- #<issue-number> (if this issue can't be fixed until another is resolved)
Or "None — can start immediately" if no blockers.
## Additional context
[Any extra observations relevant to this slice]
```
When creating a breakdown:
- **Prefer many thin issues over few thick ones** — each should be independently fixable and verifiable
- **Mark blocking relationships honestly** — if issue B genuinely can't be tested until issue A is fixed, say so. If they're independent, mark both as "None — can start immediately"
- **Create issues in dependency order** so you can reference real issue numbers in "Blocked by"
- **Maximize parallelism** — the goal is that multiple people (or agents) can grab different issues simultaneously
#### Rules for all issue bodies
- **No file paths or line numbers** — these go stale
- **Use the project's domain language** (check UBIQUITOUS_LANGUAGE.md if it exists)
- **Describe behaviors, not code** — "the sync service fails to apply the patch" not "applyPatch() throws on line 42"
- **Reproduction steps are mandatory** — if you can't determine them, ask the user
- **Keep it concise** — a developer should be able to read the issue in 30 seconds
After filing, print all issue URLs (with blocking relationships summarized) and ask: "Next issue, or are we done?"
### 5. Continue the session
Keep going until the user says they're done. Each issue is independent — don't batch them.

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interface:
display_name: "QA"
short_description: "Conversational QA that files issues"

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---
name: request-refactor-plan
description: Create a detailed refactor plan with tiny commits via user interview, then file it as a GitHub issue. Use when user wants to plan a refactor, create a refactoring RFC, or break a refactor into safe incremental steps.
---
This skill will be invoked when the user wants to create a refactor request. You should go through the steps below. You may skip steps if you don't consider them necessary.
1. Ask the user for a long, detailed description of the problem they want to solve and any potential ideas for solutions.
2. Explore the repo to verify their assertions and understand the current state of the codebase.
3. Ask whether they have considered other options, and present other options to them.
4. Interview the user about the implementation. Be extremely detailed and thorough.
5. Hammer out the exact scope of the implementation. Work out what you plan to change and what you plan not to change.
6. Look in the codebase to check for test coverage of this area of the codebase. If there is insufficient test coverage, ask the user what their plans for testing are.
7. Break the implementation into a plan of tiny commits. Remember Martin Fowler's advice to "make each refactoring step as small as possible, so that you can always see the program working."
8. Create a GitHub issue with the refactor plan. Use the following template for the issue description:
<refactor-plan-template>
## Problem Statement
The problem that the developer is facing, from the developer's perspective.
## Solution
The solution to the problem, from the developer's perspective.
## Commits
A LONG, detailed implementation plan. Write the plan in plain English, breaking down the implementation into the tiniest commits possible. Each commit should leave the codebase in a working state.
## Decision Document
A list of implementation decisions that were made. This can include:
- The modules that will be built/modified
- The interfaces of those modules that will be modified
- Technical clarifications from the developer
- Architectural decisions
- Schema changes
- API contracts
- Specific interactions
Do NOT include specific file paths or code snippets. They may end up being outdated very quickly.
## Testing Decisions
A list of testing decisions that were made. Include:
- A description of what makes a good test (only test external behavior, not implementation details)
- Which modules will be tested
- Prior art for the tests (i.e. similar types of tests in the codebase)
## Out of Scope
A description of the things that are out of scope for this refactor.
## Further Notes (optional)
Any further notes about the refactor.
</refactor-plan-template>

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interface:
display_name: "Request Refactor Plan"
short_description: "Plan a safe incremental refactor"

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---
name: research
description: Investigate a question against high-trust primary sources and capture the findings as a Markdown file in the repo. Use when the user wants a topic researched, docs or API facts gathered, or reading legwork delegated to a background agent.
---
Spin up a **background agent** to do the research, so you keep working while it reads.
Its job:
1. Investigate the question against **primary sources** — official docs, source code, specs, first-party APIs — not a secondary write-up of them. Follow every claim back to the source that owns it.
2. Write the findings to a single Markdown file, citing each claim's source.
3. Save it where the repo already keeps such notes; match the existing convention, and if there is none, put it somewhere sensible and say where.

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interface:
display_name: "Research"
short_description: "Research from high-trust sources"

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---
name: resolving-merge-conflicts
description: "Use when you need to resolve an in-progress git merge/rebase conflict."
---
1. **See the current state** of the merge/rebase. Check git history, and the conflicting files.
2. **Find the primary sources** for each conflict. Understand deeply why each change was made, and what the original intent was. Read the commit messages, check the PRs, check original issues/tickets.
3. **Resolve each hunk.** Preserve both intents where possible. Where incompatible, pick the one matching the merge's stated goal and note the trade-off. Do **not** invent new behaviour. Always resolve; never `--abort`.
4. Discover the project's **automated checks** and run them — typically typecheck, then tests, then format. Fix anything the merge broke.
5. **Finish the merge/rebase.** Stage everything and commit. If rebasing, continue the rebase process until all commits are rebased.

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interface:
display_name: "Resolving Merge Conflicts"
short_description: "Resolve merge and rebase conflicts"

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---
name: scaffold-exercises
description: Create exercise directory structures with sections, problems, solutions, and explainers that pass linting. Use when user wants to scaffold exercises, create exercise stubs, or set up a new course section.
---
# Scaffold Exercises
Create exercise directory structures that pass `pnpm ai-hero-cli internal lint`, then commit with `git commit`.
## Directory naming
- **Sections**: `XX-section-name/` inside `exercises/` (e.g., `01-retrieval-skill-building`)
- **Exercises**: `XX.YY-exercise-name/` inside a section (e.g., `01.03-retrieval-with-bm25`)
- Section number = `XX`, exercise number = `XX.YY`
- Names are dash-case (lowercase, hyphens)
## Exercise variants
Each exercise needs at least one of these subfolders:
- `problem/` - student workspace with TODOs
- `solution/` - reference implementation
- `explainer/` - conceptual material, no TODOs
When stubbing, default to `explainer/` unless the plan specifies otherwise.
## Required files
Each subfolder (`problem/`, `solution/`, `explainer/`) needs a `readme.md` that:
- Is **not empty** (must have real content, even a single title line works)
- Has no broken links
When stubbing, create a minimal readme with a title and a description:
```md
# Exercise Title
Description here
```
If the subfolder has code, it also needs a `main.ts` (>1 line). But for stubs, a readme-only exercise is fine.
## Workflow
1. **Parse the plan** - extract section names, exercise names, and variant types
2. **Create directories** - `mkdir -p` for each path
3. **Create stub readmes** - one `readme.md` per variant folder with a title
4. **Run lint** - `pnpm ai-hero-cli internal lint` to validate
5. **Fix any errors** - iterate until lint passes
## Lint rules summary
The linter (`pnpm ai-hero-cli internal lint`) checks:
- Each exercise has subfolders (`problem/`, `solution/`, `explainer/`)
- At least one of `problem/`, `explainer/`, or `explainer.1/` exists
- `readme.md` exists and is non-empty in the primary subfolder
- No `.gitkeep` files
- No `speaker-notes.md` files
- No broken links in readmes
- No `pnpm run exercise` commands in readmes
- `main.ts` required per subfolder unless it's readme-only
## Moving/renaming exercises
When renumbering or moving exercises:
1. Use `git mv` (not `mv`) to rename directories - preserves git history
2. Update the numeric prefix to maintain order
3. Re-run lint after moves
Example:
```bash
git mv exercises/01-retrieval/01.03-embeddings exercises/01-retrieval/01.04-embeddings
```
## Example: stubbing from a plan
Given a plan like:
```
Section 05: Memory Skill Building
- 05.01 Introduction to Memory
- 05.02 Short-term Memory (explainer + problem + solution)
- 05.03 Long-term Memory
```
Create:
```bash
mkdir -p exercises/05-memory-skill-building/05.01-introduction-to-memory/explainer
mkdir -p exercises/05-memory-skill-building/05.02-short-term-memory/{explainer,problem,solution}
mkdir -p exercises/05-memory-skill-building/05.03-long-term-memory/explainer
```
Then create readme stubs:
```
exercises/05-memory-skill-building/05.01-introduction-to-memory/explainer/readme.md -> "# Introduction to Memory"
exercises/05-memory-skill-building/05.02-short-term-memory/explainer/readme.md -> "# Short-term Memory"
exercises/05-memory-skill-building/05.02-short-term-memory/problem/readme.md -> "# Short-term Memory"
exercises/05-memory-skill-building/05.02-short-term-memory/solution/readme.md -> "# Short-term Memory"
exercises/05-memory-skill-building/05.03-long-term-memory/explainer/readme.md -> "# Long-term Memory"
```

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interface:
display_name: "Scaffold Exercises"
short_description: "Scaffold lint-ready course exercises"

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---
name: setup-matt-pocock-skills
description: Configure this repo for the engineering skills — set up its issue tracker, triage label vocabulary, and domain doc layout. Run once before first use of the other engineering skills.
disable-model-invocation: true
---
# Setup Matt Pocock's Skills
Scaffold the per-repo configuration that the engineering skills assume:
- **Issue tracker** — where issues live (GitHub by default; local markdown is also supported out of the box)
- **Triage labels** — the strings used for the five canonical triage roles
- **Domain docs** — where `CONTEXT.md` and ADRs live, and the consumer rules for reading them
This is a prompt-driven skill, not a deterministic script. Explore, present what you found, confirm with the user, then write.
## Process
### 1. Explore
Look at the current repo to understand its starting state. Read whatever exists; don't assume:
- `git remote -v` and `.git/config` — is this a GitHub repo? Which one?
- `AGENTS.md` and `CLAUDE.md` at the repo root — does either exist? Is there already an `## Agent skills` section in either?
- `CONTEXT.md` and `CONTEXT-MAP.md` at the repo root
- `docs/adr/` and any `src/*/docs/adr/` directories
- `docs/agents/` — does this skill's prior output already exist?
- `.scratch/` — sign that a local-markdown issue tracker convention is already in use
- Is the `triage` skill installed? (a `triage` skill folder alongside this one, or `triage` in your available skills.) This decides whether Section B runs at all.
- Monorepo signals — a `pnpm-workspace.yaml`, a `workspaces` field in `package.json`, or a populated `packages/*` with its own `src/`. Present only in a genuinely large multi-package repo; their absence means single-context, which is almost every repo.
### 2. Present findings and ask
Summarise what's present and what's missing. Then take the sections in order — one section, one answer, then the next.
Lead each section with the recommended answer so the user can accept it in a word. Give a one-line explainer only when the choice genuinely branches; skip the section entirely when exploration already settled it (Section B when `triage` isn't installed, Section C when there's no monorepo).
**Section A — Issue tracker.**
> Explainer: The "issue tracker" is where issues live for this repo. Skills like `to-tickets`, `triage`, `to-spec`, and `qa` read from and write to it — they need to know whether to call `gh issue create`, write a markdown file under `.scratch/`, or follow some other workflow you describe. Pick the place you actually track work for this repo.
Default posture: these skills were designed for GitHub. If a `git remote` points at GitHub, propose that. If a `git remote` points at GitLab (`gitlab.com` or a self-hosted host), propose GitLab. Otherwise (or if the user prefers), offer:
- **GitHub** — issues live in the repo's GitHub Issues (uses the `gh` CLI)
- **GitLab** — issues live in the repo's GitLab Issues (uses the [`glab`](https://gitlab.com/gitlab-org/cli) CLI)
- **Local markdown** — issues live as files under `.scratch/<feature>/` in this repo (good for solo projects or repos without a remote)
- **Other** (Jira, Linear, etc.) — ask the user to describe the workflow in one paragraph; the skill will record it as freeform prose
Record the choice in `docs/agents/issue-tracker.md`. The GitHub and GitLab templates carry a "PRs as a request surface" flag, defaulted **off** — leave it off and don't raise it; a user who wants external PRs in the triage queue can flip the flag in the file later.
**Section B — Triage label vocabulary.** Skip this section entirely if the `triage` skill isn't installed (exploration told you) — an uninstalled skill needs no labels.
If it is installed, ask exactly one question:
> Do you want to keep the default triage labels? (recommended: **yes**)
The defaults are the five canonical roles, each label string equal to its name: `needs-triage`, `needs-info`, `ready-for-agent`, `ready-for-human`, `wontfix`. On **yes**, write them as-is. Only if the user says no — usually because their tracker already uses other names (e.g. `bug:triage` for `needs-triage`) — collect the overrides so `triage` applies existing labels instead of creating duplicates.
**Section C — Domain docs.** Default to **single-context** — one `CONTEXT.md` + `docs/adr/` at the repo root. This fits almost every repo; write it without asking.
Offer **multi-context** — a root `CONTEXT-MAP.md` pointing to per-context `CONTEXT.md` files — only when exploration found monorepo signals. Then confirm which layout they want.
### 3. Confirm and edit
Show the user a draft of:
- The `## Agent skills` block to add to whichever of `CLAUDE.md` / `AGENTS.md` is being edited (see step 4 for selection rules)
- The contents of `docs/agents/issue-tracker.md`, `docs/agents/domain.md`, and `docs/agents/triage-labels.md` (the last only when `triage` is installed)
Let them edit before writing.
### 4. Write
**Pick the file to edit:**
- If `CLAUDE.md` exists, edit it.
- Else if `AGENTS.md` exists, edit it.
- If neither exists, ask the user which one to create — don't pick for them.
Never create `AGENTS.md` when `CLAUDE.md` already exists (or vice versa) — always edit the one that's already there.
If an `## Agent skills` block already exists in the chosen file, update its contents in-place rather than appending a duplicate. Don't overwrite user edits to the surrounding sections.
The block:
```markdown
## Agent skills
### Issue tracker
[one-line summary of where issues are tracked]. See `docs/agents/issue-tracker.md`.
### Triage labels
[one-line summary of the label vocabulary]. See `docs/agents/triage-labels.md`.
### Domain docs
[one-line summary of layout — "single-context" or "multi-context"]. See `docs/agents/domain.md`.
```
Include the `### Triage labels` sub-block, and write `docs/agents/triage-labels.md`, only when `triage` is installed and Section B ran. When it isn't, both are omitted.
Then write the docs files using the seed templates in this skill folder as a starting point:
- [issue-tracker-github.md](./issue-tracker-github.md) — GitHub issue tracker
- [issue-tracker-gitlab.md](./issue-tracker-gitlab.md) — GitLab issue tracker
- [issue-tracker-local.md](./issue-tracker-local.md) — local-markdown issue tracker
- [triage-labels.md](./triage-labels.md) — label mapping (only if `triage` is installed)
- [domain.md](./domain.md) — domain doc consumer rules + layout
For "other" issue trackers, write `docs/agents/issue-tracker.md` from scratch using the user's description.
### 5. Done
Tell the user the setup is complete and which engineering skills will now read from these files. Mention they can edit `docs/agents/*.md` directly later — re-running this skill is only necessary if they want to switch issue trackers or restart from scratch.

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interface:
display_name: "Setup Matt Pocock Skills"
short_description: "Configure a repo for the skills"
policy:
allow_implicit_invocation: false

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# Domain Docs
How the engineering skills should consume this repo's domain documentation when exploring the codebase.
## Before exploring, read these
- **`CONTEXT.md`** at the repo root, or
- **`CONTEXT-MAP.md`** at the repo root if it exists — it points at one `CONTEXT.md` per context. Read each one relevant to the topic.
- **`docs/adr/`** — read ADRs that touch the area you're about to work in. In multi-context repos, also check `src/<context>/docs/adr/` for context-scoped decisions.
If any of these files don't exist, **proceed silently**. Don't flag their absence; don't suggest creating them upfront. The `/domain-modeling` skill (reached via `/grill-with-docs` and `/improve-codebase-architecture`) creates them lazily when terms or decisions actually get resolved.
## File structure
Single-context repo (most repos):
```
/
├── CONTEXT.md
├── docs/adr/
│ ├── 0001-event-sourced-orders.md
│ └── 0002-postgres-for-write-model.md
└── src/
```
Multi-context repo (presence of `CONTEXT-MAP.md` at the root):
```
/
├── CONTEXT-MAP.md
├── docs/adr/ ← system-wide decisions
└── src/
├── ordering/
│ ├── CONTEXT.md
│ └── docs/adr/ ← context-specific decisions
└── billing/
├── CONTEXT.md
└── docs/adr/
```
## Use the glossary's vocabulary
When your output names a domain concept (in an issue title, a refactor proposal, a hypothesis, a test name), use the term as defined in `CONTEXT.md`. Don't drift to synonyms the glossary explicitly avoids.
If the concept you need isn't in the glossary yet, that's a signal — either you're inventing language the project doesn't use (reconsider) or there's a real gap (note it for `/domain-modeling`).
## Flag ADR conflicts
If your output contradicts an existing ADR, surface it explicitly rather than silently overriding:
> _Contradicts ADR-0007 (event-sourced orders) — but worth reopening because…_

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# Issue tracker: GitHub
Issues and PRDs for this repo live as GitHub issues. Use the `gh` CLI for all operations.
## Conventions
- **Create an issue**: `gh issue create --title "..." --body "..."`. Use a heredoc for multi-line bodies.
- **Read an issue**: `gh issue view <number> --comments`, filtering comments by `jq` and also fetching labels.
- **List issues**: `gh issue list --state open --json number,title,body,labels,comments --jq '[.[] | {number, title, body, labels: [.labels[].name], comments: [.comments[].body]}]'` with appropriate `--label` and `--state` filters.
- **Comment on an issue**: `gh issue comment <number> --body "..."`
- **Apply / remove labels**: `gh issue edit <number> --add-label "..."` / `--remove-label "..."`
- **Close**: `gh issue close <number> --comment "..."`
Infer the repo from `git remote -v``gh` does this automatically when run inside a clone.
## Pull requests as a triage surface
**PRs as a request surface: no.** _(Set to `yes` if this repo treats external PRs as feature requests; `/triage` reads this flag.)_
When set to `yes`, PRs run through the same labels and states as issues, using the `gh pr` equivalents:
- **Read a PR**: `gh pr view <number> --comments` and `gh pr diff <number>` for the diff.
- **List external PRs for triage**: `gh pr list --state open --json number,title,body,labels,author,authorAssociation,comments` then keep only `authorAssociation` of `CONTRIBUTOR`, `FIRST_TIME_CONTRIBUTOR`, or `NONE` (drop `OWNER`/`MEMBER`/`COLLABORATOR`).
- **Comment / label / close**: `gh pr comment`, `gh pr edit --add-label`/`--remove-label`, `gh pr close`.
GitHub shares one number space across issues and PRs, so a bare `#42` may be either — resolve with `gh pr view 42` and fall back to `gh issue view 42`.
## When a skill says "publish to the issue tracker"
Create a GitHub issue.
## When a skill says "fetch the relevant ticket"
Run `gh issue view <number> --comments`.
## Wayfinding operations
Used by `/wayfinder`. The **map** is a single issue with **child** issues as tickets.
- **Map**: a single issue labelled `wayfinder:map`, holding the Notes / Decisions-so-far / Fog body. `gh issue create --label wayfinder:map`.
- **Child ticket**: an issue linked to the map as a GitHub sub-issue (`gh api` on the sub-issues endpoint). Where sub-issues aren't enabled, add the child to a task list in the map body and put `Part of #<map>` at the top of the child body. Labels: `wayfinder:<type>` (`research`/`prototype`/`grilling`/`task`). Once claimed, the ticket is assigned to the driving dev.
- **Blocking**: GitHub's **native issue dependencies** — the canonical, UI-visible representation. Add an edge with `gh api --method POST repos/<owner>/<repo>/issues/<child>/dependencies/blocked_by -F issue_id=<blocker-db-id>`, where `<blocker-db-id>` is the blocker's numeric **database id** (`gh api repos/<owner>/<repo>/issues/<n> --jq .id`, _not_ the `#number` or `node_id`). GitHub reports `issue_dependencies_summary.blocked_by` (open blockers only — the live gate). Where dependencies aren't available, fall back to a `Blocked by: #<n>, #<n>` line at the top of the child body. A ticket is unblocked when every blocker is closed.
- **Frontier query**: list the map's open children (`gh issue list --state open`, scoped to the map's sub-issues / task list), drop any with an open blocker (`issue_dependencies_summary.blocked_by > 0`, or an open issue in the `Blocked by` line) or an assignee; first in map order wins.
- **Claim**: `gh issue edit <n> --add-assignee @me` — the session's first write.
- **Resolve**: `gh issue comment <n> --body "<answer>"`, then `gh issue close <n>`, then append a context pointer (gist + link) to the map's Decisions-so-far.

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# Issue tracker: GitLab
Issues and PRDs for this repo live as GitLab issues. Use the [`glab`](https://gitlab.com/gitlab-org/cli) CLI for all operations.
## Conventions
- **Create an issue**: `glab issue create --title "..." --description "..."`. Use a heredoc for multi-line descriptions. Pass `--description -` to open an editor.
- **Read an issue**: `glab issue view <number> --comments`. Use `-F json` for machine-readable output.
- **List issues**: `glab issue list -F json` with appropriate `--label` filters.
- **Comment on an issue**: `glab issue note <number> --message "..."`. GitLab calls comments "notes".
- **Apply / remove labels**: `glab issue update <number> --label "..."` / `--unlabel "..."`. Multiple labels can be comma-separated or by repeating the flag.
- **Close**: `glab issue close <number>`. `glab issue close` does not accept a closing comment, so post the explanation first with `glab issue note <number> --message "..."`, then close.
- **Merge requests**: GitLab calls PRs "merge requests". Use `glab mr create`, `glab mr view`, `glab mr note`, etc. — the same shape as `gh pr ...` with `mr` in place of `pr` and `note`/`--message` in place of `comment`/`--body`.
Infer the repo from `git remote -v``glab` does this automatically when run inside a clone.
## Merge requests as a triage surface
**MRs as a request surface: no.** _(Set to `yes` if this repo treats external merge requests as feature requests; `/triage` reads this flag.)_
When set to `yes`, MRs run through the same labels and states as issues, using the `glab mr` equivalents:
- **Read an MR**: `glab mr view <number> --comments` and `glab mr diff <number>` for the diff.
- **List external MRs for triage**: `glab mr list -F json`, then keep only MRs whose author is not a project member/owner (a contributor's MR, not a maintainer's in-flight work).
- **Comment / label / close**: `glab mr note`, `glab mr update --label`/`--unlabel`, `glab mr close`.
Unlike GitHub, GitLab numbers issues and MRs separately, so `#42` is unambiguous once you know which surface the maintainer means.
## When a skill says "publish to the issue tracker"
Create a GitLab issue.
## When a skill says "fetch the relevant ticket"
Run `glab issue view <number> --comments`.
## Wayfinding operations
Used by `/wayfinder`. The **map** is a single issue with **child** issues as tickets.
- **Map**: a single issue labelled `wayfinder:map`, holding the Notes / Decisions-so-far / Fog body. `glab issue create --label wayfinder:map`. (On GitLab tiers with native epics, an epic may hold the map instead; a labelled issue works everywhere.)
- **Child ticket**: an issue carrying `Part of #<map>` at the top of its description and labels `wayfinder:<type>` (`research`/`prototype`/`grilling`/`task`). Once claimed, the ticket is assigned to the driving dev.
- **Blocking**: GitLab's **native blocking link** — the canonical, UI-visible representation. Add it with the `/blocked_by #<n>` quick action, posted as a note (`glab issue note <child> --message "/blocked_by #<blocker>"`). Native blocking links are a Premium/Ultimate feature; on the free tier (or where unavailable) fall back to a `Blocked by: #<n>, #<n>` line at the top of the description. A ticket is unblocked when every blocker is closed.
- **Frontier query**: `glab issue list -F json` scoped to the map's children, drop any with an open blocker — a native `blocked_by` link to an open issue (`glab api projects/:id/issues/:iid/links`), or an open issue in the `Blocked by` line — or an assignee; first in map order wins.
- **Claim**: `glab issue update <n> --assignee @me` — the session's first write.
- **Resolve**: `glab issue note <n> --message "<answer>"`, then `glab issue close <n>`, then append a context pointer (gist + link) to the map's Decisions-so-far.

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# Issue tracker: Local Markdown
Issues and specs (you may know a spec as a PRD) for this repo live as markdown files in `.scratch/`.
## Conventions
- One feature per directory: `.scratch/<feature-slug>/`
- The spec is `.scratch/<feature-slug>/spec.md`
- Implementation issues are one file per ticket at `.scratch/<feature-slug>/issues/<NN>-<slug>.md`, numbered from `01` — never a single combined tickets file
- Triage state is recorded as a `Status:` line near the top of each issue file (see `triage-labels.md` for the role strings)
- Comments and conversation history append to the bottom of the file under a `## Comments` heading
## When a skill says "publish to the issue tracker"
Create a new file under `.scratch/<feature-slug>/` (creating the directory if needed).
## When a skill says "fetch the relevant ticket"
Read the file at the referenced path. The user will normally pass the path or the issue number directly.
## Wayfinding operations
Used by `/wayfinder`. The **map** is a file with one **child** file per ticket.
- **Map**: `.scratch/<effort>/map.md` — the Notes / Decisions-so-far / Fog body.
- **Child ticket**: `.scratch/<effort>/issues/NN-<slug>.md`, numbered from `01`, with the question in the body. A `Type:` line records the ticket type (`research`/`prototype`/`grilling`/`task`); a `Status:` line records `claimed`/`resolved`.
- **Blocking**: a `Blocked by: NN, NN` line near the top. A ticket is unblocked when every file it lists is `resolved`.
- **Frontier**: scan `.scratch/<effort>/issues/` for files that are open, unblocked, and unclaimed; first by number wins.
- **Claim**: set `Status: claimed` and save before any work.
- **Resolve**: append the answer under an `## Answer` heading, set `Status: resolved`, then append a context pointer (gist + link) to the map's Decisions-so-far in `map.md`.

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# Triage Labels
The skills speak in terms of five canonical triage roles. This file maps those roles to the actual label strings used in this repo's issue tracker.
| Label in mattpocock/skills | Label in our tracker | Meaning |
| -------------------------- | -------------------- | ---------------------------------------- |
| `needs-triage` | `needs-triage` | Maintainer needs to evaluate this issue |
| `needs-info` | `needs-info` | Waiting on reporter for more information |
| `ready-for-agent` | `ready-for-agent` | Fully specified, ready for an AFK agent |
| `ready-for-human` | `ready-for-human` | Requires human implementation |
| `wontfix` | `wontfix` | Will not be actioned |
When a skill mentions a role (e.g. "apply the AFK-ready triage label"), use the corresponding label string from this table.
Edit the right-hand column to match whatever vocabulary you actually use.

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---
name: setup-pre-commit
description: Set up Husky pre-commit hooks with lint-staged (Prettier), type checking, and tests in the current repo. Use when user wants to add pre-commit hooks, set up Husky, configure lint-staged, or add commit-time formatting/typechecking/testing.
---
# Setup Pre-Commit Hooks
## What This Sets Up
- **Husky** pre-commit hook
- **lint-staged** running Prettier on all staged files
- **Prettier** config (if missing)
- **typecheck** and **test** scripts in the pre-commit hook
## Steps
### 1. Detect package manager
Check for `package-lock.json` (npm), `pnpm-lock.yaml` (pnpm), `yarn.lock` (yarn), `bun.lockb` (bun). Use whichever is present. Default to npm if unclear.
### 2. Install dependencies
Install as devDependencies:
```
husky lint-staged prettier
```
### 3. Initialize Husky
```bash
npx husky init
```
This creates `.husky/` dir and adds `prepare: "husky"` to package.json.
### 4. Create `.husky/pre-commit`
Write this file (no shebang needed for Husky v9+):
```
npx lint-staged
npm run typecheck
npm run test
```
**Adapt**: Replace `npm` with detected package manager. If repo has no `typecheck` or `test` script in package.json, omit those lines and tell the user.
### 5. Create `.lintstagedrc`
```json
{
"*": "prettier --ignore-unknown --write"
}
```
### 6. Create `.prettierrc` (if missing)
Only create if no Prettier config exists. Use these defaults:
```json
{
"useTabs": false,
"tabWidth": 2,
"printWidth": 80,
"singleQuote": false,
"trailingComma": "es5",
"semi": true,
"arrowParens": "always"
}
```
### 7. Verify
- [ ] `.husky/pre-commit` exists and is executable
- [ ] `.lintstagedrc` exists
- [ ] `prepare` script in package.json is `"husky"`
- [ ] `prettier` config exists
- [ ] Run `npx lint-staged` to verify it works
### 8. Commit
Stage all changed/created files and commit with message: `Add pre-commit hooks (husky + lint-staged + prettier)`
This will run through the new pre-commit hooks — a good smoke test that everything works.
## Notes
- Husky v9+ doesn't need shebangs in hook files
- `prettier --ignore-unknown` skips files Prettier can't parse (images, etc.)
- The pre-commit runs lint-staged first (fast, staged-only), then full typecheck and tests

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interface:
display_name: "Setup Pre-Commit"
short_description: "Add pre-commit quality checks"

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---
name: setup-ts-deep-modules
description: Wire dependency-cruiser into a TypeScript repo so each package is a deep module — implementation hidden in subfolders, reachable only through its entry-point files. User-invoked.
disable-model-invocation: true
---
# Setup TS Deep Modules
Make every package in this repo a **deep module**: a lot of behaviour behind a small interface. A package's public surface is its **entry points** — the files at the package root — and everything in its subfolders is hidden. This skill installs [dependency-cruiser](https://github.com/sverweij/dependency-cruiser) and the rules that make the entry points the only way in, then proves the rules bite.
For the vocabulary (deep module, interface, seam, depth), run the `/codebase-design` skill — use its language throughout.
## The shape this enforces
```
src/packages/
<name>/
index.ts ← an entry point (public). Import this from outside.
client.ts ← another entry point. Packages may expose SEVERAL.
lib/ ← implementation: hidden from outside, free to import each other.
tests/ ← co-located tests + fixtures (a subfolder, so private).
```
The public surface is the package's **root files** — not one designated `index.ts`. By convention implementation lives in `lib/` and tests in `tests/`, giving every package the same two-folder shape. The rule itself is general, though: *anything* in *any* subfolder is private, so you never extend the config to add a folder.
Four rules, all `error`:
1. **Entry-point boundary** — code outside a package (app code or another package) may import only that package's entry points (its root files), never anything in its subfolders.
2. **Intra-package freedom** — a package's own files import each other freely.
3. **Tests through the entry points** — files under `<pkg>/tests/` may import any package's entry points and their own `tests/` fixtures, but never any package's subfolder internals (not even their own). Integration tests across packages are fine; deep imports are not.
4. **No cycles** — no dependency cycles.
**Entry points, not a barrel.** Because the public surface is *every* root file, a package can expose several small entry points (`index.ts`, `client.ts`, `server.ts`) instead of funnelling everything through one giant `index.ts`. Barrel files that re-export a whole subtree are discouraged — keep entry points small and hide implementation in subfolders.
Layering (which packages may depend on which) is a *different* concern and is left as a commented stub in the config for this repo to fill in.
## Steps
### 1. Detect the environment
- **Package manager**`pnpm-lock.yaml` → pnpm, `yarn.lock` → yarn, `bun.lockb` → bun, else npm. Use it for every command below (`pnpm`/`yarn`/`npm run`/`bunx`).
- **Packages root** — if `src/` exists use `src/packages`, else `packages`. Confirm the choice with the user if the repo already has a different obvious convention.
- **Existing config** — check for a `.dependency-cruiser.*` file. If one exists, do **not** overwrite it: merge the four rules and the options in, and tell the user what you added.
**Done when:** package manager, packages root, and existing-config status are all known.
### 2. Install dependency-cruiser
Install `dependency-cruiser` as a devDependency with the detected package manager.
**Done when:** `dependency-cruiser` is in `devDependencies`.
### 3. Write the config
Copy [`dependency-cruiser.config.cjs`](./dependency-cruiser.config.cjs) to the repo root as `.dependency-cruiser.cjs`. Set `PACKAGES_ROOT` to the root detected in step 1. The rules are path-depth based and extension-agnostic, so nothing else needs adapting.
**Done when:** `.dependency-cruiser.cjs` exists with the correct `PACKAGES_ROOT`, and the four forbidden rules are present.
### 4. Wire it into the checks
- Add a `lint:boundaries` script: `depcruise <packages-root>` (or `depcruise src`).
- Fold it into the repo's umbrella check command — the one that already runs typecheck (e.g. a `check` / `ci` / `validate` script). Do **not** touch `tsconfig` or add path aliases.
- If there is no umbrella script, add `lint:boundaries` and tell the user to include it in CI.
**Done when:** `lint:boundaries` exists and runs as part of the same command as typecheck.
### 5. Scaffold the example package
Create a committed `<packages-root>/example/` as a copy-me template:
- `index.ts` — an entry point. Export one function that delegates to an internal file (so the package is visibly *deep*, not a pass-through).
- `lib/impl.ts` — an internal file in a **subfolder**, imported by `index.ts`, not reachable from outside.
- `tests/example.test.ts` — imports **only** `../index` (an entry point), and asserts against the public function.
Tell the user this is a starter template to copy or delete.
**Done when:** the example package exists, exposes its behaviour through a root entry point, and hides `impl` in a subfolder.
### 6. Prove the rules bite
This is the completion criterion for the whole skill — a config that doesn't fail on a violation is worthless.
1. Run `lint:boundaries`. It must **pass** on the clean example.
2. Temporarily add a deep import to `tests/example.test.ts` (e.g. `import { thing } from "../lib/impl"`). Run `lint:boundaries` again — it must **fail** with `tests-through-entrypoints`.
3. Revert the deep import. Run once more — it must **pass**.
**Done when:** you have observed a pass, then a fail on the deep import, then a pass again. If step 2 does not fail, the rules are not wired correctly — fix before finishing.
### 7. Document the convention
Write a `README.md` **in the packages folder** (`<packages-root>/README.md`) — next to the packages it governs — covering: the `src/packages/<name>/` layout (entry points at the root, `lib/` for implementation, `tests/` for tests), "import only through a package's entry points (its root files)", and how to run `lint:boundaries`. **Discourage barrel files** explicitly — expose several small entry points instead of re-exporting a whole subtree through one index. Keep it to the copy-me snippet plus the four rules in one paragraph each.
Then add a **context pointer** to it from the repo's agent-instructions file — `CLAUDE.md` if present, else `AGENTS.md` (create `AGENTS.md` if neither exists). One line is enough, e.g. `Packages are deep modules — see [src/packages/README.md](./src/packages/README.md) before adding or importing one.` This is what makes an agent discover the boundary rule instead of tripping over it.
**Done when:** `<packages-root>/README.md` exists and discourages barrels, and the repo's `CLAUDE.md`/`AGENTS.md` links to it.
## Notes
- The config's `$1` back-references (dependency-cruiser's group matching) are what let a package reach its own internals while outsiders can't — don't flatten them into separate per-package rules.
- Public vs private is decided by **depth**: a package's root files are entry points; anything in a subfolder is private. The conventional subfolders are `lib/` (implementation) and `tests/`, but the rule doesn't hardcode them — any subfolder is private, so a new folder never needs a config change. Adding an entry point is just adding a root file — no barrel.
- Packages are **flat**: one tier of immediate children under the root. A package's internals may nest as deep as you like; a package may not contain another package.
- Use `.cjs` (not `.js`) so the config's `module.exports` works even in `"type": "module"` repos.

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interface:
display_name: "Setup TS Deep Modules"
short_description: "Enforce deep TypeScript modules"
policy:
allow_implicit_invocation: false

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// @ts-check
// Deep-module enforcement for dependency-cruiser.
//
// Each package under the packages root is a DEEP MODULE: a lot of behaviour
// behind a small interface. A package's PUBLIC SURFACE is its ENTRY POINTS —
// the files at the package root. Implementation lives in SUBFOLDERS and is
// private — by convention `lib/` for implementation and `tests/` for tests,
// though any subfolder is private. A package may expose several small entry
// points (index.ts, client.ts, server.ts, …) — prefer that over one giant
// barrel index.
//
// The only thing you should ever need to edit here is PACKAGES_ROOT.
/** Where packages live. One immediate child dir per package (flat, no nesting). */
const PACKAGES_ROOT = "src/packages";
// --- derived patterns (no need to edit) -------------------------------------
const R = PACKAGES_ROOT;
/**
* A package's private internals: anything nested inside a package subfolder.
* The package's root files are its entry points and are NOT matched here
* they stay importable from outside.
*/
const PACKAGE_INTERNALS = `^${R}/[^/]+/[^/]+/`;
/** @type {import('dependency-cruiser').IConfiguration} */
module.exports = {
forbidden: [
{
name: "entrypoint-boundary-from-app",
comment:
"App/root code may import a package's entry points (its root files), but nothing inside its subfolders.",
severity: "error",
from: { pathNot: `^${R}/` }, // importer is NOT inside any package
to: { path: PACKAGE_INTERNALS },
},
{
name: "entrypoint-boundary-across-packages",
comment:
"A package's own files import each other freely, but may reach OTHER packages only through their entry points — never their internals.",
severity: "error",
// importer is inside a package ($1), but is not a test file
from: { path: `^${R}/([^/]+)/`, pathNot: `^${R}/[^/]+/tests/` },
to: {
path: PACKAGE_INTERNALS,
pathNot: `^${R}/$1/`, // same package → intra-package freedom
},
},
{
name: "tests-through-entrypoints",
comment:
"A package's tests exercise it through its entry points like everyone else: they may import any package's entry points and their own tests/ fixtures, but never any package's internals — not even their own.",
severity: "error",
from: { path: `^${R}/([^/]+)/tests/` }, // a test file, in package $1
to: {
path: PACKAGE_INTERNALS,
pathNot: `^${R}/$1/tests/`, // own tests/ fixtures → allowed
},
},
{
name: "tests-folder-is-private",
comment:
"A package's tests/ folder is reachable only from tests — nothing else may import fixtures.",
severity: "error",
from: { pathNot: `^${R}/[^/]+/tests/` }, // importer is not itself a test
to: { path: `^${R}/[^/]+/tests/` },
},
{
name: "no-circular",
comment: "No dependency cycles. Scope to `^${R}/` if you want to allow cycles outside packages.",
severity: "error",
from: {},
to: { circular: true },
},
// --- Layering (optional, off by default) ----------------------------------
// Interface-hiding controls HOW you import (through the entry points).
// Layering controls WHICH packages may depend on which. Add your own rules
// here, e.g.:
//
// {
// name: "ui-may-not-depend-on-billing",
// severity: "error",
// from: { path: `^${R}/ui/` },
// to: { path: `^${R}/billing/` },
// },
],
options: {
doNotFollow: { path: "node_modules" },
tsConfig: { fileName: "tsconfig.json" },
enhancedResolveOptions: {
extensions: [".ts", ".tsx", ".js", ".jsx", ".json"],
},
},
};

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---
name: tdd
description: Test-driven development. Use when the user wants to build features or fix bugs test-first, mentions "red-green-refactor", or wants integration tests.
---
# Test-Driven Development
TDD is the red → green loop. This skill is the reference that makes that loop produce tests worth keeping: what a good test is, where tests go, the anti-patterns, and the rules of the loop. Every section applies on every cycle — consult them before and during the loop, not after.
When exploring the codebase, read `CONTEXT.md` (if it exists) so test names and interface vocabulary match the project's domain language, and respect ADRs in the area you're touching.
## What a good test is
Tests verify behavior through public interfaces, not implementation details. Code can change entirely; tests shouldn't. A good test reads like a specification — "user can checkout with valid cart" tells you exactly what capability exists — and survives refactors because it doesn't care about internal structure.
See [tests.md](tests.md) for examples and [mocking.md](mocking.md) for mocking guidelines.
## Seams — where tests go
A **seam** is the public boundary you test at: the interface where you observe behavior without reaching inside. Tests live at seams, never against internals.
**Test only at pre-agreed seams.** Before writing any test, write down the seams under test and confirm them with the user. No test is written at an unconfirmed seam. You can't test everything — agreeing the seams up front is how testing effort lands on the critical paths and complex logic instead of every edge case.
Ask: "What's the public interface, and which seams should we test?"
## Anti-patterns
- **Implementation-coupled** — mocks internal collaborators, tests private methods, or verifies through a side channel (querying the database instead of using the interface). The tell: the test breaks when you refactor but behavior hasn't changed.
- **Tautological** — the assertion recomputes the expected value the way the code does (`expect(add(a, b)).toBe(a + b)`, a snapshot derived by hand the same way, a constant asserted equal to itself), so it passes by construction and can never disagree with the code. Expected values must come from an independent source of truth — a known-good literal, a worked example, the spec.
- **Horizontal slicing** — writing all tests first, then all implementation. Bulk tests verify _imagined_ behavior: you test the _shape_ of things rather than user-facing behavior, the tests go insensitive to real changes, and you commit to test structure before understanding the implementation. Work in **vertical slices** instead — one test → one implementation → repeat, each test a **tracer bullet** that responds to what the last cycle taught you.
## Rules of the loop
- **Red before green.** Write the failing test first, then only enough code to pass it. Don't anticipate future tests or add speculative features.
- **One slice at a time.** One seam, one test, one minimal implementation per cycle.
- **Refactoring is not part of the loop.** It belongs to the review stage (see the `code-review` skill), not the red → green implementation cycle.

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interface:
display_name: "TDD"
short_description: "Test-driven red-green-refactor"

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# When to Mock
Mock at **system boundaries** only:
- External APIs (payment, email, etc.)
- Databases (sometimes - prefer test DB)
- Time/randomness
- File system (sometimes)
Don't mock:
- Your own classes/modules
- Internal collaborators
- Anything you control
## Designing for Mockability
At system boundaries, design interfaces that are easy to mock:
**1. Use dependency injection**
Pass external dependencies in rather than creating them internally:
```typescript
// Easy to mock
function processPayment(order, paymentClient) {
return paymentClient.charge(order.total);
}
// Hard to mock
function processPayment(order) {
const client = new StripeClient(process.env.STRIPE_KEY);
return client.charge(order.total);
}
```
**2. Prefer SDK-style interfaces over generic fetchers**
Create specific functions for each external operation instead of one generic function with conditional logic:
```typescript
// GOOD: Each function is independently mockable
const api = {
getUser: (id) => fetch(`/users/${id}`),
getOrders: (userId) => fetch(`/users/${userId}/orders`),
createOrder: (data) => fetch('/orders', { method: 'POST', body: data }),
};
// BAD: Mocking requires conditional logic inside the mock
const api = {
fetch: (endpoint, options) => fetch(endpoint, options),
};
```
The SDK approach means:
- Each mock returns one specific shape
- No conditional logic in test setup
- Easier to see which endpoints a test exercises
- Type safety per endpoint

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# Good and Bad Tests
## Good Tests
**Integration-style**: Test through real interfaces, not mocks of internal parts.
```typescript
// GOOD: Tests observable behavior
test("user can checkout with valid cart", async () => {
const cart = createCart();
cart.add(product);
const result = await checkout(cart, paymentMethod);
expect(result.status).toBe("confirmed");
});
```
Characteristics:
- Tests behavior users/callers care about
- Uses public API only
- Survives internal refactors
- Describes WHAT, not HOW
- One logical assertion per test
## Bad Tests
**Implementation-detail tests**: Coupled to internal structure.
```typescript
// BAD: Tests implementation details
test("checkout calls paymentService.process", async () => {
const mockPayment = jest.mock(paymentService);
await checkout(cart, payment);
expect(mockPayment.process).toHaveBeenCalledWith(cart.total);
});
```
Red flags:
- Mocking internal collaborators
- Testing private methods
- Asserting on call counts/order
- Test breaks when refactoring without behavior change
- Test name describes HOW not WHAT
- Verifying through external means instead of interface
```typescript
// BAD: Bypasses interface to verify
test("createUser saves to database", async () => {
await createUser({ name: "Alice" });
const row = await db.query("SELECT * FROM users WHERE name = ?", ["Alice"]);
expect(row).toBeDefined();
});
// GOOD: Verifies through interface
test("createUser makes user retrievable", async () => {
const user = await createUser({ name: "Alice" });
const retrieved = await getUser(user.id);
expect(retrieved.name).toBe("Alice");
});
```
**Tautological tests**: Expected value restates the implementation, so the test passes by construction.
```typescript
// BAD: Expected value is recomputed the way the code computes it
test("calculateTotal sums line items", () => {
const items = [{ price: 10 }, { price: 5 }];
const expected = items.reduce((sum, i) => sum + i.price, 0);
expect(calculateTotal(items)).toBe(expected);
});
// GOOD: Expected value is an independent, known literal
test("calculateTotal sums line items", () => {
expect(calculateTotal([{ price: 10 }, { price: 5 }])).toBe(15);
});
```

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# GLOSSARY.md Format
`GLOSSARY.md` is the canonical language for this teaching workspace. All explainers, exercises, and learning records should adhere to its terminology. Building it is itself part of learning: compressing a concept into a tight definition is evidence the user understands it.
## Structure
```md
# {Topic} Glossary
{One or two sentence description of the topic this glossary covers.}
## Terms
**Hypertrophy**:
Muscle growth driven by mechanical tension and metabolic stress over repeated training sessions.
_Avoid_: Bulking, getting big
**Progressive overload**:
Systematically increasing the demand on a muscle over time — via load, volume, or intensity.
_Avoid_: Pushing harder, levelling up
**RPE (Rate of Perceived Exertion)**:
A 110 self-rating of how hard a set felt, where 10 is failure and 8 means two reps left in the tank.
_Avoid_: Effort score, intensity rating
```
## Rules
- **Add a term only when the user understands it.** The glossary is a record of compressed knowledge, not a dictionary the user reads to learn. If the user has just been introduced to a concept, wait until they can use it correctly before promoting it here.
- **Be opinionated.** When several words exist for the same concept, pick the best one and list the rest as aliases to avoid. This is how language compresses.
- **Keep definitions tight.** One or two sentences. Define what the term IS, not what it does or how to do it.
- **Use the glossary's own terms inside definitions.** Once a term is in the glossary, prefer it everywhere — including inside other definitions. This is what makes complex terms easier to grasp later.
- **Group under subheadings** when natural clusters emerge (e.g. `## Anatomy`, `## Programming`). A flat list is fine when terms cohere.
- **Flag ambiguities explicitly.** If a term is used loosely in the wider field, note the resolution: "In this workspace, 'set' always means a working set — warm-ups are tracked separately."
- **Revise as understanding deepens.** A definition the user wrote in week one may be wrong by week six. Update in place; do not leave stale entries.

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# Learning Record Format
Learning records live in `./learning-records/` and use sequential numbering: `0001-slug.md`, `0002-slug.md`, etc. Create the directory lazily — only when the first record is written.
They are the teaching equivalent of ADRs: they capture non-obvious lessons, key insights, and stated prior knowledge that will steer future sessions. They are used to calculate the zone of proximal development.
## Template
```md
# {Short title of what was learned or established}
{1-3 sentences: what was learned (or what prior knowledge was established), and why it matters for future sessions.}
```
That is the whole format. A learning record can be a single paragraph. The value is recording _that_ this is now known and _why_ it changes what to teach next — not in filling out sections.
## Optional sections
Only include these when they add genuine value. Most records won't need them.
- **Status** frontmatter (`active | superseded by LR-NNNN`) — useful when an earlier understanding turns out to be wrong and is replaced.
- **Evidence** — how the user demonstrated the understanding (a question answered, an exercise completed, prior experience cited). Useful when the claim might be revisited.
- **Implications** — what this unlocks or rules out for future sessions. Worth recording when non-obvious.
## Numbering
Scan `./learning-records/` for the highest existing number and increment by one.
## When to write a learning record
Write one when any of these is true:
1. **The user demonstrated genuine understanding of something non-trivial** — not just exposure, but evidence they can use the concept correctly. This sets a new floor for what to teach next.
2. **The user disclosed prior knowledge** — "I already know X." Record it so future sessions don't re-teach it. Also record the _depth_ claimed.
3. **A misconception was corrected** — the user previously believed something wrong and now sees why. These are high-value: they predict future stumbling blocks for related topics.
4. **The mission shifted in response to learning** — the user discovered they cared about something different than they thought. Cross-link to [[MISSION.md]] and update it.
### What does _not_ qualify
- Material that was merely covered. Coverage is not learning. Wait for evidence.
- Anything already captured tersely in [[GLOSSARY.md]] as a term definition. Don't duplicate.
- Session-by-session activity logs. Learning records are not a journal — they are decision-grade insights.
## Supersession
When a later record contradicts an earlier one (the user's understanding deepened or corrected), mark the old record `Status: superseded by LR-NNNN` rather than deleting it. The history of how understanding evolved is itself useful signal.

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# MISSION.md Format
`MISSION.md` lives at the workspace root. It captures the _reason_ the user is learning this topic. Every teaching decision — what to teach next, which resources to surface, which exercises to design — should trace back to this document.
## Template
```md
# Mission: {Topic}
## Why
{1-3 sentences. The concrete real-world goal the user is chasing. What changes in their life or work when they have this skill? Avoid abstract framings like "to understand X" — push for the underlying outcome.}
## Success looks like
- {A specific, observable thing the user will be able to do}
- {Another specific thing}
- {…}
## Constraints
- {Time, budget, prior commitments, learning preferences, anything that bounds the approach}
## Out of scope
- {Adjacent topics the user explicitly does not want to chase right now — protects the zone of proximal development}
```
## Rules
- **One mission per workspace.** If the user wants to learn two unrelated things, that is two workspaces.
- **Concrete over abstract.** "Run a half marathon by October" beats "get fitter." "Ship a Rust CLI to my team" beats "learn Rust."
- **Push back on vagueness.** If the user cannot articulate why, interview them before writing anything. A bad mission is worse than no mission.
- **Revise when reality shifts.** Missions change. When the user's goal moves, update this file — don't leave a stale mission steering future sessions.
- **Keep it short.** If `MISSION.md` runs past a screen, it has stopped being a compass and started being a plan.

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# RESOURCES.md Format
`RESOURCES.md` is the curated set of trusted sources for this topic. Knowledge for explainers should be drawn from here, not from parametric guesses. Wisdom comes from the communities listed here.
## Structure
```md
# {Topic} Resources
## Knowledge
- [Book: _The Science and Practice of Strength Training_ — Zatsiorsky & Kraemer](https://example.com)
Foundational text on programming and adaptation. Use for: anything to do with periodisation, recovery, intensity zones.
- [Article: "How Much Should I Train?" — Greg Nuckols (Stronger By Science)](https://example.com)
Evidence-based review of volume landmarks. Use for: weekly set targets per muscle group.
## Wisdom (Communities)
- [r/weightroom](https://reddit.com/r/weightroom)
High-signal subreddit, moderated against bro-science. Use for: programme critique, plateau troubleshooting.
- Local: Tuesday strength class at {gym name}
Use for: real-time coaching feedback on lifts.
```
## Rules
- **High-trust only.** Prefer primary sources, recognised experts, peer-reviewed work, and communities with strong moderation. If a resource is marketing dressed as education, leave it out.
- **Annotate every entry.** A bare link is useless in three months. Add one line: what it covers and when to reach for it.
- **Group by Knowledge / Wisdom.** Mirrors the philosophy in [SKILL.md](./SKILL.md). It is fine for a resource to appear in only one group.
- **Surface gaps explicitly.** If no good resource exists for an area the mission needs, write a `## Gaps` section listing what is missing. This drives future search.
- **Prune ruthlessly.** A resource that turned out to be wrong, shallow, or off-mission should be removed, not buried. Better five sharp sources than thirty mediocre ones.
- **Record community preferences.** If the user has opted out of joining communities, note it here so future sessions don't keep proposing them.

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---
name: teach
description: Teach the user a new skill or concept, within this workspace.
disable-model-invocation: true
argument-hint: "What would you like to learn about?"
---
The user has asked you to teach them something. This is a stateful request - they intend to learn the topic over multiple sessions.
## Teaching Workspace
Treat the current directory as a teaching workspace. The state of their learning is captured in this directory in several files:
- `MISSION.md`: A document capturing the _reason_ the user is interested in the topic. This should be used to ground all teaching. Use the format in [MISSION-FORMAT.md](./MISSION-FORMAT.md).
- `./reference/*.html`: A directory of reference materials. These are the compressed learnings from the lessons - cheat sheets, reference algorithms, syntax, yoga poses, glossaries. They are the raw units of learning. They should be beautiful documents which print out well, and are designed for quick reference.
- `RESOURCES.md`: A list of resources which can be explored to ground your teaching in contextual knowledge, or to acquire knowledge and wisdom. Use the format in [RESOURCES-FORMAT.md](./RESOURCES-FORMAT.md).
- `./learning-records/*.md`: A directory of learning records, which capture what the user has learned. These are loosely equivalent to architectural decision records in software development - they capture non-obvious lessons and key insights that may need to be revised later, or drive future sessions. These should be used to calculate the zone of proximal development. They are titled `0001-<dash-case-name>.md`, where the number increments each time. Use the format in [LEARNING-RECORD-FORMAT.md](./LEARNING-RECORD-FORMAT.md).
- `./lessons/*.html`: A directory of lessons. A **lesson** is a single, self-contained HTML output that teaches one tightly-scoped thing tied to the mission. This is the primary unit of teaching in this workspace.
- `./assets/*`: Reusable **components** shared across lessons. See [Assets](#assets).
- `NOTES.md`: A scratchpad for you to jot down user preferences, or working notes.
## Philosophy
To learn at a deep level, the user needs three things:
- **Knowledge**, captured from high-quality, high-trust resources
- **Skills**, acquired through highly-relevant interactive lessons devised by you, based on the knowledge
- **Wisdom**, which comes from interacting with other learners and practitioners
Before the `RESOURCES.md` is well-populated, your focus should be to find high-quality resources which will help the user acquire knowledge. Never trust your parametric knowledge.
Some topics may require more skills than knowledge. Learning more about theoretical physics might be more knowledge-based. For yoga, more skills-based.
### Fluency vs Storage Strength
You should be careful to split between two types of learning:
- **Fluency strength**: in-the-moment retrieval of knowledge
- **Storage strength**: long-term retention of knowledge
Fluency can give the user an illusory sense of mastery, but storage strength is the real goal. Try to design lessons which build long-term retention by desirable difficulty:
- Using retrieval practice (recall from memory)
- Spacing (distributing practice over time)
- Interleaving (mixing up different but related topics in practice - for skills practice only)
## Lessons
A lesson is the main thing you produce — the unit in which knowledge and skills reach the user. Each lesson is one self-contained HTML file, saved to `./lessons/` and titled `0001-<dash-case-name>.html` where the number increments each time.
A lesson should be **beautiful** — clean, readable typography and layout — since the user will return to these later to review. Think Tufte.
The lesson should be short, and completable very quickly. Learners' working memory is very small, and we need to stay within it. But each lesson should give the user a single tangible win that they can build on. It should be directly tied to the mission, and should be in the user's zone of proximal development.
If possible, open the lesson file for the user by running a CLI command.
Each lesson should link via HTML anchors to other lessons and reference documents.
Each lesson should recommend a primary source for the user to read or watch. This should be the most high-quality, high-trust resource you found on the topic.
Each lesson should contain a reminder to ask followup questions to the agent. The agent is their teacher, and can assist with anything that's unclear.
## Assets
Lessons are built from reusable **components**, stored in `./assets/`: stylesheets, quiz widgets, simulators, diagram helpers — anything a second lesson could reuse.
Reuse is the default, not the exception. Before authoring a lesson, read `./assets/` and build from the components already there. When a lesson needs something new and reusable, write it as a component in `./assets/` and link to it — never inline code a future lesson would duplicate.
A shared stylesheet is the first component every workspace earns: every lesson links it, so the lessons look like one consistent course rather than a pile of one-offs. As the workspace grows, so should the component library.
## The Mission
Every lesson should be tied into the mission - the reason that the user is interested in learning about the topic.
If the user is unclear about the mission, or the `MISSION.md` is not populated, your first job should be to question the user on why they want to learn this.
Failing to understand the mission will mean knowledge acquisition is not grounded in real-world goals. Lessons will feel too abstract. You will have no way of judging what the user should do next.
Missions may change as the user develops more skills and knowledge. This is normal - make sure to update the `MISSION.md` and add a learning record to capture the change. Confirm with the user before changing the mission.
## Zone Of Proximal Development
Each lesson, the user should always feel as if they are being challenged 'just enough'.
The user may specify an exact thing they want to learn. If they don't, figure out their zone of proximal development by:
- Reading their `learning-records`
- Figuring out the right thing to teach them based on their mission
- Teach the most relevant thing that fits in their zone of proximal development
## Knowledge
Lessons should be designed around a skill the user is going to learn. The knowledge in the lesson should be only what's required to acquire that skill. You teach the knowledge first, then get the user to practice the skills via an interactive feedback loop.
Knowledge should first be gathered from trusted resources. Use `RESOURCES.md` to keep track of them. Lessons should be littered with citations - links to external resources to back up any claim made. This increases the trustworthiness of the lesson.
For acquiring knowledge, difficulty is the enemy. It eats working memory you need for understanding.
## Skills
If knowledge is all about acquisition, skills are about durability and flexibility. Make the knowledge stick.
For skill acquisition, difficulty is the tool. Effortful retrieval is what builds storage strength. Skills should be taught through interactive lessons. There are several tools at your disposal:
- Interactive lessons, using quizzes and light in-browser tasks
- Lessons which guide the user through a list of real-world steps to take (for instance, yoga poses)
Each of these should be based on a **feedback loop**, where the user receives feedback on their performance. This feedback loop should be as tight as possible, giving feedback immediately - and ideally automatically.
For quizzes, each answer should be exactly the same number of words (and characters, if possible). Don't give the user any clues about the answer through formatting.
## Acquiring Wisdom
Wisdom comes from true real-world interaction - testing your skills outside the learning environment.
When the user asks a question that appears to require wisdom, your default posture should be to attempt to answer - but to ultimately delegate to a **community**.
A community is a place (online or offline) where the user can test their skills in the real world. This might be a forum, a subreddit, a real-world class (budget permitting) or a local interest group.
You should attempt to find high-reputation communities the user can join. If the user expresses a preference that they don't want to join a community, respect it.
## Reference Documents
While creating lessons, you should also create reference documents. Lessons can reference these documents - they are useful for tracking raw units of knowledge useful across lessons.
Lessons will rarely be revisited later - reference documents will be. They should be the compressed essence of the lesson, in a format designed for quick reference.
Some learning topics lend themselves to reference:
- Syntax and code snippets for programming
- Algorithms and flowcharts for processes
- Yoga poses and sequences for yoga
- Exercises and routines for fitness
- Glossaries for any topic with its own nomenclature
Glossaries, in particular, are an essential reference. Once one is created, it should be adhered to in every lesson.
## `NOTES.md`
The user will sometimes express preferences of how they want to be taught, or things you should keep in mind. This is the place to record those preferences, so you can refer back to them when designing lessons or working with the user.

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interface:
display_name: "Teach"
short_description: "Learn a concept in a guided workspace"
policy:
allow_implicit_invocation: false

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---
name: to-questionnaire
description: Turn a decision you can't fully answer into a questionnaire for someone else to fill in.
disable-model-invocation: true
---
Turn something the user can't answer alone into a **questionnaire** — a Markdown document they hand to one person to fill in async, or fill out together over a meeting. The recipient holds knowledge the user lacks; the questionnaire pulls it out of them.
**Grill the send, not the subject.** Interview the user only about the _send_, which they can always answer: who it goes to, and what they need back. The questions in the document then target the **gap** between what the recipient knows and what the user needs.
1. **Who is it going to?** Ask, in one exchange, the recipient's role, expertise, and relationship to the user. This fixes the questionnaire's tone and how much context it must carry. Done when you know who the recipient is and what they know that the user doesn't.
2. **What do you need back?** Ask, in one exchange, the specific decisions or facts the user can't resolve alone and needs from this person. Done when you have a concrete list of what the user must walk away able to do or decide.
3. **Write the questionnaire.** Draft questions aimed at the gap from steps 12, following the Document structure below. Write it to `to-questionnaire-<slug>.md` in the current directory (slug from the topic) and report the path. Done when the file exists and every item the user named in step 2 is covered by a question.
## Document structure
Frame the document as a **discovery questionnaire**: the user lacks context, the recipient holds it. Order questions most-important-first — async means you may only get one pass — and group them under `##` headings by theme once there are more than a handful. Write it using the template below.
<questionnaire-template>
# <Questionnaire title>
**Purpose:** why this questionnaire exists and the decision riding on it.
**From:** <the user>**To:** <the recipient>**How your answers will be used:** <where they go>
## Context
One paragraph orienting a recipient who wasn't in the user's head. Enough to answer well, not a page.
## How to answer
Deadline and rough effort. Partial answers and "I don't know" are useful — flag anything you're unsure of rather than skipping it.
## <Theme heading>
One `##` section per theme. Under each, its questions, most-important-first. Every question is one idea — never compound — with an answer stub directly beneath, and a one-line _why this matters_ only where the question could be misread or invite a throwaway answer.
<question-example>
### What load is the system expected to handle at launch?
_Why this matters: it decides whether we provision for burst traffic now or defer it._
>
</question-example>
## Anything else?
A closing catch-all: anything we didn't ask that we should know?
</questionnaire-template>

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interface:
display_name: "To Questionnaire"
short_description: "Front-load questions into a doc for someone to answer"
policy:
allow_implicit_invocation: false

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---
name: to-spec
description: Turn the current conversation into a spec and publish it to the project issue tracker — no interview, just synthesis of what you've already discussed.
disable-model-invocation: true
---
This skill takes the current conversation context and codebase understanding and produces a spec (you may know this document as a PRD). Do NOT interview the user — just synthesize what you already know.
The issue tracker and triage label vocabulary should have been provided to you — run `/setup-matt-pocock-skills` if not.
## Process
1. Explore the repo to understand the current state of the codebase, if you haven't already. Use the project's domain glossary vocabulary throughout the spec, and respect any ADRs in the area you're touching.
2. Sketch out the seams at which you're going to test the feature. Existing seams should be preferred to new ones. Use the highest seam possible. If new seams are needed, propose them at the highest point you can. The fewer seams across the codebase, the better - the ideal number is one.
Check with the user that these seams match their expectations.
3. Write the spec using the template below, then publish it to the project issue tracker. Apply the `ready-for-agent` triage label - no need for additional triage.
<spec-template>
## Problem Statement
The problem that the user is facing, from the user's perspective.
## Solution
The solution to the problem, from the user's perspective.
## User Stories
A LONG, numbered list of user stories. Each user story should be in the format of:
1. As an <actor>, I want a <feature>, so that <benefit>
<user-story-example>
1. As a mobile bank customer, I want to see balance on my accounts, so that I can make better informed decisions about my spending
</user-story-example>
This list of user stories should be extremely extensive and cover all aspects of the feature.
## Implementation Decisions
A list of implementation decisions that were made. This can include:
- The modules that will be built/modified
- The interfaces of those modules that will be modified
- Technical clarifications from the developer
- Architectural decisions
- Schema changes
- API contracts
- Specific interactions
Do NOT include specific file paths or code snippets. They may end up being outdated very quickly.
Exception: if a prototype produced a snippet that encodes a decision more precisely than prose can (state machine, reducer, schema, type shape), inline it within the relevant decision and note briefly that it came from a prototype. Trim to the decision-rich parts — not a working demo, just the important bits.
## Testing Decisions
A list of testing decisions that were made. Include:
- A description of what makes a good test (only test external behavior, not implementation details)
- Which modules will be tested
- Prior art for the tests (i.e. similar types of tests in the codebase)
## Out of Scope
A description of the things that are out of scope for this spec.
## Further Notes
Any further notes about the feature.
</spec-template>

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interface:
display_name: "To Spec"
short_description: "Turn a conversation into a spec"
policy:
allow_implicit_invocation: false

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---
name: to-tickets
description: Break a plan, spec, or the current conversation into a set of tracer-bullet tickets, each declaring its blocking edges, published to the configured tracker — edges as text in one file per ticket locally, or native blocking links on a real tracker.
disable-model-invocation: true
---
# To Tickets
Break a plan, spec, or conversation into a set of **tickets** — tracer-bullet vertical slices, each declaring the tickets that **block** it.
The issue tracker and triage label vocabulary should have been provided to you — run `/setup-matt-pocock-skills` if not.
## Process
### 1. Gather context
Work from whatever is already in the conversation context. If the user passes a reference (a spec path, an issue number or URL) as an argument, fetch it and read its full body and comments.
### 2. Explore the codebase (optional)
If you have not already explored the codebase, do so to understand the current state of the code. Ticket titles and descriptions should use the project's domain glossary vocabulary, and respect ADRs in the area you're touching.
Look for opportunities to prefactor the code to make the implementation easier. "Make the change easy, then make the easy change."
### 3. Draft vertical slices
Break the work into **tracer bullet** tickets.
<vertical-slice-rules>
- Each slice cuts a narrow but COMPLETE path through every layer (schema, API, UI, tests) — vertical, NOT a horizontal slice of one layer
- A completed slice is demoable or verifiable on its own
- Each slice is sized to fit in a single fresh context window
- Any prefactoring should be done first
</vertical-slice-rules>
Give each ticket its **blocking edges** — the other tickets that must complete before it can start. A ticket with no blockers can start immediately.
**Wide refactors are the exception to vertical slicing.** A **wide refactor** is one mechanical change — rename a column, retype a shared symbol — whose **blast radius** fans across the whole codebase, so a single edit breaks thousands of call sites at once and no vertical slice can land green. Don't force it into a tracer bullet; sequence it as **expandcontract**. First expand: add the new form beside the old so nothing breaks. Then migrate the call sites over in batches sized by blast radius (per package, per directory), each batch its own ticket blocked by the expand, keeping CI green batch to batch because the old form still exists. Finally contract: delete the old form once no caller remains, in a ticket blocked by every migrate batch. When even the batches can't stay green alone, keep the sequence but let them share an integration branch that all block a final integrate-and-verify ticket — green is promised only there.
### 4. Quiz the user
Present the proposed breakdown as a numbered list. For each ticket, show:
- **Title**: short descriptive name
- **Blocked by**: which other tickets (if any) must complete first
- **What it delivers**: the end-to-end behaviour this ticket makes work
Ask the user:
- Does the granularity feel right? (too coarse / too fine)
- Are the blocking edges correct — does each ticket only depend on tickets that genuinely gate it?
- Should any tickets be merged or split further?
Iterate until the user approves the breakdown.
### 5. Publish the tickets to the configured tracker
Publish the approved tickets. **How** depends on the tracker `/setup-matt-pocock-skills` configured — the tickets are the same either way, only the shape of the blocking edges changes:
- **Local files** → write one file per ticket under `.scratch/<feature-slug>/issues/<NN>-<slug>.md`, numbered from `01` in dependency order (blockers first). Each file's "Blocked by" lists the numbers/titles it depends on. Use the per-ticket file template below — one ticket per file, never a single combined file.
- **A real issue tracker (GitHub, Linear, …)** → publish one issue per ticket in dependency order (blockers first) so each ticket's blocking edges can reference real identifiers. Use the platform's native blocking / sub-issue relationship where it has one; otherwise set each ticket's "Blocked by" to the blocking issues. Apply the `ready-for-agent` triage label unless instructed otherwise — the tickets are agent-grabbable by construction.
Work the **frontier**: any ticket whose blockers are all done. For a purely linear chain that means top to bottom.
Do NOT close or modify any parent issue.
<local-ticket-template>
# <NN><Ticket title>
**What to build:** the end-to-end behaviour this ticket makes work, from the user's perspective — not a layer-by-layer implementation list.
**Blocked by:** the numbers/titles of the tickets that gate this one, or "None — can start immediately".
**Status:** ready-for-agent
- [ ] Acceptance criterion 1
- [ ] Acceptance criterion 2
</local-ticket-template>
<issue-template>
## Parent
A reference to the parent issue on the tracker (if the source was an existing issue, otherwise omit this section).
## What to build
The end-to-end behaviour this ticket makes work, from the user's perspective — not layer-by-layer implementation.
## Acceptance criteria
- [ ] Criterion 1
- [ ] Criterion 2
## Blocked by
- A reference to each blocking ticket, or "None — can start immediately".
</issue-template>
In either form, avoid specific file paths or code snippets — they go stale fast. Exception: if a prototype produced a snippet that encodes a decision more precisely than prose can (state machine, reducer, schema, type shape), inline it and note briefly that it came from a prototype. Trim to the decision-rich parts — not a working demo, just the important bits.

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interface:
display_name: "To Tickets"
short_description: "Split a plan into tracer-bullet tickets"
policy:
allow_implicit_invocation: false

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# Writing Agent Briefs
An agent brief is a structured comment posted on a GitHub issue or PR when it moves to `ready-for-agent`. It is the authoritative specification that an AFK agent will work from. The original body and discussion are context — the agent brief is the contract.
The brief states **what the agent should do**, which stretches to both surfaces: for an issue, that's building the change from nothing; for a PR, it's what's left to do *to the existing diff* — finish it, close gaps, address review points. Same principles either way; the PR example below shows the difference.
## Principles
### Durability over precision
The issue may sit in `ready-for-agent` for days or weeks. The codebase will change in the meantime. Write the brief so it stays useful even as files are renamed, moved, or refactored.
- **Do** describe interfaces, types, and behavioral contracts
- **Do** name specific types, function signatures, or config shapes that the agent should look for or modify
- **Don't** reference file paths — they go stale
- **Don't** reference line numbers
- **Don't** assume the current implementation structure will remain the same
### Behavioral, not procedural
Describe **what** the system should do, not **how** to implement it. The agent will explore the codebase fresh and make its own implementation decisions.
- **Good:** "The `SkillConfig` type should accept an optional `schedule` field of type `CronExpression`"
- **Bad:** "Open src/types/skill.ts and add a schedule field on line 42"
- **Good:** "When a user runs `/triage` with no arguments, they should see a summary of issues needing attention"
- **Bad:** "Add a switch statement in the main handler function"
### Complete acceptance criteria
The agent needs to know when it's done. Every agent brief must have concrete, testable acceptance criteria. Each criterion should be independently verifiable.
- **Good:** "Running `gh issue list --label needs-triage` returns issues that have been through initial classification"
- **Bad:** "Triage should work correctly"
### Explicit scope boundaries
State what is out of scope. This prevents the agent from gold-plating or making assumptions about adjacent features.
## Template
```markdown
## Agent Brief
**Category:** bug / enhancement
**Summary:** one-line description of what needs to happen
**Current behavior:**
Describe what happens now. For bugs, this is the broken behavior.
For enhancements, this is the status quo the feature builds on.
**Desired behavior:**
Describe what should happen after the agent's work is complete.
Be specific about edge cases and error conditions.
**Key interfaces:**
- `TypeName` — what needs to change and why
- `functionName()` return type — what it currently returns vs what it should return
- Config shape — any new configuration options needed
**Acceptance criteria:**
- [ ] Specific, testable criterion 1
- [ ] Specific, testable criterion 2
- [ ] Specific, testable criterion 3
**Out of scope:**
- Thing that should NOT be changed or addressed in this issue
- Adjacent feature that might seem related but is separate
```
## Examples
### Good agent brief (bug)
```markdown
## Agent Brief
**Category:** bug
**Summary:** Skill description truncation drops mid-word, producing broken output
**Current behavior:**
When a skill description exceeds 1024 characters, it is truncated at exactly
1024 characters regardless of word boundaries. This produces descriptions
that end mid-word (e.g. "Use when the user wants to confi").
**Desired behavior:**
Truncation should break at the last word boundary before 1024 characters
and append "..." to indicate truncation.
**Key interfaces:**
- The `SkillMetadata` type's `description` field — no type change needed,
but the validation/processing logic that populates it needs to respect
word boundaries
- Any function that reads SKILL.md frontmatter and extracts the description
**Acceptance criteria:**
- [ ] Descriptions under 1024 chars are unchanged
- [ ] Descriptions over 1024 chars are truncated at the last word boundary
before 1024 chars
- [ ] Truncated descriptions end with "..."
- [ ] The total length including "..." does not exceed 1024 chars
**Out of scope:**
- Changing the 1024 char limit itself
- Multi-line description support
```
### Good agent brief (enhancement)
```markdown
## Agent Brief
**Category:** enhancement
**Summary:** Add `.out-of-scope/` directory support for tracking rejected feature requests
**Current behavior:**
When a feature request is rejected, the issue is closed with a `wontfix` label
and a comment. There is no persistent record of the decision or reasoning.
Future similar requests require the maintainer to recall or search for the
prior discussion.
**Desired behavior:**
Rejected feature requests should be documented in `.out-of-scope/<concept>.md`
files that capture the decision, reasoning, and links to all issues that
requested the feature. When triaging new issues, these files should be
checked for matches.
**Key interfaces:**
- Markdown file format in `.out-of-scope/` — each file should have a
`# Concept Name` heading, a `**Decision:**` line, a `**Reason:**` line,
and a `**Prior requests:**` list with issue links
- The triage workflow should read all `.out-of-scope/*.md` files early
and match incoming issues against them by concept similarity
**Acceptance criteria:**
- [ ] Closing a feature as wontfix creates/updates a file in `.out-of-scope/`
- [ ] The file includes the decision, reasoning, and link to the closed issue
- [ ] If a matching `.out-of-scope/` file already exists, the new issue is
appended to its "Prior requests" list rather than creating a duplicate
- [ ] During triage, existing `.out-of-scope/` files are checked and surfaced
when a new issue matches a prior rejection
**Out of scope:**
- Automated matching (human confirms the match)
- Reopening previously rejected features
- Bug reports (only enhancement rejections go to `.out-of-scope/`)
```
### Good agent brief (PR)
For a PR, "Current behavior" describes the state of the diff, and the brief asks the agent to finish or fix it rather than build from scratch.
```markdown
## Agent Brief
**Category:** enhancement
**Summary:** Finish the contributor's `--json` output flag for `triage list`
**Current behavior:**
The PR adds a `--json` flag that serializes the issue list to JSON. The happy
path works and the diff matches the project's command structure. Two gaps
remain: errors are still printed as human text (not JSON), and the new flag has
no test coverage.
**Desired behavior:**
With `--json`, all output — including errors — is well-formed JSON on stdout,
and the command's exit codes are unchanged. The existing human-readable output
is untouched when the flag is absent.
**Key interfaces:**
- The command's error path should emit `{ "error": string }` under `--json`
instead of the plain-text error
- Reuse the existing serializer the PR already added; don't introduce a second
**Acceptance criteria:**
- [ ] `triage list --json` emits valid JSON for both success and error cases
- [ ] Exit codes match the non-JSON command
- [ ] A test covers the `--json` success output and one error case
- [ ] Default (non-JSON) output is byte-for-byte unchanged
**Out of scope:**
- Adding `--json` to any other command
- Changing the JSON shape of the success payload the PR already defined
```
### Bad agent brief
```markdown
## Agent Brief
**Summary:** Fix the triage bug
**What to do:**
The triage thing is broken. Look at the main file and fix it.
The function around line 150 has the issue.
**Files to change:**
- src/triage/handler.ts (line 150)
- src/types.ts (line 42)
```
This is bad because:
- No category
- Vague description ("the triage thing is broken")
- References file paths and line numbers that will go stale
- No acceptance criteria
- No scope boundaries
- No description of current vs desired behavior

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# Out-of-Scope Knowledge Base
The `.out-of-scope/` directory in a repo stores persistent records of rejected feature requests. It serves two purposes:
1. **Institutional memory** — why a feature was rejected, so the reasoning isn't lost when the issue is closed
2. **Deduplication** — when a new issue comes in that matches a prior rejection, the skill can surface the previous decision instead of re-litigating it
## Directory structure
```
.out-of-scope/
├── dark-mode.md
├── plugin-system.md
└── graphql-api.md
```
One file per **concept**, not per issue. Multiple issues requesting the same thing are grouped under one file.
## File format
The file should be written in a relaxed, readable style — more like a short design document than a database entry. Use paragraphs, code samples, and examples to make the reasoning clear and useful to someone encountering it for the first time.
```markdown
# Dark Mode
This project does not support dark mode or user-facing theming.
## Why this is out of scope
The rendering pipeline assumes a single color palette defined in
`ThemeConfig`. Supporting multiple themes would require:
- A theme context provider wrapping the entire component tree
- Per-component theme-aware style resolution
- A persistence layer for user theme preferences
This is a significant architectural change that doesn't align with the
project's focus on content authoring. Theming is a concern for downstream
consumers who embed or redistribute the output.
```ts
// The current ThemeConfig interface is not designed for runtime switching:
interface ThemeConfig {
colors: ColorPalette; // single palette, resolved at build time
fonts: FontStack;
}
```
## Prior requests
- #42 — "Add dark mode support"
- #87 — "Night theme for accessibility"
- #134 — "Dark theme option"
```
### Naming the file
Use a short, descriptive kebab-case name for the concept: `dark-mode.md`, `plugin-system.md`, `graphql-api.md`. The name should be recognizable enough that someone browsing the directory understands what was rejected without opening the file.
### Writing the reason
The reason should be substantive — not "we don't want this" but why. Good reasons reference:
- Project scope or philosophy ("This project focuses on X; theming is a downstream concern")
- Technical constraints ("Supporting this would require Y, which conflicts with our Z architecture")
- Strategic decisions ("We chose to use A instead of B because...")
The reason should be durable. Avoid referencing temporary circumstances ("we're too busy right now") — those aren't real rejections, they're deferrals.
## When to check `.out-of-scope/`
During triage (Step 1: Gather context), read all files in `.out-of-scope/`. When evaluating a new issue:
- Check if the request matches an existing out-of-scope concept
- Matching is by concept similarity, not keyword — "night theme" matches `dark-mode.md`
- If there's a match, surface it to the maintainer: "This is similar to `.out-of-scope/dark-mode.md` — we rejected this before because [reason]. Do you still feel the same way?"
The maintainer may:
- **Confirm** — the new issue gets added to the existing file's "Prior requests" list, then closed
- **Reconsider** — the out-of-scope file gets deleted or updated, and the issue proceeds through normal triage
- **Disagree** — the issues are related but distinct, proceed with normal triage
## When to write to `.out-of-scope/`
Only when an **enhancement** (not a bug) is *rejected* as `wontfix`. This applies to enhancement PRs exactly as it does to issues — a rejected PR is recorded here so the same request doesn't return as fresh code.
Do **not** write here when something is closed as `wontfix` because it's **already implemented**. That's a built feature, not a rejected one; recording it would poison the dedup checks with false rejections. Instead, the closing comment points to where the feature already lives.
The flow:
1. Maintainer decides a feature request is out of scope
2. Check if a matching `.out-of-scope/` file already exists
3. If yes: append the new issue to the "Prior requests" list
4. If no: create a new file with the concept name, decision, reason, and first prior request
5. Post a comment on the issue explaining the decision and mentioning the `.out-of-scope/` file
6. Close the issue with the `wontfix` label
## Updating or removing out-of-scope files
If the maintainer changes their mind about a previously rejected concept:
- Delete the `.out-of-scope/` file
- The skill does not need to reopen old issues — they're historical records
- The new issue that triggered the reconsideration proceeds through normal triage

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---
name: triage
description: Move issues and external PRs through a state machine of triage roles — categorise, verify, grill if needed, and write agent-ready briefs.
disable-model-invocation: true
---
# Triage
Move issues on the project issue tracker through a small state machine of triage roles.
If this repo treats external pull requests as a request surface (see the issue-tracker config), triage covers them too: **a PR is an issue with attached code** — same roles, same states, same machine, with a few deltas marked "for a PR" below. Resolve a bare `#42` to an issue or PR per the tracker config.
Every comment or issue posted to the issue tracker during triage **must** start with this disclaimer:
```
> *This was generated by AI during triage.*
```
## Reference docs
- [AGENT-BRIEF.md](AGENT-BRIEF.md) — how to write durable agent briefs
- [OUT-OF-SCOPE.md](OUT-OF-SCOPE.md) — how the `.out-of-scope/` knowledge base works
## Roles
Two **category** roles:
- `bug` — something is broken
- `enhancement` — new feature or improvement
Five **state** roles:
- `needs-triage` — maintainer needs to evaluate
- `needs-info` — waiting on reporter for more information
- `ready-for-agent` — fully specified, ready for an AFK agent
- `ready-for-human` — needs human implementation
- `wontfix` — will not be actioned
For a PR, the same states read against the attached code: `ready-for-agent` means a brief is attached and an agent should take the next step on the diff; `ready-for-human` means it's ready for a human to merge.
Every triaged issue should carry exactly one category role and one state role. If state roles conflict, flag it and ask the maintainer before doing anything else.
These are canonical role names — the actual label strings used in the issue tracker may differ. The mapping should have been provided to you - run `/setup-matt-pocock-skills` if not.
State transitions: an unlabeled issue normally goes to `needs-triage` first; from there it moves to `needs-info`, `ready-for-agent`, `ready-for-human`, or `wontfix`. `needs-info` returns to `needs-triage` once the reporter replies. The maintainer can override at any time — flag transitions that look unusual and ask before proceeding.
## Invocation
The maintainer invokes `/triage` and describes what they want in natural language. Interpret the request and act. Examples:
- "Show me anything that needs my attention"
- "Let's look at #42" (issue or PR)
- "Move #42 to ready-for-agent"
- "What's ready for agents to pick up?"
## Show what needs attention
Query the issue tracker and present three buckets, oldest first:
1. **Unlabeled** — never triaged.
2. **`needs-triage`** — evaluation in progress.
3. **`needs-info` with reporter activity since the last triage notes** — needs re-evaluation.
When PRs are in scope, include external PRs in these buckets and tag each line `[PR]` or `[issue]`. Discovery surfaces only *external* PRs (the tracker config defines who counts as external) — a collaborator's in-flight PR is not triage work. This filter is discovery-only; an explicitly named PR is always triaged regardless of author.
Show counts and a one-line summary per item. Let the maintainer pick.
## Triage a specific issue or PR
1. **Gather context.** Read the full issue or PR (body, comments, labels, author, dates; for a PR, the diff too). Parse any prior triage notes so you don't re-ask resolved questions. Explore the codebase using the project's domain glossary, respecting ADRs in the area. Run two checks against the codebase: (a) **redundancy** — search for an existing implementation of the requested behavior by domain concept (not just the request's wording), and report where you looked. If found, it's an already-implemented `wontfix` (step 5). (b) **prior rejection** — read `.out-of-scope/*.md` and surface any that resembles this request.
2. **Recommend.** Tell the maintainer your category and state recommendation with reasoning, plus a brief codebase summary relevant to the request — including whether it's already implemented. Wait for direction.
3. **Verify the claim.** Before any grilling, check that the claim holds up. For a bug, reproduce it from the reporter's steps. For a PR, confirm the diff does what it claims — check it out, run the relevant tests or commands. Report what happened: confirmed (with code path), failed, or insufficient detail (a strong `needs-info` signal). A confirmed verification makes a much stronger agent brief.
4. **Grill (if needed).** If the request needs fleshing out, run the `/grilling` and `/domain-modeling` skills together — grill it into shape one question at a time, sharpening domain terms and updating `CONTEXT.md`/ADRs inline as decisions land.
5. **Apply the outcome:**
- `ready-for-agent` — post an agent brief comment ([AGENT-BRIEF.md](AGENT-BRIEF.md)).
- `ready-for-human` — same structure as an agent brief, but note why it can't be delegated (judgment calls, external access, design decisions, manual testing).
- `needs-info` — post triage notes (template below).
- `wontfix` — close, with the comment depending on *why*:
- **Already implemented** — the change already exists in the codebase. Point to where it lives; do **not** write to `.out-of-scope/` (that KB is for *rejected* requests, not built ones).
- **Rejected (bug)** — polite explanation, then close.
- **Rejected (enhancement)** — write to `.out-of-scope/`, link to it from a comment, then close ([OUT-OF-SCOPE.md](OUT-OF-SCOPE.md)).
- `needs-triage` — apply the role. Optional comment if there's partial progress.
## Quick state override
If the maintainer says "move #42 to ready-for-agent", trust them and apply the role directly. Confirm what you're about to do (role changes, comment, close), then act. Skip grilling. If moving to `ready-for-agent` without a grilling session, ask whether they want to write an agent brief.
## Needs-info template
```markdown
## Triage Notes
**What we've established so far:**
- point 1
- point 2
**What we still need from you (@reporter):**
- question 1
- question 2
```
Capture everything resolved during grilling under "established so far" so the work isn't lost. Questions must be specific and actionable, not "please provide more info".
## Resuming a previous session
If prior triage notes exist on the issue or PR, read them, check whether the reporter has answered any outstanding questions, and present an updated picture before continuing. Don't re-ask resolved questions.

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interface:
display_name: "Triage"
short_description: "Move issues through triage roles"
policy:
allow_implicit_invocation: false

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---
name: ubiquitous-language
description: Extract a DDD-style ubiquitous language glossary from the current conversation, flagging ambiguities and proposing canonical terms. Saves to UBIQUITOUS_LANGUAGE.md. Use when user wants to define domain terms, build a glossary, harden terminology, create a ubiquitous language, or mentions "domain model" or "DDD".
disable-model-invocation: true
---
# Ubiquitous Language
Extract and formalize domain terminology from the current conversation into a consistent glossary, saved to a local file.
## Process
1. **Scan the conversation** for domain-relevant nouns, verbs, and concepts
2. **Identify problems**:
- Same word used for different concepts (ambiguity)
- Different words used for the same concept (synonyms)
- Vague or overloaded terms
3. **Propose a canonical glossary** with opinionated term choices
4. **Write to `UBIQUITOUS_LANGUAGE.md`** in the working directory using the format below
5. **Output a summary** inline in the conversation
## Output Format
Write a `UBIQUITOUS_LANGUAGE.md` file with this structure:
```md
# Ubiquitous Language
## Order lifecycle
| Term | Definition | Aliases to avoid |
| ----------- | ------------------------------------------------------- | --------------------- |
| **Order** | A customer's request to purchase one or more items | Purchase, transaction |
| **Invoice** | A request for payment sent to a customer after delivery | Bill, payment request |
## People
| Term | Definition | Aliases to avoid |
| ------------ | ------------------------------------------- | ---------------------- |
| **Customer** | A person or organization that places orders | Client, buyer, account |
| **User** | An authentication identity in the system | Login, account |
## Relationships
- An **Invoice** belongs to exactly one **Customer**
- An **Order** produces one or more **Invoices**
## Example dialogue
> **Dev:** "When a **Customer** places an **Order**, do we create the **Invoice** immediately?"
> **Domain expert:** "No — an **Invoice** is only generated once a **Fulfillment** is confirmed. A single **Order** can produce multiple **Invoices** if items ship in separate **Shipments**."
> **Dev:** "So if a **Shipment** is cancelled before dispatch, no **Invoice** exists for it?"
> **Domain expert:** "Exactly. The **Invoice** lifecycle is tied to the **Fulfillment**, not the **Order**."
## Flagged ambiguities
- "account" was used to mean both **Customer** and **User** — these are distinct concepts: a **Customer** places orders, while a **User** is an authentication identity that may or may not represent a **Customer**.
```
## Rules
- **Be opinionated.** When multiple words exist for the same concept, pick the best one and list the others as aliases to avoid.
- **Flag conflicts explicitly.** If a term is used ambiguously in the conversation, call it out in the "Flagged ambiguities" section with a clear recommendation.
- **Only include terms relevant for domain experts.** Skip the names of modules or classes unless they have meaning in the domain language.
- **Keep definitions tight.** One sentence max. Define what it IS, not what it does.
- **Show relationships.** Use bold term names and express cardinality where obvious.
- **Only include domain terms.** Skip generic programming concepts (array, function, endpoint) unless they have domain-specific meaning.
- **Group terms into multiple tables** when natural clusters emerge (e.g. by subdomain, lifecycle, or actor). Each group gets its own heading and table. If all terms belong to a single cohesive domain, one table is fine — don't force groupings.
- **Write an example dialogue.** A short conversation (3-5 exchanges) between a dev and a domain expert that demonstrates how the terms interact naturally. The dialogue should clarify boundaries between related concepts and show terms being used precisely.
<example>
## Example dialogue
> **Dev:** "How do I test the **sync service** without Docker?"
> **Domain expert:** "Provide the **filesystem layer** instead of the **Docker layer**. It implements the same **Sandbox service** interface but uses a local directory as the **sandbox**."
> **Dev:** "So **sync-in** still creates a **bundle** and unpacks it?"
> **Domain expert:** "Exactly. The **sync service** doesn't know which layer it's talking to. It calls `exec` and `copyIn` — the **filesystem layer** just runs those as local shell commands."
</example>
## Re-running
When invoked again in the same conversation:
1. Read the existing `UBIQUITOUS_LANGUAGE.md`
2. Incorporate any new terms from subsequent discussion
3. Update definitions if understanding has evolved
4. Re-flag any new ambiguities
5. Rewrite the example dialogue to incorporate new terms

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interface:
display_name: "Ubiquitous Language"
short_description: "Build a shared domain glossary"
policy:
allow_implicit_invocation: false

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---
name: wayfinder
description: Plan a huge chunk of work — more than one agent session can hold — as a shared map of decision tickets on your issue tracker, and resolve them one at a time until the way to the destination is clear.
disable-model-invocation: true
---
A loose idea has arrived — too big for one agent session, and wrapped in fog: the way from here to the **destination** isn't visible yet. Wayfinding is about finding that way, not charging at the destination. This skill charts the way as a **shared map** on the repo's issue tracker, then works its **decision tickets** — questions whose resolution is a decision, not slices of a build to execute — one at a time until the route is clear.
The destination varies per effort, and naming it is the first act of charting — it shapes every ticket. It might be a spec to hand off and iterate on, a decision to lock before planning starts, or a change made in place like a data-structure migration. The map is domain-agnostic — engineering work, course content, whatever fits the shape.
## Plan, don't do
Wayfinder is **planning** by default: each ticket resolves a decision, and the map is done when the way is clear — nothing left to decide before someone goes and does the thing. The pull to just do the work is usually the signal you've reached the edge of the map and it's time to hand off. An effort can override this in its **Notes** — carrying execution into the map itself — but absent that, produce decisions, not deliverables.
## Refer by name
Every map and ticket is an issue, so it has a **name** — its title. In everything the human reads — narration, the map's Decisions-so-far — refer to it by that name, never by a bare id, number, or slug. A wall of `#42, #43, #44` is illegible; names read at a glance. The id and URL don't vanish — a name wraps its link — but they ride *inside* the name, never stand in for it.
## The Map
The map is a single issue on this repo's issue tracker, labelled `wayfinder:map` — the canonical artifact. Its tickets are child issues of the map.
The map is an **index**, not a store. It lists the decisions made and points at the tickets that hold their detail; a decision lives in exactly one place — its ticket — so the map never restates it, only gists it and links.
**Where the map, its child tickets, blocking, and frontier queries physically live is tracker-specific.** The issue tracker should have been provided to you — run `/setup-matt-pocock-skills` if not. Consult the tracker doc's "Wayfinding operations" section for how _this_ repo expresses them. If no tracker has been provided, default to the local-markdown tracker.
### The map body
The whole map at low resolution, loaded once per session. Open tickets are **not** listed — they are open child issues, found by query.
```markdown
## Destination
<what reaching the end of this map looks like the spec, decision, or change this effort is finding its way to. One or two lines; every session orients to it before choosing a ticket.>
## Notes
<domain; skills every session should consult; standing preferences for this effort>
## Decisions so far
<!-- the index — one line per closed ticket: enough to judge relevance, then zoom the link for the detail the ticket holds -->
- [<closed ticket title>](link) — <one-line gist of the answer>
## Not yet specified
<!-- see "Fog of war": in-scope fog you can't ticket yet; graduates as the frontier advances -->
## Out of scope
<!-- see "Out of scope": work ruled beyond the destination; closed, never graduates -->
```
### Tickets
Each ticket is a **child issue** of the map; the tracker's issue id is its identity. Its body is the question, sized to one 100K token agent session:
```markdown
## Question
<the decision or investigation this ticket resolves>
```
Each ticket carries a `wayfinder:<type>` label — one of `research`, `prototype`, `grilling`, `task` (see [Ticket Types](#ticket-types)).
A session **claims** a ticket by assigning it to the dev driving the map, **first**, before any work, so concurrent sessions skip it. That assignee _is_ the claim: an open, unassigned ticket is unclaimed.
Blocking uses the tracker's **native** dependency relationship — essential because it renders the frontier _visually_ in the tracker's own UI, so the human sees what's takeable without opening the map. Only a tracker that lacks native blocking falls back to a body convention. A ticket is **unblocked** when every ticket blocking it is closed; the **frontier** is the open, unblocked, unclaimed children — the edge of the known.
The answer isn't part of the body — it's recorded on resolution (see [Work through the map](#work-through-the-map)). Assets created while resolving a ticket are linked from the issue, not pasted in.
## Ticket Types
Every ticket is either **HITL** — human in the loop, worked *with* a human who speaks for themselves — or **AFK**, driven by the agent alone. A HITL ticket only resolves through that live exchange; the agent never stands in for the human's side of it (a grilling agent that answers its own questions has broken this).
- **Research** (AFK): Reading documentation, third-party APIs, or local resources like knowledge bases to surface a fact a decision waits on. Resolved by a `/research` **subagent**. Use when knowledge outside the current working directory is required.
- **Prototype** (HITL): Raise the fidelity of the discussion by making a cheap, rough, concrete artifact to react to — an outline, a rough take, a stub, or UI/logic code via the /prototype skill. Links the prototype as an asset. Use when "how should it look" or "how should it behave" is the key question.
- **Grilling** (HITL): Conversation via the /grilling and /domain-modeling skills, one question at a time. The default case.
- **Task** (HITL or AFK): Manual work that must happen before a *decision* can be made — nothing to decide, prototype, or research, but the discussion is blocked until it's done. Signing up for a service so its API can be judged, provisioning access, moving data so its shape can be seen. This is the one type that *does* rather than decides — and it earns its place by unblocking a decision, not by delivering the destination. The agent drives it alone where it can (AFK); otherwise it hands the human a precise checklist (HITL). Resolved when the work is done; the answer records what was done and any resulting facts (credentials location, new URLs, row counts) later tickets depend on.
## Fog of war
The map is _deliberately_ incomplete: don't chart what you can't yet see. Beyond the live tickets lies the **fog of war** — the dim view of decisions and investigations you can tell are coming but can't yet pin down, because they hang on questions still open. Resolving a ticket clears the fog ahead of it, graduating whatever's now specifiable into fresh tickets — one at a time, until the way to the destination is clear and no tickets remain.
The map's **Not yet specified** section is where that dim view is written down: the suspected question, the area to revisit later. It's the undiscovered frontier _toward_ the destination — everything here is in scope, just not sharp enough to ticket. Write as loosely or as fully as the view allows; it doubles as a signpost for collaborators reading where the effort is headed.
**Fog or ticket?** The test is whether you can state the question precisely now — _not_ whether you can answer it now.
- **Ticket when** the question is already sharp — even if it's blocked and you can't act on it yet.
- **Not yet specified when** you can't yet phrase it that sharply. Don't pre-slice the fog into ticket-sized pieces: it's coarser than a ticket, and one patch may graduate into several tickets, or none, once the frontier reaches it.
**Not yet specified** excludes what's already decided (Decisions so far), what's already a live ticket, and what's out of scope (the next section).
## Out of scope
Fog only ever gathers _toward_ the destination. The destination fixes the scope, so work beyond it is **out of scope** — it isn't fog, and it doesn't belong in **Not yet specified**. It gets its own **Out of scope** section on the map: work you've consciously ruled out of _this_ effort. Scope, not sharpness, lands it here.
Out-of-scope work never graduates — the frontier stops at the destination — so it returns only if the destination is redrawn, and then as a fresh effort, not a resumption.
Ruling something out of scope is a scoping act, not a step on the route. When a ticket that already exists turns out to sit past the destination — mis-scoped in while charting, or exposed by a resolution — **close it** (a closed ticket is unambiguously off the frontier) and leave one line in the **Out of scope** section: the gist plus why it's out of scope, linking the closed ticket. It stays out of **Decisions so far**, which records the route actually walked — a scope boundary isn't a step on it.
## Invocation
Two modes. Either way, **never resolve more than one ticket per session** — with the exception of research tickets.
### Chart the map
User invokes with a loose idea.
1. **Name the destination.** Run a `/grilling` and `/domain-modeling` session to pin down what this map is finding its way to — the spec, decision, or change. The destination fixes the scope, so it's settled first.
2. **Map the frontier.** Grill again, **breadth-first** this time: fan out across the whole space rather than deep on any one thread, surfacing the open decisions and the first steps takeable now. **If this surfaces no fog** — the way to the destination is already clear, the whole journey small enough for one session — you don't need a map. Stop and ask the user how they'd like to proceed.
3. **Create the map** (label `wayfinder:map`): Destination and Notes filled in, Decisions-so-far empty, the fog sketched into **Not yet specified**.
4. **Create the tickets you can specify now** as child issues of the map — then wire blocking edges in a **second pass** (issues need ids before they can reference each other). Wiring sorts them into the frontier and the blocked; everything you can't yet specify stays in the fog — the **Not yet specified** section.
5. **Fire the research subagents.** For each `research` ticket you just created, spin up a `/research` subagent to resolve it in parallel, capturing its findings on a throwaway `research/<name>` branch with a context pointer from the ticket.
6. Stop — charting is one session's work; it hand-resolves nothing.
### Work through the map
User invokes with a map (URL or number). A ticket is **optional** — without one, you pick the next decision, not the user.
1. Load the **map** — the low-res view, not every ticket body.
2. Choose the ticket. If the user named one, use it. Otherwise take the first frontier ticket in order. **Claim it**: assign it to yourself before any work.
3. Resolve it — **zoom as needed**: fetch the full body of any related or closed ticket on demand; invoke the skills the `## Notes` block names. If in doubt, use `/grilling` and `/domain-modeling`.
4. Record the resolution: post the answer as a **resolution comment**, **close** the issue, and **append a context pointer** to the map's Decisions-so-far.
5. Add newly-surfaced tickets (create-then-wire); graduate any fog the answer has made specifiable, clearing each graduated patch from **Not yet specified** so it lives only as its new ticket. If the answer reveals a ticket — this one or another — sits beyond the destination, **rule it out of scope** rather than resolving it on the route. If the decision invalidates other parts of the map, update or delete those tickets.
The user may run unblocked tickets in parallel, so expect other sessions to be editing the tracker concurrently.

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interface:
display_name: "Wayfinder"
short_description: "Map a large effort as decision tickets"
policy:
allow_implicit_invocation: false

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---
name: wizard
description: Generate an interactive bash wizard that walks a human through a manual procedure — third-party setup, a one-off migration, an A→B state transition — opening URLs, capturing values, confirming each step, and writing .env files and GitHub Actions secrets.
disable-model-invocation: true
---
# Wizard
A **wizard** is a bash script that walks a human, step by step, through a manual procedure that's tedious to do by hand and tedious to re-explain to an AI every time. It opens each URL, says exactly what to click and copy, captures the values, writes them where they belong (`.env`, GitHub secrets), confirms at every stage, and shows how much is left. It might configure third-party services, run a one-off migration, or move the project from one state to another.
The delightful UX is already solved by [template.sh](template.sh) — progress with time-remaining, confirmation gates, cross-platform URL opening (including WSL), hidden secret entry, idempotent `.env` upserts, `gh secret`/`gh variable` writes, and a closing summary. **Your job is only to scope the procedure and author its stages.** The library above the `STAGES` marker is identical in every wizard; that consistency is the point — never hand-edit it.
A wizard is ephemeral by default — built for one run, saved to a scratch or `scripts/` path, deleted when the job's done. Commit it only when the user wants a repeatable setup path that should live in the repo.
## Process
### 1. Scope the procedure
Work out every manual step the human must take and every value that gets captured along the way. Read the repo first — don't ask cold:
- For setup: `.env`, `.env.example`, `.env.*`, `README`, `docker-compose*`, framework config, and `.github/workflows/*` (every `secrets.*` / `vars.*` reference is a value the wizard must produce).
- For a migration or transition: the current state, the target state, and the irreversible actions between them.
Then show the user the ordered list of stages and the values each produces, and confirm — they may add, drop, or reorder.
**Done when:** every stage is named in order, and for each captured value you know (a) where the human gets it, (b) where it's written (`.env`, a GitHub secret, both, or nowhere — some stages are pure actions), and (c) whether it's secret (hidden entry) or public.
### 2. Map each stage's journey
For each stage, write the precise path a human follows: which URL to open, what to do there, where a value is shown, which variable it fills — e.g. "Dashboard → Developers → API keys → Reveal test key → copy". Where you don't actually know the current UI or the exact command, say so and ask the user or check the docs — never invent steps that may not exist.
**Done when:** every stage traces to concrete instructions a stranger could follow.
### 3. Author the wizard
Copy `template.sh` to the target path. Replace the example stage with one `stage` per step, in dependency order. Use the library helpers — `stage`, `say`/`step`, `open_url`, `ask`/`ask_secret`, `write_env`, `set_secret`/`set_var`, `pause`/`confirm` — and set `TOTAL_STAGES` and `TOTAL_MINUTES` to honest estimates (this drives the time-remaining display).
Hold the bar the template sets: open the URL before asking for its value, use `ask_secret` for anything secret, `write_env` every persisted value, `set_secret` only the values CI actually needs, and `confirm` before any irreversible action. Each `stage` clears the screen so only the current step is visible — keep a stage to one focused task so nothing the human needs scrolls away. Don't touch the library above the marker.
### 4. Verify and hand off
- `bash -n <script>`; run `shellcheck` if available.
- `chmod +x <script>`.
- Don't run it end-to-end yourself — it opens browsers and blocks on human input. Trace it statically instead: every value from step 1 is captured and lands where step 1 said, and every `set_secret` name exactly matches a `secrets.*` reference in CI.
- Tell the user how to run it. If it's a repeatable setup path, commit it and link it from the README so the next person runs the script instead of asking an AI.

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interface:
display_name: "Wizard"
short_description: "Generate an interactive setup wizard"
policy:
allow_implicit_invocation: false

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#!/usr/bin/env bash
#
# A wizard — walks a human through a manual procedure step by step.
# Generated by the /wizard skill.
#
# Everything above the "STAGES" marker is the wizard library: do not hand-edit
# it. Author the per-step stages below the marker.
set -euo pipefail
# ──────────────────────────────────────────────────────────────────────────
# Wizard library — delightful, consistent UX. Identical across every wizard.
# ──────────────────────────────────────────────────────────────────────────
if [[ -t 1 ]] && command -v tput >/dev/null 2>&1 && [[ "$(tput colors 2>/dev/null || echo 0)" -ge 8 ]]; then
BOLD=$(tput bold); DIM=$(tput dim); RESET=$(tput sgr0)
BLUE=$(tput setaf 4); GREEN=$(tput setaf 2); YELLOW=$(tput setaf 3); RED=$(tput setaf 1)
else
BOLD=""; DIM=""; RESET=""; BLUE=""; GREEN=""; YELLOW=""; RED=""
fi
# Author sets these two at the top of the stages section.
TOTAL_STAGES=0
TOTAL_MINUTES=0
_STAGE_INDEX=0
_MINUTES_ELAPSED=0
ENV_FILE="${ENV_FILE:-.env}"
WRITTEN_ENV=() # KEYs written to ENV_FILE this run
WRITTEN_SECRET=() # secret NAMEs set this run
SKIPPED=() # things we couldn't do (e.g. gh missing)
# _clear — wipe the terminal so only the current step is on screen. No-op when
# output isn't a terminal, so piped logs stay readable.
_clear() {
[[ -t 1 ]] || return 0
if command -v tput >/dev/null 2>&1; then tput clear; else printf '\033[2J\033[3J\033[H'; fi
}
# banner "Title" — opening frame: what this wizard does and how long it takes.
banner() {
_clear
printf '\n%s%s %s%s\n' "$BOLD" "$BLUE" "$1" "$RESET"
printf '%s %s stages · about %s minutes%s\n\n' \
"$DIM" "$TOTAL_STAGES" "$TOTAL_MINUTES" "$RESET"
printf '%s You drive the browser; this wizard tells you exactly what to do and\n' "$DIM"
printf ' captures the values you copy back. Stop any time with Ctrl-C and re-run\n'
printf ' later — it remembers values already saved.%s\n' "$RESET"
pause "Ready to start?"
}
# stage "Name" <minutes> — clear the screen, then announce a stage and show
# progress + time remaining. Clearing keeps only the current step on screen.
stage() {
_clear
_STAGE_INDEX=$((_STAGE_INDEX + 1))
local remaining=$((TOTAL_MINUTES - _MINUTES_ELAPSED))
(( remaining < 0 )) && remaining=0
_MINUTES_ELAPSED=$((_MINUTES_ELAPSED + ${2:-0}))
printf '\n%s%s▸ Stage %s/%s · %s%s %s(~%s min left)%s\n' \
"$BOLD" "$BLUE" "$_STAGE_INDEX" "$TOTAL_STAGES" "$1" "$RESET" "$DIM" "$remaining" "$RESET"
}
# say "..." — a plain instruction line.
say() { printf ' %s\n' "$1"; }
# step "..." — a numbered-feeling action the human takes in the browser.
step() { printf ' %s•%s %s\n' "$BLUE" "$RESET" "$1"; }
note() { printf ' %s%s%s\n' "$DIM" "$1" "$RESET"; }
warn() { printf ' %s⚠ %s%s\n' "$YELLOW" "$1" "$RESET"; }
# open_url URL — open in the human's browser, cross-platform incl. WSL.
open_url() {
local url="$1"
printf ' %s↗ opening%s %s\n' "$GREEN" "$RESET" "$url"
{ if command -v wslview >/dev/null 2>&1; then wslview "$url"
elif command -v explorer.exe >/dev/null 2>&1; then explorer.exe "$url"
elif command -v xdg-open >/dev/null 2>&1; then xdg-open "$url"
elif command -v open >/dev/null 2>&1; then open "$url"
else warn "couldn't open a browser — visit it manually: $url"; fi
} >/dev/null 2>&1 || warn "couldn't open a browser — visit it manually: $url"
}
# pause "msg" — wait for the human to confirm they've done the manual part.
pause() {
printf ' %s%s%s ' "$DIM" "${1:-Press Enter to continue}" "$RESET"
read -r _ || true
}
# confirm "question" — y/N gate; returns success on yes.
confirm() {
local reply=""
printf ' %s? %s [y/N] ' "$YELLOW" "$1"
read -r reply || true
[[ "$reply" =~ ^[Yy] ]]
}
# _existing KEY — current value of KEY in ENV_FILE, if any.
_existing() {
[[ -f "$ENV_FILE" ]] || return 1
local line; line=$(grep -E "^${1}=" "$ENV_FILE" | tail -n1) || return 1
printf '%s' "${line#*=}"
}
# ask KEY "Prompt" — read a value into $KEY. Offers the existing .env value as
# a default on re-runs (Enter keeps it). Visible input (non-secret).
ask() {
local key="$1" prompt="$2" current input
current=$(_existing "$key" || true)
if [[ -n "$current" ]]; then
printf ' %s%s%s %s[Enter keeps current]%s ' "$BOLD" "$prompt" "$RESET" "$DIM" "$RESET"
else
printf ' %s%s%s ' "$BOLD" "$prompt" "$RESET"
fi
read -r input || true
[[ -z "$input" && -n "$current" ]] && input="$current"
printf -v "$key" '%s' "$input"
}
# ask_secret KEY "Prompt" — like ask, but input is hidden.
ask_secret() {
local key="$1" prompt="$2" current input
current=$(_existing "$key" || true)
if [[ -n "$current" ]]; then
printf ' %s%s%s %s[Enter keeps current]%s ' "$BOLD" "$prompt" "$RESET" "$DIM" "$RESET"
else
printf ' %s%s%s ' "$BOLD" "$prompt" "$RESET"
fi
read -rs input || true
printf '\n'
[[ -z "$input" && -n "$current" ]] && input="$current"
printf -v "$key" '%s' "$input"
}
# write_env KEY VALUE — upsert KEY=VALUE into ENV_FILE (creates it; replaces
# any existing line). Idempotent.
write_env() {
local key="$1" value="$2" tmp
touch "$ENV_FILE"
tmp=$(mktemp)
grep -vE "^${key}=" "$ENV_FILE" > "$tmp" || true
printf '%s=%s\n' "$key" "$value" >> "$tmp"
mv "$tmp" "$ENV_FILE"
WRITTEN_ENV+=("$key")
printf ' %s✓ wrote%s %s → %s\n' "$GREEN" "$RESET" "$key" "$ENV_FILE"
}
# set_secret NAME VALUE — set a GitHub Actions repo secret via gh. Falls back
# to a warning (and records it) if gh is unavailable or unauthenticated.
set_secret() {
local name="$1" value="$2"
if command -v gh >/dev/null 2>&1 && gh auth status >/dev/null 2>&1; then
if printf '%s' "$value" | gh secret set "$name" >/dev/null 2>&1; then
WRITTEN_SECRET+=("$name")
printf ' %s✓ set%s GitHub secret %s\n' "$GREEN" "$RESET" "$name"
return
fi
fi
SKIPPED+=("GitHub secret $name (set it manually: gh secret set $name)")
warn "skipped GitHub secret $name — gh not ready; set it later"
}
# set_var NAME VALUE — set a GitHub Actions repo variable (non-secret).
set_var() {
local name="$1" value="$2"
if command -v gh >/dev/null 2>&1 && gh auth status >/dev/null 2>&1; then
if gh variable set "$name" --body "$value" >/dev/null 2>&1; then
printf ' %s✓ set%s GitHub variable %s\n' "$GREEN" "$RESET" "$name"
return
fi
fi
SKIPPED+=("GitHub variable $name")
warn "skipped GitHub variable $name — gh not ready; set it later"
}
# finish — clear, then a closing summary of everything configured.
finish() {
_clear
printf '\n%s%s ✓ Setup complete%s\n' "$BOLD" "$GREEN" "$RESET"
(( ${#WRITTEN_ENV[@]} )) && note "wrote ${#WRITTEN_ENV[@]} value(s) to $ENV_FILE: ${WRITTEN_ENV[*]}"
(( ${#WRITTEN_SECRET[@]} )) && note "set ${#WRITTEN_SECRET[@]} GitHub secret(s): ${WRITTEN_SECRET[*]}"
if (( ${#SKIPPED[@]} )); then
printf '\n'; warn "still to do by hand:"
for s in "${SKIPPED[@]}"; do note " - $s"; done
fi
printf '\n'
}
# ──────────────────────────────────────────────────────────────────────────
# STAGES — author this section. One stage() per step the human takes.
# Replace the example below. Set the two totals to match the stages you write.
# ──────────────────────────────────────────────────────────────────────────
TOTAL_STAGES=1
TOTAL_MINUTES=5
banner "Stripe setup"
# ── Example stage: replace with your real steps ───────────────────────────
stage "Stripe — API keys" 5
say "We'll grab your Stripe test keys and store them for local dev + CI."
open_url "https://dashboard.stripe.com/test/apikeys"
step "On the API keys page, copy the Publishable key (starts pk_test_)."
ask STRIPE_PUBLISHABLE_KEY "Paste the publishable key:"
step "Click 'Reveal test key' on the Secret key row, then copy it."
ask_secret STRIPE_SECRET_KEY "Paste the secret key:"
write_env STRIPE_PUBLISHABLE_KEY "$STRIPE_PUBLISHABLE_KEY"
write_env STRIPE_SECRET_KEY "$STRIPE_SECRET_KEY"
set_secret STRIPE_SECRET_KEY "$STRIPE_SECRET_KEY" # CI needs this one
# ──────────────────────────────────────────────────────────────────────────
finish

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---
name: writing-beats
description: Writing, exploit — assemble raw material into a journey of beats, grounding each term before a beat leans on it.
disable-model-invocation: true
---
<what-to-do>
The user has passed (or will pass) a markdown file of raw material. This is **exploit**: the exploring is done, the pile is fixed — commit to a path through it and mine the pile to fill each beat.
If the user did not say where to save the article, ask once and remember the path.
Then run a beat-by-beat journey, choose-your-own-adventure style:
1. **Establish the prerequisites.** Before any beats, settle with the user what the audience already knows walking in — the concepts that are **grounded** from the start. Everything else must be grounded by a beat before a later beat can use it. See [Grounding](#grounding).
2. Write 23 candidate **starting beats**, drawn from the raw material. Each is a different entry point into the article. Each may only lean on grounded concepts; note what new concepts each one grounds. Show the user the beats before writing to the article file. The user picks one. Preview what beats that pick unlocks — as if the user is seeing a little way down the path.
3. Once the user picks a starting beat, write **only that beat** to the article file. A beat may be one sentence or several paragraphs — whatever that beat naturally is. Stop there.
4. Re-read the article file from disk. Then offer 23 candidate **next beats** — different directions the journey could pivot to from where the article now stands. Each must be reachable from the current grounded set; note what each one grounds.
5. Loop steps 35 until the article reaches a natural end.
</what-to-do>
<supporting-info>
## Grounding
Every **concept** has to be **grounded** before a beat can lean on it: the audience either walked in knowing it or met it in an earlier beat. A beat that reaches for an ungrounded concept loses the reader — that is the one move the journey can't make. The unit is the concept, not the word for it: a beat can lean on an idea the reader lacks even with no jargon in sight. Where a concept has a name — a **term** — grounding it means landing the idea and the term together.
A concept gets grounded one of two ways:
- **Prerequisite** — grounded before the first beat. The audience brings it. Fixed at the start.
- **Introduced** — a beat establishes it, and from then on it's grounded for every later beat.
So each beat does two jobs: it **requires** concepts that are already grounded, and it **grounds** new ones. Keep a running list of what's grounded so far, and update it each time a beat lands.
This is what shapes the choose-your-own-adventure. A candidate beat is only reachable if everything it requires is already grounded; picking a beat that grounds concept X unlocks every beat that was waiting on X. When you offer next beats, they must all be reachable from the current grounded set — and say what each one grounds, so the user can see which paths it opens.
The big lever is what you make a prerequisite versus what you ground inside the piece. Demand too much up front and you shut out readers who don't have it; ground too much inside and the early beats drown in definitions. Settle this with the user when you establish prerequisites, and revisit it whenever a tempting beat turns out to require a concept nothing has grounded yet — the fix is either a grounding beat before it, or promoting the concept to a prerequisite.
## What is a beat
A beat is one move in the journey. It does one thing — sets a scene, lands a point, asks a question, drops an aside, twists the angle. Then it stops, leaving the reader at a place where the next beat can pivot.
A beat is sized by what it needs:
- A single sentence if that's all the move is ("And then nothing happened for three weeks.").
- A short paragraph if the move needs setup.
- Multiple paragraphs if the beat is a self-contained vignette, argument, or example.
If a "beat" needs five paragraphs and three subheadings, it's not a beat — it's two beats glued together. Split it.
## Pulling from the pile
Pull material from the raw pile to populate each beat. You can paraphrase, split, recombine, or quote. The pile is a quarry.
## Ending the journey
The article ends when the journey is complete — not when the pile is empty. Most piles will have leftover fragments that don't make it in. That is fine; that is the point of having more raw material than you need.
## Writing rhythm
- Append one beat at a time. Never write ahead.
- Re-read the article file from disk before every write. Preserve user edits absolutely.
- If the user edits a previous beat substantially, let it change what comes next.
- If the user says "rewrite that beat" or "go back and try a different beat 3", do it — edit in place, leave the rest alone.
</supporting-info>

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interface:
display_name: "Writing Beats"
short_description: "Assemble raw material into beats"
policy:
allow_implicit_invocation: false

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