- _supplement_decision_logs: executing evals missing a decision log get a
platform-derived execute_session (deficit) or start_analysis (all sessions
done) entry. Audit backfill only — records observable state, does not change
agent execution. Called each scan tick after requeue+scan.
- t480 legacy cron workers (5) disabled: superseded by platform-triggered
headless agent (plan C); they kept firing every minute and failing on
Channel-required.
openclaw agent has no cron state; a bare 'agenteval-intelligent-worker'
message made the worker skill decide then 'wait for the next tick',
deadlocking (task assigned, session never created). The trigger message now
demands '立即完成当前任务，不要等待下一节拍' and, when all sessions are
done, delegates to agenteval-intelligent-analyst. Verified end-to-end on
t480: 1h-window eval went executing -> session (2 real turns) -> close ->
report -> completed, fully agent-driven, no external IM channel.
OpenClaw cron requires a channel (announce->last fail-closed); webchat is a
Control-UI feature, not an addressable channel, and platform-side static
execution would degrade the intelligent eval into a static evaluation.
Solution (plan C): the platform keeps the scan loop and, when the queue has
a pending task, invokes the headless agent:
docker exec openclaw-eval openclaw agent --agent main \
-m agenteval-intelligent-worker --json
--deliver defaults to false, so no cron delivery channel is involved. The
worker skill runs unchanged under the OpenClaw agent (LLM decisions +
evaluator/analyst skills). Verified headless invocation returns ok.
scan_and_enqueue_tasks had no scheduler: the OpenClaw Worker wakes every
minute but the platform never enqueued executing evals, so the queue was
always empty. lifespan now starts an asyncio background task that scans
executing intelligent evals every 60s (aligned with the Worker wake),
cancelled cleanly on shutdown. Verified by a new startup test (879 total).
create_decision_log now checks for an existing log with the same
(eval_id, decision_type, context) tuple before inserting. If found, it
returns the existing row's dict instead of appending a duplicate. The
append-only audit invariant is preserved (a worker that re-emits the
same decision within a single minute no longer produces duplicate rows).
Removed the xfail guard in test_decision_log_immutability; the test
now passes (3 identical POSTs → 1 DB row).
AlertManager gains an optional openclaw_client. check_alerts records
each newly created alert and AlertManager.maybe_autoscale (called
from the async router for each alert) invokes cron_pool.scale_up(1).
scale_up itself caps at MAX_POOL_SIZE so repeated invocations are safe.
Removed the xfail guard in test_alert_autoscale_link; rewrote the test
to use task_backlog (duration_minutes=0) so a single check_alerts call
fires an alert and triggers auto-scale.
_send_webhook:
- Dedupe: skip if alert.webhook_sent is already True (guards against
repeated check_alerts ticks re-sending the same alert).
- Retry: up to 3 attempts with exponential backoff (1s, 2s) before
giving up. webhook_sent=True is persisted only on success.
Two xfail guards in test_openclaw_client_and_webhook now pass (876/4 xfail).
Replace read-check-write in task_queue.assign_task with UPDATE...WHERE
status='pending' and decide on rowcount so two concurrent workers
cannot both claim the same task. Also harden complete_task with the
same CAS pattern (status='assigned') so a worker + stuck-handler
double-complete leaves the DB in one state.
The xfail guard in test_worker_task_resilience now passes (4/4).
P1 deepening (issue #7):
S1: is the single source of truth for time-slot parsing,
slot-due checks, session deficit, priority, attention reason, and
high-severity detection. and now delegate
their internal helpers to while keeping the same signatures
(tests continue to pass via the thin wrappers).
S4: encapsulates the stuck-cron
task settlement (fail current task + enqueue retry).
calls it instead of the previous runtime import of .
No observable behaviour change — 873 passed + 5 xfailed unchanged.
- Add Cron Pool Monitor entry to sidebar menu
- Install Docker CE CLI from Aliyun mirror for container exec
- Mount Docker socket for managing openclaw-eval container
- Fix OpenClaw CLI commands (cron add/rm/list instead of automations)
- Add gateway token auth for CLI access
- Add list_decision_logs API endpoint
- Add DecisionProcess component with timeline, list, filter, and export
- Add decision log API calls to api.ts
- Add "决策过程" button in EvalDetail to access decision history
- Implement decision log export to JSON
- Pass TypeScript type checking
All 853 tests passing.
- Add metrics.py with pool utilization, task backlog, stuck rate, avg processing time, eval completion rate
- Add alerts.py with alert rules (pool utilization > 90%, task backlog > 50, stuck rate > 10%)
- Implement alert history and webhook notifications
- Add metrics and alerts APIs
- Add database migration for alert history table
- Add 11 unit tests for metrics, 10 unit tests for alerts, 8 integration tests
- Update migration tests to include new alert history table
All 853 tests passing.
- Add config_snapshot.py with save/list/get/compare functions
- Auto-save snapshots on eval creation and plan submission
- Implement snapshot query APIs (list, get single)
- Implement snapshot comparison API (diff two snapshots)
- Add 8 unit tests and 7 integration tests
Snapshots track config changes over time (created/plan_submitted/config_updated).
All 813 tests passing.
- Add OpenClawClient wrapping CLI commands (create/delete/list crons)
- Implement pool initialization, scale up/down, auto-scaling logic
- Implement cron state sync and stuck cron detection
- Add pool status and manual scaling APIs
- Add 13 unit tests and 5 integration tests
Pool automatically scales between 5-20 crons based on load.
All 778 tests passing.
Three role-split skills synced via the existing deploy pipeline:
planner produces the coarse plan for approval, evaluator self-wakes by
time distribution to run virtual-user sessions, analyst aggregates session
evidence into the structured report.
Wrap the judge prompt and two docstrings past the 120-col convention;
record three implementation rulings in the v0.9 spec (exploration read
outlets, round-based sampling, findings carrying all ratings).
report, markdown and analysis each repeated the
summarize_exploration(repo.list_by_campaign(...)) shape; collapse it
into summarize_campaign_exploration so the aggregation has one home.
Ticket 05 asks the judge review conclusions to flow into the report
verbatim; the aggregation silently dropped good/acceptable dimensions.
Collect every finding sorted poor-first and color drawer tags by rating.
E2E on t480 showed assistant bubbles rendering {'content': '...'} because
tutu replies carry msgBody as a parsed object and the router stored
str(reply.content). Coerce to the inner text before persisting.
