Single-run summary口径 (pass_rate / judged_pass_rate / avg_latency /
connectivity split) was inlined in run(), reachable only by driving a
whole async run, and report.py recomputed judged_pass_rate independently.
Extract build_run_summary — a pure function parallel to aggregate_runs
(cross-run) and combine_case_outcome (case-level). run() now collects
material and delegates; judged_pass_rate is stored in RunSummary so the
report reads it instead of recomputing.
Give EvalRun.summary a typed RunSummary value (unified RunError, lenient
legacy parsing) so readers stop reaching into a schemaless dict, and route
every cross-run rollup — dashboard, scenario ranking, trend, campaign
report — through one aggregate_runs seam. Fixes the divergence where
stats averaged pass_rate over completed-only runs while the campaign
report counted faults as 0.0. Cross-run rule (ADR-0004): genuine faults
count 0.0, user-cancelled runs are excluded from both denominators.
Add the pure scheduling seam (campaign_scheduler.decide_schedule) that, given a
static plan and window-clock offset, decides which plan entries are due and
whether the window ended — mirroring judgement.combine_case_outcome, with
time_scale confined to the clock mapping so it never touches judgement/report.
The campaign_runner shell maps injected elapsed time to a window offset, spawns
due child Runs through the existing EvalEngine.run(existing_run=...) path with
campaign_id + RunTrigger.CAMPAIGN, and persists spawned-entry indices per entry
for idempotent, restart-recoverable progress. No auto loop yet (ticket 03).
