feat: add run replay for archetype effectiveness analysis
- archeflow-decision.sh records decision points during runs - archeflow-replay.sh: timeline, whatif, compare commands - What-if replay with adjustable archetype weights - /af-replay skill for interactive use - Tests in archeflow-replay.bats
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@@ -352,6 +352,7 @@ Emit events via `./lib/archeflow-event.sh <run_id> <type> <phase> <agent> '<json
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| After agent returns | `agent.complete` | archetype, duration_ms, artifacts, summary |
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| Phase boundary | `phase.transition` | from, to, artifacts_so_far |
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| Alternative chosen | `decision` | what, chosen, alternatives, rationale |
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| Orchestrator decision (replay) | `decision.point` | archetype, input, decision, confidence — use `./lib/archeflow-decision.sh` |
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| Reviewer verdict | `review.verdict` | archetype, verdict, findings[] |
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| Fix addressing review | `fix.applied` | source, finding, file, line |
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| End of PDCA cycle | `cycle.boundary` | cycle, max_cycles, exit_condition, convergence |
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@@ -403,6 +404,12 @@ Scores stored in `.archeflow/memory/effectiveness.jsonl`. After 10+ runs, recomm
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## Run replay (decision log + what-if)
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After key choices (routing, fast-path skip, escalation), emit `decision.point` via `./lib/archeflow-decision.sh` so runs can be inspected with `./lib/archeflow-replay.sh timeline|whatif|compare <run_id>`. Weighted what-if helps estimate how much each review archetype swayed the effective ship/block outcome. See skill `af-replay`.
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---
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## Dry-Run Mode
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When `--dry-run`: Run Plan phase only. Display workflow, agent counts, confidence scores, cost estimate. Ask user to proceed. If yes, continue with `--start-from do`.
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