Add council review tally command

2026-03-19 15:26:11 +08:00
parent dd6a0e31b6
commit 740a7b4acd
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+# Orch Council Tally
+
+## Status
+
+- `completed`
+
+## Owner
+
+- codex
+
+## Started At
+
+- `2026-03-19`
+
+## Goal
+
+- implement `orch council tally` so completed reviewer outputs can be parsed, grouped, and persisted as council findings and grouped recommendations
+
+## Scope
+
+- parse reviewer output JSON from completed council reviewer threads
+- persist parsed findings into `council_findings`
+- group recommendations into `consensus`, `majority`, and `minority` buckets and persist them into `council_groups`
+- add integration tests for normal and strict similarity modes
+- update the implementation roadmap and archive this workstream when complete
+
+## Checklist
+
+- [x] inspect council tally docs and current council storage
+- [x] implement council tally store and CLI command
+- [x] add integration coverage for normal and strict tally behavior
+- [x] run `go test ./...`
+- [x] update `docs/implementation-roadmap.md`
+- [x] archive this roadmap with a completion summary
+
+## Files
+
+- `docs/roadmaps/archive/orch-council-tally.md`
+- `docs/implementation-roadmap.md`
+- `docs/council-review.md`
+- `internal/store/council.go`
+- `internal/cli/orch/council.go`
+- `internal/cli/orch/council_tally.go`
+- `internal/cli/orch/integration_test.go`
+
+## Decisions
+
+- read reviewer outputs from the latest `result` message on each reviewer thread
+- require reviewer outputs to be valid structured JSON before tallying
+- use a simple normalized proposal grouping strategy for v1, with `strict` preserving wording differences and `normal` grouping by normalized intent tokens
+
+## Blockers
+
+- none
+
+## Next Step
+
+- move on to `orch council report`
+
+## Completion Summary
+
+- `orch council tally` now parses structured reviewer output JSON from completed reviewer result messages
+- parsed reviewer findings are persisted into `council_findings`, and grouped recommendations are persisted into `council_groups`
+- tally supports `normal` and `strict` similarity modes and computes `consensus`, `majority`, and `minority` buckets