Deep strategic research engine — decomposes questions into parallel research threads, spawns multiple agents, and synthesizes into actionable strategic analysis
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Run one task through the V-model verification loop: CP-2 plan → CP-3 build → CP-3v component verify → CP-4 integration verify (full lane) → CP-5 acceptance. The worker never grades its own homework; evidence rows trace back to AC-n. Opt-in: invoke with /closed-loop or by asking for the closed loop, proper verification, or an evidence trail. Ordinary work does not run this.
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查看安装方法安装前可以查看交给 AI 代理的指令内容。
Mechanical verification pipeline. Every verify step emits evidence rows tied to acceptance criterion IDs (AC-n).
The harness is opt-in. Run it when:
/closed-loop <task> or /closed-loop <spec-path>.verification_harness: on in 00-inbox/MY-PROFILE.md and this is a build task.normal+ lane reaches its verify step.Do not run it on a request that did not ask for it. Notes, briefs, research, drafts, and ordinary edits are not harness runs, and a checkpoint ledger on those is pure overhead.
bash .claude/lib/lane-classify.sh explain "<task>"
bash .claude/lib/checkpoint.sh init 04-projects/harness/runs/<YYYY-MM-DD-HHmm>
| Lane | Checkpoints |
|---|---|
tiny | CP-3 → CP-5 (if mutating) |
normal | CP-1 → CP-2 → CP-3 → CP-3v → CP-5 |
full | + CP-4 + claim-verifier + CP-6 |
bug | root-cause ledger (CP-0) before CP-3 |
Record: checkpoint.sh record <run-dir> CP-0 PASS|SKIP "<lane>"
If spec exists, use its ## Acceptance criteria + traceability matrix. Else write:
04-projects/harness/runs/<id>/criteria.md using references/spec-template.md (criteria + matrix sections only).
Each criterion: falsifiable + AC-n ID + verify method.
Record: checkpoint.sh record <run-dir> CP-1 PASS "N criteria"
Map tasks → AC IDs in evidence/CP-2-plan.md. Update matrix status to pending.
Record: checkpoint.sh record <run-dir> CP-2 PASS
Worker implements. Returns deliverable path only.
retry=0
loop:
spawn task-verifier (fresh context, read-only)
merge EVIDENCE rows into evidence/ledger.md
if PASS → break
if FAIL:escalate → record CP-3v FAIL, escalate
if FAIL:fixable && retry < 2 → fix-agent → retry++
else → escalate
Copy verifier EVIDENCE rows into evidence/CP-3v-component.md.
Record: checkpoint.sh record <run-dir> CP-3v PASS|FAIL
full or multi-task)Spawn integration-verifier (read-only). Append rows to ledger.
Skip for single-task normal.
Record: checkpoint.sh record <run-dir> CP-4 PASS|SKIP
For each mutation, observe artifact (curl, screenshot, re-fetch). Emit:
EVIDENCE AC-n | CP-5 | PASS | <observation> | <artifact>
UI/UX flow changes: the post-condition is visual. Screenshot every meaningful state with whatever browser tooling the environment has, then read the image and confirm no overflow, misalignment, clipping, wrong color, or broken responsive layout before PASS. The Observation must describe what you saw; the artifact is the screenshot/GIF in evidence/. Fix any visual defect and re-capture. See CLAUDE.md → Visual Verification.
Write evidence/CP-5-acceptance.md. Traceability closure: every AC in matrix has ≥1 PASS row in ledger.
Record: checkpoint.sh record <run-dir> CP-5 PASS|FAIL
.claude/logs/loop-ledger.tsvverifiedfull lane / big task: generate an HTML rollup from references/report-template.html → 04-projects/harness/runs/<id>/report.html, filled from criteria.md + evidence/ledger.md (criteria, AC traceability, verifier verdicts, post-condition observations). Self-contained; SendUserFile it or publish as an Artifact. Skip for normal/tiny./retro <run-dir> for CP-7| Skill | Lane | CP-4 |
|---|---|---|
ultragoal | full per phase (never downgraded) | integration-verifier + north-star acceptance |
team-brief | full | claim-verifier |
comprehensive-analysis, auto-research | full | claim-verifier on cited claims |
content-factory | normal | skip |
review-cockpit | normal | skip; CP-6 is the user's approval per card |
ESCALATED — <task>
Lane: <lane> | Last CP: <CP-n>
Evidence bundle: 04-projects/harness/runs/<id>/evidence/
Open AC IDs: <list without PASS rows>
Decision needed: <one question>
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Deep strategic research engine — decomposes questions into parallel research threads, spawns multiple agents, and synthesizes into actionable strategic analysis
中文简介正在准备中。当前显示原文说明。
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中文简介正在准备中。当前显示原文说明。
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中文简介正在准备中。当前显示原文说明。
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中文简介正在准备中。当前显示原文说明。
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中文简介正在准备中。当前显示原文说明。
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中文简介正在准备中。当前显示原文说明。