Deep strategic research engine — decomposes questions into parallel research threads, spawns multiple agents, and synthesizes into actionable strategic analysis
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CP-7 retrospective: audit checkpoints, evidence quality, action items, and harvest candidates. Closes the V-model cycle and feeds the next run. Use via /retro after ship, escalate, or significant session.
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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。
Every non-tiny shipped or escalated run gets a retro. Retro is advisory but strongly expected: it is how the harness improves.
/ultragoal phase (one retro per phase)/retro <run-dir or spec path>Read:
04-projects/harness/runs/<id>/evidence/ (ledger, checkpoints.tsv, CP-* files).claude/logs/loop-ledger.tsv (last rows for this run)04-projects/<goal>/STATUS.md if an ultragoal phaseFor each CP the lane required, mark Expected vs Actual vs Gap:
| CP | tiny | normal | full |
|---|---|---|---|
| CP-1 spec | skip | required | required |
| CP-3v component | skip | required | required |
| CP-4 integration | skip | skip | required if multi-task |
| CP-5 acceptance | if mutate | required | required |
| CP-6 ship | if external | if external | required |
Ask:
Copy references/retro-template.md to:
04-projects/harness/retro/YYYY-MM-DD-<slug>.md
Fill all sections. Action items get IDs (AI-01…).
AI-n rows to 04-projects/harness/BACKLOG.md if harness workAC-n## Checkpoint log CP-7 rowbash .claude/lib/checkpoint.sh record <run-dir> CP-7 PASS "retro: <path>"TL;DR: outcome, top lesson, top action item, retro path.
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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。
Quick capture of raw thoughts with intelligent domain classification and competitive intelligence extraction
中文简介正在准备中。当前显示原文说明。
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.
中文简介正在准备中。当前显示原文说明。
Deep-dive 7-day analysis across all data sources for weekly reviews, board prep, and strategic planning
中文简介正在准备中。当前显示原文说明。
Autonomous content pipeline - scout announcements in your field, triage by trend momentum and personal angle, produce posts/blogs/videos in your voice with ledger-based dedup, hard volume caps, and screenshot-verified publishing
中文简介正在准备中。当前显示原文说明。
Create user stories with duplicate checking across any project tracker (Linear, GitHub Issues, Jira)
中文简介正在准备中。当前显示原文说明。