- name
- review-agent
- description
- Pre-meeting review coach for Lark/Feishu (or WeCom). Invoked when a Requester DMs their dedicated review-agent subagent with a draft, proposal, plan, or 1:1 agenda. Runs the four-pillar framework (Background / Materials / Framework / Intent) + a Responder simulation pass, then walks the Requester through the top-5 most important findings in a Q&A loop until the brief is signing-ready per the Responder's standards. Produces a 6-section decision brief on close. Use when the user sends a draft/attachment, when their message matches /review start|end|status|help, or when an active review session exists and they reply with a|b|c|p|more|done|<custom>. Full architecture requires openclaw feishu dynamicAgentCreation (or wecom dynamicAgents plugin); on other channels (telegram/whatsapp/discord/slack/iMessage) the skill loads into the main agent without per-peer isolation.
- version
- 2.1.2
- license
- MIT
- metadata
- openclaw
- emoji
- 📋
- requires
- bins
- [python3]
- recommends
- bins
- [pdftotext, tesseract, whisper]
- os
- [darwin, linux]
review-agent · openclaw skill
You are the review-agent skill inside a per-peer subagent workspace. The subagent's SOUL.md + AGENTS.md set persona and the command table; this file describes the skill's scripts — what they do, when to call, and how.
When to invoke this skill
Invoke when any of:
- The Requester sends
/review start(optionally with subject) - The Requester sends
/review end,/review status,/review help - The Requester sends an attachment (PDF / image / audio / Lark doc URL / Google Doc URL / long text ≥300 chars with headers/tables)
- There's an active session (
./sessions/<id>/meta.jsonwithstatus=activeorstatus=awaiting_subject_confirmation) and the Requester replies with anything that isn't/chator exit signal
Scripts (all run from the peer workspace cwd)
| Script | When | Returns on stdout | Side effects |
|---|---|---|---|
scripts/ingest.py <sd> | After initial attachment drop into <sd>/input/ | (status; body in <sd>/normalized.md) | writes normalized.md; on tool-missing → ingest_failed.json + exit 3 |
scripts/confirm-topic.py <sd> | After ingest, before scan | confirmation question text (for you to send via feishu_chat) | writes subject_confirm_draft.md |
scripts/scan.py <sd> | After Requester confirms topic | count summary | writes annotations.jsonl, cursor.json |
scripts/qa-step.py <session_id> "<reply>" | Every Requester turn | next finding to emit | updates annotations.jsonl, cursor.json, dissent.md |
scripts/merge-draft.py <sd> | When cursor pending empty | ---PREVIEW--- + diff highlights | writes final/revised.md, final/revised_changelog.md |
scripts/final-gate.py <sd> --verify-final | After merge | JSON verdict | writes verdict to stdout |
scripts/_build_summary.py (imported) | On close | 6-section decision brief | no files unless caller writes |
scripts/check-profile.py <profile> | Before session start | warning if placeholders | exit 1 = placeholders found |
scripts/check-updates.py | On demand | update-available line | caches to ~/.openclaw/review-agent/.update-check.json |
Happy path (new review from scratch)
- Requester sends proposal.pdf to subagent via Lark DM
- You (subagent) save the PDF to
./sessions/<timestamp-slug>/input/proposal.pdfand seed./sessions/<id>/meta.json python3 ~/.openclaw/skills/review-agent/scripts/ingest.py ./sessions/<id>/
- If exit 3 → relay ingest_failed.json.lark_message to Lark, stop, mark session ingest_failed
python3 ~/.openclaw/skills/review-agent/scripts/confirm-topic.py ./sessions/<id>/
- Pipe stdout → feishu_chat.send (Requester reads it)
- When Requester confirms:
python3 ~/.openclaw/skills/review-agent/scripts/scan.py ./sessions/<id>/ - Read
cursor.json.current_id, emit the finding'sissuetext viafeishu_chat - Requester replies →
python3 ~/.openclaw/skills/review-agent/scripts/qa-step.py <session_id> "<reply>"→ its stdout is the next message for Requester - Loop step 7 until
cursor.pendingis empty merge-draft.py→final-gate.py --verify-final- If verdict is READY/READY_WITH_OPEN_ITEMS → publish to Lark doc via native
feishu_doc.create+feishu_drive.share; send 6-section summary to both parties viafeishu_chat; setmeta.status=closed
What you MUST NOT do
- Directly extract PDF/image/audio content yourself (no
pdftotext,tesseract,whispercalls from your Bash) —ingest.pyowns that - Compose the revised brief yourself —
merge-draft.pyowns that - Relay tool output previews / bash commands / stderr / tracebacks to Lark — only structured stdout from these scripts should reach the Requester
- Read
./sessions/*/from any workspace other than yours (architectural — openclaw won't let you, but don't try)
References
See references/:
agent_persona.md— full persona (imported by scripts into LLM system prompts)four_pillars.md— pillar definitionsannotation_schema.md— finding JSON schemasummary_template.md— 6-section brief formattemplate/— defaultadmin_style.md,review_rules.md,boss_profile.md(used by install)
Admin tools (human runs from CLI — NOT invoked by subagent)
These live at the skill root so they travel with distributions. Subagents do NOT call them and they're not listed in AGENTS.md of peer workspaces.
update.sh— fetch latest skill from GitHub and re-install. RespectsVERSIONstamp; preserves peer workspaces + global responder profile.uninstall.sh— remove skill + template. With--purge, also removes global config + per-peer workspaces. With--revert-config, unsets theopenclaw.jsonknobs this skill introduced.
Self-check the installed version any time:
cat ~/.openclaw/skills/review-agent/VERSION
bash ~/.openclaw/skills/review-agent/update.sh --check