convex-improve-convex-plugin
Send this coding session's transcript to the Convex team for an AI post-mortem that improves the quickstart system. Run only when the user explicitly asks.
- License 许可
- MIT
- 所属仓库
- openclaw/clawhub
- 最近更新
- 2026-11-13
- Stars
- ★ 9.6k
- Forks
- 1.5k
01 前言 Front Matter
- name
- convex-improve-convex-plugin
- description
- Send this coding session's transcript to the Convex team for an AI post-mortem that improves the quickstart system. Run only when the user explicitly asks.
03 SKILL.md 正文
<!-- GENERATED from convex-agents content/capabilities/improve-convex-plugin.json — do not edit by hand. -->
improve-convex-plugin
Sends the current coding session transcript to the anteater POST /review endpoint for an AI post-mortem. The review returns structured findings (ambiguous instructions, agent-stuck patterns, tooling failures, wins) targeted at the runbook, bootstrap script, skills, and components — not end-user data. Sharing is opt-in: the anteater-served helper asks once (Always / Just this once / Never) and remembers the choice.
Workflow
- Run the anteater-served helper:
curl -fsSL "<anteater>/send-transcript" | bash -s -- --idea "<one-line app idea from this session>". - If it prints CONSENT_REQUIRED (exit 4), the user has not chosen yet — ask them to share Always, Just this once, or Never, then re-run appending --consent always|once|never. Do not send until they answer.
- Watch for output markers: REVIEW_SOURCE (transcript found), REVIEW_SUBMITTED id=... (accepted), REVIEW_DONE status=done (findings ready).
- Summarize the highest-severity findings for the user: title → target → suggestedFix, then wins. Keep the summary about the system, not the user's data.
Rules
- Never send a transcript until the user has explicitly chosen to share (the helper prints CONSENT_REQUIRED and exits until they do).
- REVIEW_NO_TRANSCRIPT means no Claude/Codex .jsonl was found — tell the user.
- Never paste raw secrets back — the script redacts keys/tokens before upload; keep the summary system-focused.
- This is a system-improvement loop, not end-user feature feedback.
04 同仓库更多 Skills
convex-advisor
Read the Convex deployment's 72h insights (read limits, OCC contention), root-cause each event in code, report evidence-backed perf/cost findings with fixes.
convex-add
Add a capability to the CURRENT Convex app — consults the served Convex capability catalog for always-current procedures (billing, crons, auth, agent, search, …); falls back to built-in hosting or @convex-dev component search. TRIGGER when the user runs /add, or asks to add hosting/publishing or any backend capability to an existing Convex app.
convex-acquire-domain
Find and buy a domain for the current Convex app through Convex, then bind it (labs; spend action).
controlling-costs
Analyzes Axiom query patterns to find unused data, then builds dashboards and monitors for cost optimization. Use when asked to reduce Axiom costs, find unused columns or field values, identify data waste, or track ingest spend.
clawhub-production-release
Run and verify ClawHub production deploys and stable ClawHub CLI npm releases. Use when deploying backend or frontend changes to clawhub.ai, dispatching the Deploy workflow, publishing a stable CLI tag, checking release prerequisites, or proving the exact production SHA and workflow outcome.
clawhub-pr-maintainer
Use when reviewing, triaging, validating, or discussing ClawHub GitHub issues or pull requests, including author context, CI, UI proof, evidence, labels, close decisions, and maintainer handoff.