SECURITY REVIEW
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Agent Development · Communication / AGENT SKILL
convex-improve-convex-plugin
0
Share a coding session transcript with the Convex team for quickstart improvement analysis.
Send this coding session's transcript to the Convex team for an AI post-mortem that improves the quickstart system.
Understand the trade-offs.
SKILL QUALITY
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How clearly the skill guides your agent, how complete its workflow is, and how you can check the outcome.
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The full skill.
Original instructions from the publisher’s SKILL.md
<!-- 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 1. Run the anteater-served helper: `curl -fsSL "<anteater>/send-transcript" | bash -s -- --idea "<one-line app idea from this session>"`. 2. 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. 3. Watch for output markers: REVIEW_SOURCE (transcript found), REVIEW_SUBMITTED id=... (accepted), REVIEW_DONE status=done (findings ready). 4. 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.