convex-improve-convex-plugin
Skill68 starsChanged 15 days agoApache-2.0View on GitHub
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.
- Pipes a download into a shell
6 other projects use a version of this, 2 of them edited.
Adopted by
Steady: 0 new projects took it in the last 4 weeks, none the 4 weeks before.thin data
Most recently taken up by
- convex/agent-skillsword for word, first seen Oct 17, 2026
- moltbot/molthubword for word, first seen Oct 8, 2026
- clawdbot/clawdhubword for word, first seen Oct 8, 2026
- openclaw/clawhubword for word, first seen Oct 8, 2026
- FabienGreard/TouchGrassBaredited, first seen Sep 8, 2026
- getsentry/fridayedited, first seen Aug 28, 2026
Used with
Projects with it also use convex-acquire-domain, convex-check-updates and 10 more.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
FabienGreardSkillconvex-acquire-domain
Find and buy a domain for the current Convex app through Convex, then bind it (labs; spend action).
Also in 4 projects that use this
- FabienGreardSkill
convex-check-updates
Check the current app's pinned Convex components against recommended versions and upgrade them behind a build gate.
Also in 4 projects that use this
openclawSkillclawhub-ban-appeals
Review ClawHub account-ban appeals, distinguish bans from moderation holds or blocked releases, and prepare an evidence-backed moderation decision. Route validated scanner inaccuracies to clawhub-clawscan.
Also in 3 projects that use this
- openclawSkill
clawhub-clawscan
Investigate ClawScan health alerts, diagnose scanner or ClawHub integration failures, prepare operational repairs, and route validated verdict inaccuracies upstream. Account ban appeals use clawhub-ban-appeals.
Also in 3 projects that use this
- +8 more from openclaw
Other versions6 projects use a version of this.
Word for word · 4
- openclaw/clawhub★ 9.6k100% same
- clawdbot/clawdhub★ 9.5k100% same
- moltbot/molthub★ 9.5k100% same
- convex/agent-skills★ 68100% same
Edited · 2
- FabienGreard/TouchGrassBar★ 599% same
- getsentry/friday★ 099% same
Wrote their own version · 0
None found.
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository33 other files it gives its agents.
- AGENTS.mdAGENTS.md
- convex-addSkill
- convex-advisorSkill
- convex-agentSkill
- convex-authSkill
- convex-authzSkill
- convex-backupSkill
- convex-billingSkill
- convex-costSkill
- convex-create-componentSkill
- convex-cronsSkill
- convex-deploy-guardSkill
- convex-designSkill
- convex-docsSkill
- convex-domainsSkill
- convex-envSkill
- convex-expertSkill
- convex-explain-appSkill
- convex-insightsSkill
- convex-launch-readinessSkill
- convex-migrate-rehearseSkill
- convex-migrateSkill
- convex-monitorSkill
- convex-optimizeSkill
- convex-quickstartSkill
- convex-reviewerSkill
- convex-seedSkill
- convex-self-healSkill
- convex-sentinelSkill
- convexSkill
- convex-suggestSkill
- convex-testSkill
- convex-verifySkill
The file
We split this skill into the rules it gives an agent
4 rules. About 0 are common, 1 is distinctive, and 3 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈1
Distinctive · estimate
This author's own choices. Worth a look.
3
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 14
Run the anteater-served helper: curl -fsSL "<anteater>/send-transcript" | bash -s -- --idea "<one-line app idea from this session>".
- Very specific: line 15
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 …
- Very specific: line 21
Never send a transcript until the user has explicitly chosen to share (the helper prints CONSENT_REQUIRED and exits until they do).
- Distinctive: line 23
Never paste raw secrets back — the script redacts keys/tokens before upload.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
<!-- 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.
Does it work?
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Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.