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Convex Improve Convex Plugin

ConvexOfficialPublished by Convex

  • Skill
  • Workflow
  • Software development
  • Apache-2.0
  • Medium risk
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From the author

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.
— the description by Convex

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

This skill facilitates a feedback loop for the Convex quickstart system by sending session transcripts to an AI-driven review endpoint. It is designed to identify patterns of agent failure, ambiguous instructions, and tooling issues to improve future development experiences. The process is strictly opt-in, requiring explicit user consent before any data is transmitted, and includes automated redaction of sensitive information.

What it does

  • Triggers a transcript submission process for AI-based post-mortem analysis.
  • Handles user consent requirements for data sharing.
  • Identifies system-level issues such as agent-stuck patterns and tooling failures.
  • Summarizes high-severity findings including suggested fixes and system wins.
  • Redacts secrets and tokens from transcripts before transmission.

When to use it

  • When you want to contribute to the improvement of the Convex quickstart system.
  • After completing a coding session where you encountered agent-related friction or tooling issues.
  • When you wish to provide structured feedback on the effectiveness of the current development workflow.

Advantages

  • Directly contributes to the refinement of agent workflows and system documentation.
  • Ensures privacy through mandatory opt-in consent and automated secret redaction.
  • Provides actionable insights based on real-world coding session data.
  • Focuses on system-level improvements rather than end-user data.

Usage examples

“Can you send this session's transcript to the Convex team for a post-mortem?”
The agent initiates the transcript submission process, checks for consent, and provides a summary of the system findings once the review is complete.

Install

  1. Download the skill as a ZIP:

    https://mp-staging.autogineer.com/agent-skills/convex/convex-improve-convex-plugin/download

  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip convex-improve-convex-plugin.zip -d .agents/skills

Documentation by Convex

<!-- 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.

Files

Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Security

What our scanner noticed· Medium risk

  • Downloads piped into a shell

A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.

Attribution and licence

Published by
Convex
Publisher
Convex (Official)
Source
convex/agent-skills · skills/convex-improve-convex-plugin · commit f60629d
Licence
Apache License 2.0 (redistribution allowed)
  • LICENSE (added by AutoGineer from LICENSE)
  • ATTRIBUTION.md (written by AutoGineer)
Synced

AutoGineer is not affiliated with or endorsed by Convex.

Download ZIP

The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download convex-improve-convex-plugin.zip