Agent skill · Code Review & Quality

gepetto

Creates detailed, sectionized implementation plans through research, stakeholder interviews, and multi-LLM review. Use when planning features that need thorough pre-implementation analysis.

Softaworks2,247★ · +27/wk · 1 repos on radarProfile →
claude-codeMIT
Install
npx skills add softaworks/agent-toolkit --skill gepetto --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 7
SKILL.md size: 10 KB
Bundled scripts: none
Path: skills/gepetto/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 2,276 · +29 this week
Language: Python
Read our review of the source →

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Gepetto Orchestrates a multi-step planning process: Research → Interview → Spec Synthesis → Plan → External Review → Sections ## CRITICAL: First Actions **BEFORE anything else**, do these in order: ### 1. Print Intro Print intro banner immediately: ``` ═══════════════════════════════════════════════════════════════ GEPETTO: AI-Assisted Implementation Planning ════════════════════════════════════

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About this skill
What does the gepetto skill do?

Creates detailed, sectionized implementation plans through research, stakeholder interviews, and multi-LLM review. Use when planning features that need thorough pre-implementation analysis.

How do I install it?

Run `npx skills add softaworks/agent-toolkit --skill gepetto --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From softaworks/agent-toolkit, a repository with 2,276 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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