Agent skill · AI & Agents

skill-evolve

Optional sidecar skill for controlled feedback-driven skill evolution. Not part of the default pipeline. Only activates when explicitly requested.

Yiming Zhao438★ · 1 repos on radarProfile →
cursorships scriptsMIT
Install
npx skills add gaotiexinqu/OneResearchClaw --skill skill-evolve --agent cursor

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

Facts
Files in the skill folder: 13
SKILL.md size: 12 KB
Bundled scripts: yes
Path: .cursor/skills/skill-evolve/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 438
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

# Skill Evolve (Optional Sidecar) **This is an OPTIONAL sidecar capability, NOT part of the default pipeline.** --- ## What This Skill Is Skill Evolve is a **controlled, opt-in framework** for turning real user feedback into skill improvements over time. It is designed to: - Collect and normalize user feedback - Generate minimal patch proposals - Require manual review/refinement of generated patch

More from OneResearchClaw
All skills →
About this skill
What does the skill-evolve skill do?

Optional sidecar skill for controlled feedback-driven skill evolution. Not part of the default pipeline. Only activates when explicitly requested.

How do I install it?

Run `npx skills add gaotiexinqu/OneResearchClaw --skill skill-evolve --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 gaotiexinqu/OneResearchClaw, a repository with 438 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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