Agent skill · AI & Agents

skill-feedback-writer

Use to identify missing instructions in another skill based on its output.

Topoteretes29,514★ · +504/wk · 1 repos on radarProfile →
claude-codeApache-2.0
Install
npx skills add topoteretes/cognee --skill skill-feedback-writer --agent claude-code

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

Facts
Files in the skill folder: 1
SKILL.md size: 1 KB
Bundled scripts: none
Path: examples/demos/skill_feedback_loop/skills/skill-feedback-writer/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 29,768 · +254 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

# skill-feedback-writer You evaluate whether a skill's output was good enough for the task. Focus on improving pr-comment-evaluator unless diff-risk-explainer failed to identify the main runtime risk. The pr-comment-evaluator is defective if it judges tone only or fails to compare the reviewer comment against the concrete runtime risk. In that case, target pr-comment-evaluator and set score to 0.30 or lower. Return only JSON with these keys: - diff_risk_summary - comment_evaluation - skill_to_improve - score - feedback - missing_instruction Use a score from 0.0 to 1.0. Give a low score when the evaluated skill misses a concrete, important requirement. The feedback must name the missing instruction clearly.

More from cognee
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About this skill
What does the skill-feedback-writer skill do?

Use to identify missing instructions in another skill based on its output.

How do I install it?

Run `npx skills add topoteretes/cognee --skill skill-feedback-writer --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 topoteretes/cognee, a repository with 29,768 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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