Agent skill

perf-theory-gatherer

Use when generating performance hypotheses backed by git history and code evidence.

Composio HQ21,770★ · 3 repos on radarProfile →
claude-code
Install
npx skills add composio-community/awesome-claude-plugins --skill theory --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
Version: 1.0.0
Path: perf/skills/theory/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 1,858
Language: JavaScript
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

# perf-theory-gatherer Generate performance hypotheses for a specific scenario. Follow `docs/perf-requirements.md` as the canonical contract. ## Required Steps 1. Review recent git history (scope to relevant paths when possible). 2. Identify code paths involved in the scenario (repo-map or grep). 3. Produce up to 5 hypotheses with evidence + confidence. ## Output Format ``` hypotheses: - id: H1 hypothesis: <short description> evidence: <file/path or git change> confidence: low|medium|high - id: H2 ... ``` ## Constraints - MUST check git history before hypothesizing. - No optimization suggestions; only hypotheses. - Keep to 5 hypotheses maximum.

What's inside
Steps it walks through
  1. Required Steps
  2. Output Format
  3. Constraints
More from awesome-claude-plugins
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About this skill
What does the perf-theory-gatherer skill do?

Use when generating performance hypotheses backed by git history and code evidence.

How do I install it?

Run `npx skills add composio-community/awesome-claude-plugins --skill theory --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 composio-community/awesome-claude-plugins, a repository with 1,858 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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