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- Claude Plugins
- Skill Finder
skill-finder_skill
- Python
14
GitHub Stars
5
Bundled Files
2 months ago
Catalog Refreshed
3 months ago
First Indexed
Readme & install
Copy the install command, review bundled files from the catalogue, and read any extended description pulled from the listing source.
Installation
Preview and clipboard use veilstrat where the catalogue uses aiagentskills.
npx veilstrat add skill tenequm/claude-plugins --skill skill-finder- CHANGELOG.md550 B
- package.json337 B
- project.json576 B
- README.md542 B
- SKILL.md14.9 KB
Overview
This skill locates and evaluates Claude skills tailored to a specific task using semantic search, quality assessment, and a fitness score. It reads each skill's manifest and content, applies Anthropic best-practice checks, and ranks candidates by how well they solve your exact request. Results include actionable quality feedback and installation or evaluation pointers.
How this skill works
The skill extracts semantic terms from your query, runs multi-source searches across GitHub and curated lists, and collects candidate repositories. For each candidate it fetches and parses the skill's manifest and content, evaluates against a best-practices checklist, and computes a fitness score combining semantic match, quality, community signals, and freshness. Top candidates are ranked and returned with concise quality breakdowns and recommendations.
When to use it
- When you ask for a skill for a specific task (e.g., "find a skill for pitch decks").
- When you need quality-assessed recommendations rather than popularity lists.
- When choosing between several similar skills and you want concrete tradeoffs.
- When you want suggestions drawn from curated lists or awesome-collections.
- When you need a shortlist of installable, well-documented options.
Best practices
- Use precise user queries with primary and secondary terms to improve semantic matching.
- Ensure the skill manifest includes clear description, examples, and workflows for better evaluation.
- Prefer skills with documented dependencies and testing evidence to improve reliability.
- Check freshness and community signals—recent updates and stars boost confidence.
- Review the provided quality breakdown before installing; combine multiple skills if coverage is partial.
Example use cases
- Find the best Claude skill for creating investor pitch decks, with templates and slide workflows.
- Locate skills that automate data analysis and generate summary reports from CSVs.
- Compare skills that assist with git commit message generation and pick the most robust one.
- Search awesome-lists for curated skill collections and extract candidates that meet your criteria.
- Get a ranked shortlist and a recommended single best match for a narrowly defined task.
FAQ
No. It prioritizes semantic fit and quality for your specific task rather than raw popularity.
How is fitness scored?
Fitness combines semantic match to your query, a quality score from a best-practices checklist, repository stars, and a freshness multiplier.
What if no strong matches are found?
You receive partial matches with explanations and suggestions: broaden terms, check curated lists, or consider composing multiple skills.