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- Richtabor
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- Skill Review
skill-review_skill
- Shell
49
GitHub Stars
2
Bundled Files
2 months ago
Catalog Refreshed
4 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 richtabor/agent-skills --skill skill-review- README.md2.1 KB
- SKILL.md5.3 KB
Overview
This skill reviews and validates agent skills against a compiled set of best practices and standards. It inspects structure, frontmatter metadata, description quality, progressive disclosure, and common anti-patterns. The goal is actionable feedback and a short remediation plan to make skills reliable and triggerable.
How this skill works
The skill loads the standard references and a checklist, then identifies the review target (single skill file, all skills in a directory, or a draft). It runs a structural audit, validates frontmatter metadata, evaluates description trigger quality and token efficiency, scans for anti-patterns, and produces a concise report with prioritized recommendations. A quick-review mode can run only the checklist and return failures.
When to use it
- When you ask “review this skill”, “check my skill”, or “validate skill”
- When creating a new skill draft and you want feedback before publishing
- When you suspect poor trigger reliability or vague descriptions
- When you need a fast checklist-based audit across many skills
- When you want assurance that scripts, references, and paths are consistent
Best practices
- Keep the primary skill document short and put long details in referenced files
- Make the description third-person, include what it does and explicit trigger phrases
- Use forward-slash paths and document external binaries or dependencies
- Provide defaults for multi-option tasks and reduce degrees of freedom for fragile operations
- Prefer examples over long prose and keep each line justifying its token cost
Example use cases
- Validate a newly drafted skill file before adding it to the catalog
- Audit an entire skills directory for naming, path, and reference depth issues
- Quick-check a skill when a model fails to trigger it reliably
- Get a prioritized remediation list for a skill flagged as verbose or ambiguous
- Confirm that script paths referenced in the skill exist and are portable
FAQ
A single-skill structured review takes a few minutes; an audit of many skills scales with count but the quick-review checklist returns results in seconds.
What output format should I expect?
You get a compact report with a one-line summary, pass/fail checks for structure and metadata, a description quality score, listed anti-patterns, and 2–5 prioritized recommendations.