SKILL.md Readiness Auditor

The problem

Publishing an AI skill that fails to trigger, requests excessive permissions, or lacks a clear workflow leads to rejection and poor user experiences. Developers often struggle to identify structural gaps or safety risks in their SKILL.md files before submission.

What it does

• Validates YAML frontmatter syntax and required metadata fields for Agensi and compatible marketplaces.
• Analyzes trigger precision to ensure the skill activates on the correct requests and ignores out-of-scope tasks.
• Audits permission requests against the principle of least privilege to flag unjustified tool access.
• Identifies security risks like potential prompt injection, credential leaks, and unsafe execution of untrusted code.
• Provides a structured readiness report with a numerical score and specific corrective actions for publication blockers.

Frameworks & tools

SKILL.md, Agensi, Cursor, Claude Code, and Codex CLI.

Why this beats prompting it yourself

Standard LLM prompts often overlook subtle packaging requirements like folder naming alignment or YAML delimiter errors. This skill uses a codified readiness rubric and security checklist to catch technical blockers that manual reviews miss.

Use cases

• Reviewing a SKILL.md file for structural validity and marketplace compliance.
• Auditing a full skill folder to ensure listing promises match the actual code.
• Identifying excessive tool permissions that could lead to user rejection.
• Testing trigger boundaries to prevent a skill from being too broad or generic.

Known limitations

Does not execute scripts or certify legal compliance. Limited to analyzing visible file content and instructions without external URL access.