How does the recommendation system work?

The recommender performs a gap analysis by comparing your current skill library against a taxonomy of 20 categories, identifying missing capabilities and generating ready-to-use templates for new skills.

What dimensions does Skill Sentinel audit?

It analyzes seven key areas: Code Quality (complexity and documentation), Security (secrets and injections), Performance (timeouts and retries), Governance (logging and rate limits), Documentation (triggers and structure), Dependencies (pinned versions), and Cross-Skill patterns (duplication).

Can Skill Sentinel help reduce AI costs?

Yes, it includes a cost optimizer that analyzes token usage in SKILL.md files, script verbosity, and the absence of structured JSON outputs to minimize operational overhead.

Is it compatible with tools other than Claude Code?

Yes, Skill Sentinel is designed to work across various platforms including Claude Code, Cursor, Gemini CLI, Codex CLI, and the Antigravity framework.

Skill Sentinel

Name: Skill Sentinel
Author: sickn33

bysickn33

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31,721

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Analytics & Monitoring

Audits and evolves AI skill ecosystems by analyzing code quality, security, performance, and governance across seven critical dimensions.

Skill Sentinel acts as a meta-agent designed to maintain the health and efficiency of your AI skill collection. It automatically scans for duplicate capabilities, identifies security vulnerabilities like hardcoded secrets, optimizes token costs, and evaluates code quality. By providing detailed health reports and comprehensive gap analysis, it helps developers ensure their agentic tools remain secure, performant, and well-documented while suggesting new specialist skills to fill functional gaps in the ecosystem.

Key Features

01Gap analysis with automated recommendations for new skills

02Detailed executive reporting with severity-based findings and action plans

03Automated cost optimization for token usage and script verbosity

04Multi-dimensional health audits covering security, quality, and performance

05Cross-skill analysis to detect duplication and shared patterns

0631,721 GitHub stars

Use Cases

01Performing a full security and quality audit on a local library of AI skills

02Optimizing API costs and token consumption across multiple agentic workflows

03Identifying missing capabilities in an automation ecosystem to prioritize development

Key Features

01Gap analysis with automated recommendations for new skills

02Detailed executive reporting with severity-based findings and action plans

03Automated cost optimization for token usage and script verbosity

04Multi-dimensional health audits covering security, quality, and performance

05Cross-skill analysis to detect duplication and shared patterns

0631,721 GitHub stars

Use Cases

01Performing a full security and quality audit on a local library of AI skills

02Optimizing API costs and token consumption across multiple agentic workflows

03Identifying missing capabilities in an automation ecosystem to prioritize development