Skill UI

Skill Sentinel audits and evolves a skills ecosystem by analyzing quality, security, cost, governance, documentation, dependencies, and cross-skill duplication, then generates health reports, recommendations, and orchestrates assessments for teams managing multiple automations.

This comprehensive index covers 37 advanced engineering skills designed for complex system architecture, platform operations, and reliability. Skills include agent design, RAG implementation, CI/CD, observability, database modeling, and security auditing, supporting the entire development lifecycle for powerful enterprise applications.

This comprehensive index provides access to 32 production-ready, specialized engineering skills. It covers the entire development lifecycle, including system architecture, frontend, backend, DevOps, security operations, AI/ML, and data engineering. It is designed to guide users in selecting and loading only the specific module needed, ensuring focused expertise for complex tasks.

Validates SKILL.md files against the agentskills specification and Anthropic best practices, catching structure, semantic, naming, and quality issues in a single read-only pass before publishing or debugging skills.

Scan installed skills, extract shared cross-domain principles, and distill them into reusable rules. Supports appending, revising, or creating rule files during regular maintenance or after skill inventory updates.

This skill systematically audits a given project by analyzing its historical memory, rollout summaries, and local skill definitions. It identifies repeated complex workflows, recurring operational patterns, or areas where existing skills are stale. The audit process guides the user to recommend the highest-value skills to either add (if a new pattern emerges) or update (if current skills are outdated or incomplete), ensuring the AI agent operates with the most accurate and context-specific knowledge base for optimal project execution.

This skill provides a comprehensive, read-only audit of a development workspace, including active repositories, installed plugins, connected services, and environment configurations. It analyzes existing capabilities against best practices to identify functional gaps and recommends the most valuable ECC-native skills, hooks, and workflows needed to enhance the development experience. Ideal for setup planning and architectural reviews.

Generates a precise, evidence-based installation plan for a project's component catalog (ECC). Instead of loading a full, noisy bundle, this skill analyzes the repository's actual code structure, dependencies, and CI/CD evidence to classify skills, rules, and commands into 'DAILY' (essential) and 'LIBRARY' (referenceable) buckets. It ensures only necessary components are active, optimizing the development environment.

Helps users discover and install open agent skills by translating requests like “how do I do X” into CLI searches, reviewing sources, and guiding safe installs with security warnings and confirmations.

Explores Feishu/Lark native OpenAPI docs when existing lark-* skills or CLI commands lack coverage, fetching markdown indexes stepwise to surface raw API specs and ready-to-run `lark-cli api` invocations.

Guides developers to wrap Feishu API calls into reusable lark-cli skills, covering API research, command templates, and best practices for authentication, permissions, and orchestration.

Guides agents through researching Microsoft technologies via Learn MCP docs, then scaffolds hybrid skills that store essential knowledge locally while enabling dynamic lookups for depth.