Recognize and capture reusable patterns, workflows, and domain knowledge from work sessions into new skills. Use when completing tasks that involve novel approaches repeated 2+ times, synthesizing complex domain knowledge across conversations, discovering effective reasoning patterns, or developing workflow optimizations. Optimizes for high context window ROI by identifying patterns that will save 500+ tokens per reuse across 10+ future uses.
Active diagnostic tool for analyzing skill prompts to identify token waste, anti-patterns, trigger issues, and optimization opportunities. Use when reviewing skill prompts, debugging why skills aren't triggering, optimizing token usage, or preparing skills for publication. Provides specific, actionable suggestions with examples.
Debug, diagnose, and troubleshoot skill issues including trigger failures, parameter problems, prompt conflicts, and SKILL.md structural issues. Use when skills don't activate as expected, trigger incorrectly, produce unexpected behavior, conflict with system instructions, or fail packaging validation. Analyzes YAML frontmatter, descriptions, progressive disclosure, token budget, absolute statements, and reference file organization. For skill creators reviewing, validating, or fixing skill problems.
Analyzes skill ecosystem to visualize dependencies, identify workflow bottlenecks, and recommend optimal skill stacks. Use when asked about skill combinations, workflow optimization, bottleneck identification, or which skills work together. Triggers include phrases like "which skills work together", "skill dependencies", "workflow bottlenecks", "optimal skill stack", or "recommend skills for".
Auto-generates standardized README documentation from SKILL.md files, validates consistency (frontmatter, descriptions, terminology), and creates usage examples. Use when documenting individual skills, generating docs for multiple skills in a directory, or validating skill quality standards.
Analyzes the user's skill library to identify coverage gaps, redundant overlaps, and optimization opportunities. Use when users want to understand their skill ecosystem, optimize their skill collection, find missing capabilities for common workflows, or reduce redundant coverage. Triggered by requests like "analyze my skills," "what skills am I missing," "are any of my skills redundant," or "optimize my skill library."
Analyzes skill usage patterns across conversations to track token consumption, identify heavy vs. lightweight skills, measure invocation frequency, detect co-occurrence patterns, and suggest consolidation opportunities. Use when the user asks to analyze skill performance, optimize skill usage, identify token-heavy skills, find consolidation opportunities, or review skill metrics.
Comprehensive security risk analysis for Claude skills. Use when asked to analyze security risks, review security stance, audit skills for vulnerabilities, check security before deployment, or evaluate safety of skill files. Triggers include "analyze security," "security risks," "security audit," "security review," "is this skill safe," or "check for vulnerabilities."