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Found 28 Skills
Scans .NET code for ~50 performance anti-patterns across async, memory, strings, collections, LINQ, regex, serialization, and I/O with tiered severity classification. Use when analyzing .NET code for optimization opportunities, reviewing hot paths, or auditing allocation-heavy patterns.
Reviews and validates agent skills against best practices. Triggers on "review this skill", "check my skill", "validate skill", "is this skill well-written", or when creating/editing skills.
Learns from DAG execution history to improve future performance. Identifies successful patterns, detects anti-patterns, and provides recommendations. Activate on 'learn patterns', 'execution patterns', 'what worked', 'optimize based on history', 'pattern analysis'. NOT for failure analysis (use dag-failure-analyzer) or performance profiling (use dag-performance-profiler).
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.
This skill should be used when the user asks to "roast my code", "review code brutally", "find code sins", "what's wrong with my code", "shame my code", "critique this code", "find antipatterns", "code quality roast", or wants entertaining but actionable code criticism with severity-ranked fixes. Delivers brutally honest roasts with file:line citations and redemption paths.
This skill should be used when recognizing recurring themes, identifying patterns in work or data, or when "pattern", "recurring", or "repeated" are mentioned. For implementation, see codify skill.
Evaluates agent skills against Anthropic's best practices. Use when asked to review, evaluate, assess, or audit a skill for quality. Analyzes SKILL.md structure, naming conventions, description quality, content organization, and identifies anti-patterns. Produces actionable improvement recommendations.
This skill should be used when the user asks to "rewrite my resume", "fix my resume", "humanize my resume", "make my resume sound human", "clean up my resume bullets", "reword my resume", or wants AI-sounding text in their resume rewritten with annotations explaining each change. Works for all resume and CV types: standard US, federal, academic, legal, medical, consulting, tech, executive, military transition, education, nonprofit, trades, creative, investment banking, and EU/Europass formats. Entry-level through executive.
Evaluates agent skills against Anthropic's best practices. Use when asked to review, evaluate, assess, or audit a skill for quality. Analyzes SKILL.md structure, naming conventions, description quality, content organization, and identifies anti-patterns. Produces actionable improvement recommendations.
Analyze codebases for anti-patterns, code smells, and quality issues using ast-grep structural pattern matching. Use when reviewing code quality, identifying technical debt, or performing comprehensive code analysis across JavaScript, TypeScript, Python, Vue, React, or other supported languages.
Perform systematic self-review of code changes before commits using structured checklist. Validates architecture boundaries, code quality, test coverage, documentation, and project-specific anti-patterns. Use before committing, creating PRs, or when user says "review my changes", "self-review", "check my code". Adapts to Python, JavaScript, TypeScript, Go, Rust projects.
Find similar or analogous code patterns elsewhere in a codebase. Use when answering "Do we do something similar elsewhere?" or "What existing patterns match this?" Returns factual findings about similar code - locations, similarity type, and confidence.