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munlucky AI Skills

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Browse published AI skills maintained by munlucky. Compare skill descriptions and follow each source repository for setup instructions.

Author statistics

Indexed skills

42

Repository stars across indexed skills

0

Repository forks

0

Average repository stars per indexed skill

0

Repository stars may repeat across skills from the same repository.

42 skills

Browse skills

GitHub

codex-review-code

munlucky

Review implementation quality and regression risks via claude-delegator (Code Reviewer expert). Use after implementation for complex tasks, refactors, or API changes.

GitHub

security-reviewer

munlucky

Reviews code for security vulnerabilities. Use when security concerns are detected or before deploying critical changes.

GitHub

moonshot-detect-uncertainty

munlucky

Detects missing requirements and generates clarification questions. Use after classification/complexity to decide if user input is needed.

GitHub

codex-validate-plan

munlucky

Validate architecture/plan quality via claude-delegator (Plan Reviewer expert). Use after writing context.md for complex feature/refactor work.

GitHub

moonshot-classify-task

munlucky

Classifies a user request into task types (feature, modification, bugfix, refactor) and extracts intent keywords. Use at the start of PM analysis.

GitHub

moonshot-decide-sequence

munlucky

Determines phase and execution chain based on analysisContext (task type, complexity, signals). Use after uncertainty detection.

GitHub

project-md-refresh

munlucky

Analyze the current repository and create or refresh .claude/PROJECT.md to match the project. Use when PROJECT.md is missing, stale, or the user asks to generate/update project-specific rules, structure, comman...

GitHub

implementation-runner

munlucky

Performs implementation in the chain and records completion state and changed files in analysisContext. Use during implementation.

GitHub

security-reviewer

munlucky

Reviews code for security vulnerabilities. Use when security concerns are detected or before deploying critical changes.

The default order uses GitHub repository stars from our indexed data. Stars belong to the source repository and may be shared by multiple skills. They indicate repository interest, not skill installs or an independent quality score.