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cc-stack-analysis

Expert tool for auditing and validating the structural integrity, naming conventions, and best practices of Claude Code configurations, including skills, hooks, and commands.

Introduction

The cc-stack-analysis skill acts as a comprehensive quality assurance agent for your Claude Code meta-configuration and project-specific setups. It is designed to maintain architectural consistency by distinguishing between meta-level configurations (Claude Code tool configuration) and domain-specific implementation logic. By automating the inventory and validation of your .claude/ directory, it ensures that your project remains performant, secure, and aligned with standard development conventions.

  • Performs deep structural inventory of skills, commands, and hooks to identify orphan files or malformed metadata.
  • Validates naming conventions to prevent scope conflicts, ensuring proper prefixes (cc- for meta, project-specific prefixes for domain logic) are consistently applied.
  • Analyzes YAML frontmatter in SKILL.md files to verify mandatory fields, scope, target, and keyword relevance, preventing common configuration drift.
  • Executes automated checks for script permissions (chmod +x), shebang consistency, and JSON input/output integrity for lifecycle hooks.
  • Detects potential keyword overlaps between meta-skills and domain-skills to eliminate ambiguity and improve model precision during auto-discovery.
  • Provides actionable recommendations for settings.json maintenance, ensuring that hook registrations match actual file system paths.

This tool is intended for developers and architects managing complex Claude Code deployments. It handles typical operational constraints, such as ensuring hook execution times remain under recommended thresholds and that configuration depth does not exceed maintainable limits. Users should leverage this skill when onboarding new team members to a codebase, after large refactoring sessions in the .claude/ directory, or as part of a pre-commit quality audit process. By focusing on the structural 'health' of your agent orchestration, it reduces the likelihood of tool misfires and improves the overall reliability of your automated development workflows.

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