analyze-size
Analyze codebase size and language distribution using cloc. Use when user wants to understand codebase scale, primary languages, code composition, or assess project complexity. Provides total LOC, size category, language breakdown percentages, and key insights.
Best use case
analyze-size is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Analyze codebase size and language distribution using cloc. Use when user wants to understand codebase scale, primary languages, code composition, or assess project complexity. Provides total LOC, size category, language breakdown percentages, and key insights.
Teams using analyze-size should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/analyze-size/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How analyze-size Compares
| Feature / Agent | analyze-size | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Analyze codebase size and language distribution using cloc. Use when user wants to understand codebase scale, primary languages, code composition, or assess project complexity. Provides total LOC, size category, language breakdown percentages, and key insights.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Analyze Size **Role:** Analyze codebase size, language distribution, and code metrics using `cloc` (Count Lines of Code). **Goal:** Provide comprehensive understanding of codebase scale, primary languages, and code distribution to help assess project complexity and composition. ## Workflow 1. **Run cloc** with these flags: ```bash cloc . --exclude-dir=node_modules,.git,dist,build,coverage,out,.next,.turbo --quiet 2>/dev/null || echo "cloc not found. Please install: brew install cloc (macOS) or apt-get install cloc (Linux)" ``` 2. **Interpret results** - Identify total lines of code (excluding blank lines and comments) - Determine language distribution (files, code lines per language) - Calculate percentage breakdown of languages - Assess codebase size category 3. **Provide analysis** using this format: ``` ## Codebase Size Analysis **Total Lines of Code:** X,XXX lines **Size Category:** [tiny (<1K) / small (1-10K) / medium (10-50K) / large (50-100K) / very large (>100K)] **Language Distribution:** - Language1: XX.X% (X,XXX lines) - Language2: XX.X% (X,XXX lines) - ... **Key Insights:** - Brief observation about codebase composition - Any notable patterns or characteristics (e.g., high documentation ratio, test coverage indicators) - Suggestions if relevant (e.g., "Primarily a TypeScript/React project") [Include the raw cloc output table for reference] ``` ## Constraints - Focus on source code and meaningful configuration files - Distinguish between source code, configuration, and documentation - Provide context-appropriate insights based on language mix - If cloc not installed, inform user with installation instructions
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