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athola/claude-night-market121 installs

file-analysis

Maps file structure and module organization of a codebase. Use before architecture reviews, refactoring planning, or migration scope estimation.

How do I install this agent skill?

npx skills add https://github.com/athola/claude-night-market --skill file-analysis
view source ↗

Is this agent skill safe to install?

  • Gen Agent Trust Hubpass

    The skill performs codebase structural analysis using standard shell utilities. While generally safe, it is vulnerable to command injection in Step 3, where workspace filenames are passed directly to the shell via command substitution without sanitization.

  • Socketpass

    No alerts

  • Snykpass

    Risk: LOW · No issues

  • Runlayerpass

    1 file scanned · No issues

What does this agent skill do?

File Analysis

When To Use

  • Before architecture reviews to understand module boundaries and file organization.
  • When exploring unfamiliar codebases to map structure before making changes.
  • As input to scope estimation for refactoring or migration work.

When NOT To Use

  • General code exploration - use the Explore agent
  • Searching for specific patterns - use Grep directly

Required TodoWrite Items

  1. file-analysis:root-identified
  2. file-analysis:structure-mapped
  3. file-analysis:patterns-detected
  4. file-analysis:hotspots-noted

Mark each item as complete as you finish the corresponding step.

Step 1: Identify Root (file-analysis:root-identified)

  • Confirm the analysis root directory with pwd.
  • Note any monorepo boundaries, workspace roots, or subproject paths.
  • Capture the project type (language, framework) from manifest files (package.json, Cargo.toml, pyproject.toml, etc.).

Step 2: Map Structure (file-analysis:structure-mapped)

  • Run tree -L 2 -d or find . -type d -maxdepth 2 to capture the top-level directory layout.
  • Identify standard directories: src/, lib/, tests/, docs/, scripts/, configs/.
  • Note any non-standard organization patterns that may affect downstream analysis.

Step 3: Detect Patterns (file-analysis:patterns-detected)

  • Use find . -name "*.ext" -not -path "*/.venv/*" -not -path "*/__pycache__/*" -not -path "*/node_modules/*" -not -path "*/.git/*" | wc -l to count files by extension.
  • Identify dominant languages and their file distributions.
  • Note configuration files, generated files, and vendored dependencies.
  • Run wc -l $(find . -not -path "*/.venv/*" -not -path "*/__pycache__/*" -not -path "*/node_modules/*" -not -path "*/.git/*" -name "*.py" -o -name "*.rs" | head -20) to sample file sizes.

Step 4: Note Hotspots (file-analysis:hotspots-noted)

  • Identify large files (potential "god objects"): find . -type f -exec wc -l {} + | sort -rn | head -10.
  • Flag deeply nested directories that may indicate complexity.
  • Note files with unusual naming conventions or placement.

Exit Criteria

  • TodoWrite items are completed with concrete observations.
  • Downstream workflows (architecture review, refactoring) have structural context.
  • File counts, directory layout, and hotspots are documented for reference.

Add the canonical catalog link to the repository README so users can inspect current installs and available audits. The publishing guide covers the complete discovery path.

<a href="https://skillzs.dev/skills/athola/claude-night-market/file-analysis">View file-analysis on skillZs</a>