Skill: athola/nm-sanctum-file-analysis (version 1.0.2)

--- name: file-analysis description: | Map file structure and organization for downstream review and refactoring workflows version: 1.9.5 triggers: - files - structure - analysis - codebase - exploration metadata: {"openclaw": {"homepage": "https://github.com/athola/claude-night-market/tree/master/plugins/sanctum", "emoji": "\ud83e\udd9e", "requires": {"config": ["night-market.sanctum:shared", "night-market.imbue:proof-of-work"]}}} source: claude-night-market source_plugin: sanctum --- > **Night Market Skill** — ported from [claude-night-market/sanctum](https://github.com/athola/claude-night-market/tree/master/plugins/sanctum). For the full experience with agents, hooks, and commands, install the Claude Code plugin. # 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. ## Troubleshooting ### Common Issues **Command not found** Ensure all dependencies are installed and in PATH **Permission errors** Check file permissions and run with appropriate privileges **Unexpected behavior** Enable verbose logging with `--verbose` flag


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)