File Analysis

---
name: file-analysis
description: 'Provides structural context for downstream review and refactoring workflows.
  Use when before architecture reviews to understand file organization, exploring
  unfamiliar codebases to map structure, estimating scope for refactoring or migration.
  Do not use when general code exploration - use the Explore agent. DO NOT use when:
  searching for specific patterns - use Grep directly.'
category: workspace-ops
tags:
- files
- structure
- analysis
- codebase
- exploration
tools:
- Bash
- Glob
- Grep
- TodoWrite
complexity: medium
estimated_tokens: 800
dependencies:
- sanctum:shared
- imbue:proof-of-work
---

# 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