code-analyzerlisted

# Code Analyzer Analyze codebase to build comprehensive mental model for downstream operations. ## Workflow Overview 1. **Scan** — Collect facts via bash script (deterministic) 2. **Understand** — Interpret structure and stack 3. **Trace** — Follow execution paths through abstraction layers (skip if greenfield) 4. **Build** — Construct dependency graph and mental model 5. **Confirm** — Output summary with key files list ## Step 1: Scan Project Run codebase scanner to collect facts: ```bash .claude/skills/code-analyzer/scripts/scan-codebase.sh ``` Scanner auto-detects project root (git root or pwd) and collects: - Structure: file count, extensions, configs, directories, src modules - Markers: AICODE-NOTE, AICODE-TODO, AICODE-FIX with locations - Git: branch, modified/added/deleted files Outputs JSON. No external dependencies required. ### Exclusions (automatic) - node_modules, .git, dist, build - __pycache__, .venv, venv - ai-docs, .next, .nuxt, coverage, .cache ## Step 2: Understand Structure Interpret scan results to determine: - **Stack**: Language(s) from extensions, framework from configs - **Entry points**: Main/index/app files in directories - **Modules**: Domain boundaries from src_modules or directories - **Conventions**: Naming patterns, structure style ## Step 3: Trace Patterns **Skip if greenfield project (no src files found in Step 1).** For existing codebases, trace how code actually works — not just what files exist: **3.1 Find similar features**