- π€ LLM usage: $0.5710 (336 commits)
- π€ Human dev: ~$14034 (140.3h @ $100/h, 30min dedup)
Generated on 2026-10-18 using openrouter/deep/deep-v4-pro
This directory contains the complete analysis of your project generated by code2llm. Each file serves a specific purpose for understanding, refactoring, and documenting your codebase. # noqa: E501
When you run code2llm ./ -f all, the following files are created:
| File | Format | Purpose | Key Insights |
|---|---|---|---|
evolution.toon.yaml |
YAML | π Refactoring queue - Prioritized improvements | 0 refactoring actions needed |
map.toon.yaml |
YAML | πΊοΈ Structural map + project header - Modules, imports, exports, signatures, stats, alerts, hotspots, trend | Project architecture overview |
projections.json |
JSON | π Bounded symbol catalog (code2llm.projection/v1) for intent retrieval / external indexers β deterministic, digested, capped at 2048 records |
Reuse contract without analyzer internals |
| File | Format | Purpose | Use Case |
|---|---|---|---|
context.md |
Markdown | π LLM narrative - Architecture summary | Paste into ChatGPT/Claude for code analysis |
| File | Format | Purpose | Description |
|---|---|---|---|
calls.mmd |
Mermaid | π Call graph | Function dependencies (edges only) |
# Quick health check (TOON format only) code2llm ./ -f toon # Generate all formats (what created these files) code2llm ./ -f all # LLM-ready context only code2llm ./ -f context
# Fast analysis for large projects code2llm ./ -f toon --strategy quick # Memory-limited analysis code2llm ./ -f all --max-memory 500 # Skip PNG generation (faster) code2llm ./ -f all --no-png
# Get refactoring recommendations code2llm ./ -f evolution # Focus on specific code smells code2llm ./ -f toon --refactor --smell god_function # Data flow analysis code2llm ./ -f flow --data-flow
Purpose: Quick overview of code health issues Key sections:
- HEALTH: Critical issues (π΄) and warnings (π‘)
- REFACTOR: Prioritized refactoring actions
- COUPLING: Module dependencies and potential cycles
- LAYERS: Package complexity metrics
- FUNCTIONS: High-complexity functions (CC β₯ 10)
- CLASSES: Complex classes needing attention
Example usage:
# View health issues cat analysis.toon | head -30 # Check refactoring priorities grep "REFACTOR" analysis.toon
Purpose: Step-by-step refactoring plan Key sections:
- NEXT: Immediate actions to take
- RISKS: Potential breaking changes
- METRICS-TARGET: Success criteria
Example usage:
# Get refactoring plan cat evolution.toon.yaml # Track progress grep "NEXT" evolution.toon.yaml
Purpose: Understand data movement through the system (legacy / explicit opt-in) Key sections:
- PIPELINES: Data processing chains
- CONTRACTS: Function input/output contracts
- SIDE_EFFECTS: Functions with external impacts
Example usage:
# Find data pipelines grep "PIPELINES" flow.toon # Identify side effects grep "SIDE_EFFECTS" flow.toon
Purpose: High-level architecture overview plus compact project header Key sections:
- MODULES: All modules with basic stats
- IMPORTS: Dependency relationships
- EXPORTS: Public API surface and signatures
- HEADER: Stats, alerts, hotspots, evolution trend
Example usage:
# See project structure cat map.toon.yaml | head -50 # Find public APIs grep "SIGNATURES" map.toon.yaml
Purpose: Compact module view generated from project.yaml data Status: Legacy view generated on demand from unified project.yaml
Example usage:
# View compact project structure cat project.toon.yaml | head -30 # Find largest files grep -E "^ .*[0-9]{3,}$" project.toon.yaml | sort -t',' -k2 -n -r | head -10
Purpose: Pre-formatted prompt listing all generated files for LLM conversation
Generation: Written when code2llm runs with a source path and requests -f all (including --no-chunk) or code2logic # noqa: E501
Contents:
- Files section: Lists all existing generated files with descriptions, including
project.toon.yamlwhen generated by-f all# noqa: E501 - Source files section: Highlights important source files such as
cli_exports/orchestrator.py - Missing section: Shows which files weren't generated (if any)
- Task section: Refactoring brief with concrete execution instructions, not just analysis
- Priority Order section: State-dependent refactoring priorities, starting with blockers and then architecture cleanup # noqa: E501
- Requirements section: Guidelines for suggested changes
Example usage:
# View the prompt cat prompt.txt # Copy to clipboard and paste into ChatGPT/Claude cat prompt.txt | pbcopy # macOS cat prompt.txt | xclip -sel clip # Linux
Purpose: Ready-to-paste context for AI assistants Key sections:
- Overview: Project statistics
- Architecture: Module breakdown
- Entry Points: Public interfaces
- Patterns: Design patterns detected
Example usage:
# Copy to clipboard for LLM cat context.md | pbcopy # macOS cat context.md | xclip -sel clip # Linux # Use with Claude/ChatGPT for code analysis
Purpose: Visual understanding of code structure Files:
flow.mmd- Detailed control flow with complexity colorscalls.mmd- Simple call graphcompact_flow.mmd- High-level module view*.png- Pre-rendered images
Example usage:
# View diagrams open flow.png # macOS xdg-open flow.png # Linux # Edit in Mermaid Live Editor # Copy content of .mmd files to https://mermaid.live
# Quick health check code2llm ./ -f toon cat analysis.toon | grep -E "(HEALTH|REFACTOR)"
# Get refactoring queue code2llm ./ -f evolution cat evolution.toon.yaml # Focus on specific issues code2llm ./ -f toon --refactor --smell god_function
# Generate context for AI code2llm ./ -f context cat context.md # Use with Claude: "Based on this context, help me refactor the god modules"
# Generate all docs for team code2llm ./ -f all -o ./docs/ # Create visual diagrams open docs/flow.png
- π΄ Critical (β₯5.0): Immediate refactoring needed
- π High (3.0-4.9): Consider refactoring
- π‘ Medium (1.5-2.9): Monitor complexity
- π’ Low (0.1-1.4): Acceptable
- βͺ Basic (0.0): Simple functions
- GOD Module: Too large (>500 lines, >20 methods)
- HUB: High fan-out (calls many modules)
- FAN-IN: High incoming dependencies
- CYCLES: Circular dependencies
- PIPELINE: Sequential data processing
- CONTRACT: Clear input/output specification
- SIDE_EFFECT: External state modification
#!/bin/bash # Analyze code quality in CI code2llm ./ -f toon -o ./analysis if grep -q "π΄ GOD" ./analysis/analysis.toon; then echo "β God modules detected" exit 1 fi
#!/bin/sh # .git/hooks/pre-commit code2llm ./ -f toon -o ./temp_analysis if grep -q "π΄" ./temp_analysis/analysis.toon; then echo "β οΈ Critical issues found. Review before committing." fi rm -rf ./temp_analysis
# Generate docs for README code2llm ./ -f context -o ./docs/ echo "## Architecture" >> README.md cat docs/context.md >> README.md
- Review
analysis.toon- Identify critical issues - Check
evolution.toon.yaml- Plan refactoring priorities - Use
context.md- Get LLM assistance for complex changes - Reference visualizations - Understand system architecture
- Track progress - Re-run analysis after changes
# Deep analysis with all insights code2llm ./ -m hybrid -f all --max-depth 15 -v # Performance-optimized code2llm ./ -m static -f toon --strategy quick # Refactoring-focused code2llm ./ -f toon,evolution --refactor
# Separate output directories code2llm ./ -f all -o ./analysis-$(date +%Y%m%d) # Split YAML into multiple files code2llm ./ -f yaml --split-output # Separate orphaned functions code2llm ./ -f yaml --separate-orphans
Generated by: code2llm ./ -f all --readme
Analysis Date: 2026-05-25
Total Functions: 1312
Total Classes: 143
Modules: 427
For more information about code2llm, visit: https://github.com/tom-sapletta/code2llm
Licensed under Apache-2.0.
See dependency updates and Python tool groups for locked tests, daily updates and freshness checks.