Zero-configuration AI context generation system that analyzes any codebase instantly through CLI, MCP, or HTTP interfaces. Built by Pragmatic AI Labs with extreme quality standards and zero tolerance for technical debt.
Toyota Way Success: Achieved 97% complexity reduction in stubs.rs through complete modular refactoring (v0.29.5). Project maintains zero tolerance standards: 0 SATD comments, 0 failing doctests, 0 failing property tests, 72+ comprehensive property tests, and proper separation of concerns across all components. Latest refactoring created dedicated modules (language_analyzer.rs, defect_formatter.rs, dead_code_formatter.rs) eliminating 549 lines of duplicated code while maintaining full functionality β
Install pmat using one of the following methods:
-
From Crates.io (Recommended):
cargo install pmat
-
With the Quick Install Script (Linux only):
curl -sSfL https://raw.githubusercontent.com/paiml/paiml-mcp-agent-toolkit/master/scripts/install.sh | shmacOS users: Please use
cargo install pmatinstead. Pre-built binaries are only available for Linux. -
From Source:
git clone https://github.com/paiml/paiml-mcp-agent-toolkit cd paiml-mcp-agent-toolkit cargo build --release -
From GitHub Releases: Pre-built binaries for Linux are available on the releases page. macOS and Windows users should use
cargo install pmat.
- Rust: 1.80.0 or later
- Git: For repository analysis
# Analyze current directory
pmat context
# Get complexity metrics for top 10 files
pmat analyze complexity --top-files 10
# Analyze specific files with include patterns
pmat analyze complexity --include "src/*.rs" --format json
# Test with validated examples (try these!)
cargo run --example complexity_demo
pmat analyze complexity --include "server/examples/complexity_*.rs"
# Find technical debt
pmat analyze satd
# Run comprehensive quality checks
pmat quality-gate --strictAdd to your Cargo.toml:
[dependencies]
pmat = "0.28.0"Basic usage:
use pmat::{
services::code_analysis::CodeAnalysisService,
types::ProjectPath,
};
#[tokio::main]
async fn main() -> Result<(), Box<dyn std::error::Error>> {
let service = CodeAnalysisService::new();
let path = ProjectPath::new(".");
// Generate context
let context = service.generate_context(path, None).await?;
println!("Project context: {}", context);
// Analyze complexity
let complexity = service.analyze_complexity(path, Some(10)).await?;
println!("Complexity results: {:?}", complexity);
Ok(())
}- Deep Context Analysis - Comprehensive AST-based code analysis with defect prediction
- Complexity Analysis - Accurate McCabe cyclomatic and cognitive complexity metrics with AST-based precision
- β v0.28.6+: Fixed algorithm accuracy - now provides 100% correct complexity calculations
- Supports nested control flow, match statements, async functions, and complex branching
- Validated against manual calculations with comprehensive test examples
- Dead Code Detection - Find unused code across your project
- Technical Debt Gradient (TDG) - Quantify and prioritize technical debt
- SATD Detection - Find Self-Admitted Technical Debt in comments
- Code Duplication - Detect exact, renamed, gapped, and semantic clones
- AI-Powered Auto Refactoring -
pmat refactor autoachieves extreme quality standards- Single File Mode -
pmat refactor auto --single-file-mode --file path/to/file.rsfor targeted refactoring
- Single File Mode -
- Documentation Cleanup -
pmat refactor docsmaintains Zero Tolerance Quality Standards - Interactive Refactoring - Step-by-step guided refactoring with explanations
- Enforcement Mode - Enforce extreme quality standards using state machines
- Single File Mode -
pmat enforce extreme --file path/to/file.rsfor file-specific enforcement
- Single File Mode -
- Lint Hotspot Analysis - Find files with highest defect density using EXTREME Clippy standards
- Single File Mode -
pmat lint-hotspot --file path/to/file.rsfor targeted analysis
- Single File Mode -
- Provability Analysis - Lightweight formal verification with property analysis
- Defect Prediction - ML-based prediction of defect-prone code
- Quality Enforcement - Exit with error codes for CI/CD integration
- NEW: All analyze commands now support
--fail-on-violationfor CI/CD pipelines - Exit code 0 on success, 1 when violations exceed thresholds
- Perfect for GitHub Actions, GitLab CI, Jenkins, and other CI/CD systems
- NEW: All analyze commands now support
- Rust - Full support with cargo integration
- TypeScript/JavaScript - Modern AST-based analysis
- Python - Comprehensive Python 3 support
- Kotlin - Memory-safe parsing with full language support
- C/C++ - Tree-sitter based analysis
- WebAssembly - WASM binary and text format analysis
- AssemblyScript - TypeScript-like syntax for WebAssembly
- Makefiles - Specialized linting and analysis
# Zero-configuration context generation
pmat context # Auto-detects language
pmat context --format json # JSON output
pmat context -t rust # Force toolchain
pmat context --skip-expensive-metrics # Fast mode
# Code analysis
pmat analyze complexity --top-files 5 # Complexity analysis
pmat analyze complexity --fail-on-violation # CI/CD mode - exit(1) if violations
pmat analyze churn --days 30 # Git history analysis
pmat analyze dag --target-nodes 25 # Dependency graph
pmat analyze dead-code --format json # Dead code detection
pmat analyze dead-code --fail-on-violation --max-percentage 10 # CI/CD mode
pmat analyze satd --top-files 10 # Technical debt
pmat analyze satd --strict --fail-on-violation # Zero tolerance for debt
pmat analyze deep-context --format json # Comprehensive analysis
pmat analyze deep-context --full # Full detailed report
pmat analyze deep-context --include-pattern "*.rs" # Filter by file pattern
pmat analyze big-o # Big-O complexity analysis
pmat analyze makefile-lint # Makefile quality linting
pmat analyze proof-annotations # Provability analysis
# Analysis commands
pmat analyze graph-metrics # Graph centrality metrics (PageRank, betweenness, closeness)
pmat analyze name-similarity "function_name" # Fuzzy name matching with phonetic support
pmat analyze symbol-table # Symbol extraction with cross-references
pmat analyze duplicates --min-lines 10 # Code duplication detection
pmat quality-gate --fail-on-violation # Comprehensive quality enforcement
pmat diagnose --verbose # Self-diagnostics and health checks
# WebAssembly Support
pmat analyze assemblyscript --wasm-complexity # AssemblyScript analysis with WASM metrics
pmat analyze webassembly --include-binary # WebAssembly binary and text format analysis
# Project scaffolding
pmat scaffold rust --templates makefile,readme,gitignore
pmat list # Available templates
# Refactoring engine
pmat refactor interactive # Interactive refactoring
pmat refactor serve --config refactor.json # Batch refactoring
pmat refactor status # Check refactor progress
pmat refactor resume # Resume from checkpoint
pmat refactor auto # AI-powered automatic refactoring
pmat refactor docs --dry-run # Clean up documentation
# Demo and visualization
pmat demo --format table # CLI demo
pmat demo --web --port 8080 # Web interface
pmat demo --repo https://github.com/user/repo # Analyze GitHub repo
# Quality enforcement
pmat quality-gate --fail-on-violation # CI/CD quality gate
pmat quality-gate --checks complexity,satd,security # Specific checks
pmat quality-gate --format human # Human-readable output
pmat enforce extreme # Enforce extreme quality standardsπ« See CLI usage in action
Context and code analysis:
Running demos/visualization:
# Add to Claude Code
claude mcp add pmat ~/.local/bin/pmatπ« See Claude Code usage in action
Available MCP tools:
generate_template- Generate project files from templatesscaffold_project- Generate complete project structureanalyze_complexity- Code complexity metrics with tool compositionanalyze_code_churn- Git history analysisanalyze_dag- Dependency graph generationanalyze_dead_code- Dead code detectionanalyze_deep_context- Comprehensive analysis with tool compositiongenerate_context- Zero-config context generationanalyze_big_o- Big-O complexity analysis with confidence scoresanalyze_makefile_lint- Lint Makefiles with 50+ quality rulesanalyze_proof_annotations- Lightweight formal verificationanalyze_graph_metrics- Graph centrality and PageRank analysisrefactor_interactive- Interactive refactoring with explanations
AI agents can now chain analysis tools using the --files parameter:
# Step 1: Find complexity hotspots
pmat analyze complexity --top-files 5 --format json
# Step 2: Deep analyze those specific files (MCP composition)
pmat analyze comprehensive --files src/complex.rs,src/legacy.rs
# Step 3: Target refactoring on problematic files
pmat refactor auto --files src/complex.rsMCP Agent Workflow Example:
// AI agent discovers hotspots
const hotspots = await callTool("pmat_analyze_complexity", {
top_files: 5,
format: "json"
});
// Agent extracts file paths and performs deep analysis
const detailed = await callTool("pmat_analyze_comprehensive", {
files: hotspots.files.map(f => f.path)
});
// Agent generates targeted refactoring plan
const refactor = await callTool("pmat_refactor_auto", {
files: detailed.high_risk_files
});# Start server
pmat serve --port 8080 --cors
# API endpoints
curl "https://localhost:8080/health"
curl "https://localhost:8080/api/v1/analyze/complexity?top_files=5"
curl "https://localhost:8080/api/v1/templates"
# POST analysis
curl -X POST "https://localhost:8080/api/v1/analyze/deep-context" \
-H "Content-Type: application/json" \
-d '{"project_path":"./","include":["ast","complexity","churn"]}'All analyze commands now support --fail-on-violation for seamless CI/CD integration:
name: Code Quality
on: [push, pull_request]
jobs:
quality:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v3
- uses: dtolnay/rust-toolchain@stable
- name: Install pmat
run: cargo install pmat
- name: Check Complexity
run: |
pmat analyze complexity \
--max-cyclomatic 15 \
--max-cognitive 10 \
--fail-on-violation
- name: Check Technical Debt
run: pmat analyze satd --strict --fail-on-violation
- name: Check Dead Code
run: |
pmat analyze dead-code \
--max-percentage 10.0 \
--fail-on-violation
- name: Run Quality Gate
run: pmat quality-gate --fail-on-violation- Complexity:
--max-cyclomatic(default: 20),--max-cognitive(default: 15) - Dead Code:
--max-percentage(default: 15.0%) - SATD: Fails on ANY technical debt when using
--fail-on-violation
- 0: Success - no violations found or within thresholds
- 1: Failure - violations exceed configured thresholds
See examples/ci_integration.rs for more CI/CD patterns including GitLab CI, Jenkins, and pre-commit hooks.
- Fixed Quality Gate Bug: Quality gate dead code detection now correctly analyzes code instead of always reporting violations
- Fixed Include Patterns:
--includepatterns now properly work with test directories (e.g.,--include "tests/**/*.rs") - Fixed Clippy Warning: Replaced deprecated
map_orwithis_some_andfor cleaner code
- Massive Complexity Reduction: Core
handle_refactor_autofunction complexity reduced from 136 β 21 (84% reduction) - Zero Quality Violations: Project now maintains 0 lint violations, 0 max complexity, 0 SATD comments
- Toyota Way Implementation: Applied Kaizen (continuous improvement), Genchi Genbutsu (go and see), Jidoka (quality at source), and Poka-Yoke (error-proofing) principles
- Code Size Optimization: Net reduction of 3,401 lines while improving functionality and maintainability
- Comprehensive Testing: Added extensive property tests, doctests, and unit tests for all refactored components
- Zero Compromise: No hacks, shortcuts, or technical debt introduced during refactoring
- CI/CD Support: All analyze commands now support
--fail-on-violationflag - Exit Codes: Commands exit with code 1 when violations exceed thresholds
- Configurable Thresholds: Added
--max-percentagefor dead-code analysis - Examples: Added comprehensive CI/CD examples for GitHub Actions, GitLab CI, Jenkins
- Documentation: Updated all documentation with CI/CD integration patterns
- Single File Analysis: Added
--fileflag topmat analyze comprehensivefor analyzing individual files. - Bug Fix: Fixed "No such file or directory" error in single-file refactor mode by using dynamic executable path detection.
- Test Improvements: Fixed stack overflow issues in CLI tests by using wildcard pattern matching.
- Documentation: Updated CLI reference with new single-file analysis capabilities.
- Quality Gate Tests: Added comprehensive integration tests for CI/CD quality gates.
- Public API: Made quality gate structs public for better testing support.
- Doctests: Added doctests for quality gate and DAG generation functions.
- Bug Fixes: Fixed mermaid test failures and unused import warnings.
- SATD Elimination: Removed all TODO/FIXME/HACK comments from implementation.
- Complexity Reduction: All functions now below a cyclomatic complexity of 20.
- Extreme Linting:
make lintpasses with pedantic and nursery standards. - Single File Mode: Enhanced support for targeted quality improvements.
- AI-assisted documentation cleanup to maintain Zero Tolerance Quality Standards.
- Identifies and removes temporary files, outdated reports, and build artifacts.
- Interactive mode for reviewing files before removal with automatic backups.
- Graph Metrics:
pmat analyze graph-metricsfor centrality analysis. - Name Similarity:
pmat analyze name-similarityfor fuzzy name matching. - Symbol Table:
pmat analyze symbol-tablefor symbol extraction. - Code Duplication:
pmat analyze duplicatesfor detecting duplicate code.
This project exemplifies the Toyota Way philosophy through disciplined quality practices:
- 84% Complexity Reduction: Achieved through systematic refactoring
- Zero Quality Violations: Maintained through iterative improvement
- Net -3,401 Lines: Simplified while enhancing functionality
- Data-Driven Decisions: Used actual metrics to identify complexity hotspots
- Root Cause Analysis: Fixed underlying architectural issues, not symptoms
- Measurement-Based: Every improvement verified through quantitative analysis
- ZERO SATD: No TODO, FIXME, HACK, or placeholder implementations
- ZERO High Complexity: No function exceeds cyclomatic complexity of 20
- ZERO Known Defects: All code must be fully functional
- ZERO Incomplete Features: Only complete, tested features are merged
- Comprehensive Testing: Property tests, doctests, and unit tests prevent regressions
- Automated Quality Gates: CI/CD integration prevents quality degradation
- Type Safety: Rust's type system eliminates entire categories of errors
- JSON - Structured data for tools and APIs
- Markdown - Human-readable reports
- SARIF - Static analysis format for IDEs
- Mermaid - Dependency graphs and diagrams
- Context Generation: Give AI perfect project understanding
- Code Analysis: Deterministic metrics and facts
- Template Generation: Scaffolding with best practices
- Code Reviews: Automated complexity and quality analysis
- Technical Debt: SATD detection and prioritization
- Onboarding: Quick project understanding
- CI/CD: Integrate quality gates and analysis
- Documentation: Auto-generated project overviews
- Quality Gates: Automated quality scoring
- Dependency Analysis: Visual dependency graphs
- Project Health: Comprehensive health metrics
# .github/workflows/quality.yml
- name: Run Quality Gate
run: |
pmat quality-gate \
--checks complexity,satd,security,dead-code \
--max-complexity-p99 20 \
--fail-on-violation- complexity - Cyclomatic complexity thresholds
- satd - Self-admitted technical debt (TODO/FIXME/HACK)
- security - Hardcoded passwords and API keys
- dead-code - Unused functions and variables
- entropy - Code diversity metrics
- duplicates - Code duplication detection
- coverage - Test coverage thresholds
- sections - Required documentation sections
- provability - Formal verification readiness
Explore our comprehensive documentation to get the most out of pmat.
- Architecture: Understand the system design and principles.
- CLI Reference: View the full command-line interface guide.
- API Documentation: Browse the complete Rust API documentation on docs.rs.
- Feature Overview: Discover all available features.
- MCP Integration: Learn how to integrate
pmatwith AI agents. - CI/CD Integration: Set up quality gates in your CI/CD pipeline.
- Contributing Guide: Read our guidelines for contributing to the project.
- Release Process: Follow our step-by-step release workflow.
For systems with low swap space, we provide a configuration tool:
make config-swap # Configure 8GB swap (requires sudo)
make clear-swap # Clear swap memory between heavy operationsThe project uses a distributed test architecture for fast feedback:
# Run specific test suites
make test-unit # <10s - Core logic tests
make test-services # <30s - Service integration
make test-protocols # <45s - Protocol validation
make test-e2e # <120s - Full system tests
make test-performance # Performance regression
# Run all tests in parallel
make test-all
# Coverage analysis
make coverage-stratifiedWe welcome contributions! Please see our Contributing Guide for details.
# Clone and setup
git clone https://github.com/paiml/paiml-mcp-agent-toolkit
cd paiml-mcp-agent-toolkit
# Install dependencies
make install-deps
# Run tests
make test-fast # Quick validation
make test-all # Complete test suite
# Check code quality
make lint # Run extreme quality lints
make coverage # Generate coverage report- Fork the repository
- Create a feature branch (
git checkout -b feature/amazing-feature) - Make your changes following our Zero Tolerance Quality Standards
- Run quality checks before committing:
make lint # Check code quality make test # Run all tests (fast, doctests, property tests, examples)
- Submit a pull request with a clear description of changes
Note: The make test command runs comprehensive testing including:
- β‘ Fast unit and integration tests
- π Documentation tests (doctests)
- π² Property-based tests
- π All cargo examples
See CONTRIBUTING.md for detailed guidelines.
Licensed under either of:
- Apache License, Version 2.0 (LICENSE-APACHE)
- MIT license (LICENSE-MIT)
at your option.
Built with β€οΈ by Pragmatic AI Labs