Zero-configuration AI context generation system with extreme quality enforcement and Toyota Way standards. Analyze any codebase instantly through CLI, MCP, or HTTP interfaces. Built by Pragmatic AI Labs.
Two groundbreaking systems that redefine code quality and AI collaboration!
- Unified Quality Enforcement System (v2.82.0): Real-time monitoring with ML intelligence and SRE-style budgets
- AGENTS.md Integration (v2.83.0): Bridge markdown-based agent guidance with PMAT's quality enforcement
- 📖 Full Documentation → | 🚀 Quick Start → | 🏗️ Architecture →
🚀 Unified Quality Enforcement System (NEW in v2.82.0)
Complete quality automation from monitoring to enforcement! Revolutionary dual-track quality system with immediate production value:
- 🔄 Real-time Monitoring: 5-10ms file analysis with incremental AST parsing
- ⚖️ SRE-style Error Budgets: Team-specific quality budgets with regeneration
- 🧠 ML-driven Intelligence: Context-aware refactoring suggestions with confidence scoring
- 🤖 Conservative Automation: Safe transformations with Git rollback protection
- 📊 Comprehensive Observability: Web dashboard (port 8080), Prometheus metrics, GitHub Actions
- 🎓 Progressive Adoption: Team onboarding with gamification and phased rollout
- 📖 Deployment Guide → | 🔧 Quick Start → | 📊 Dashboard →
🤖 AGENTS.md Integration (NEW in v2.83.0)
Bridge AI agents with your codebase through standardized markdown! Complete integration of the AGENTS.md standard:
- 📝 Full Parser: Extract commands, guidelines, and quality rules from AGENTS.md files
- 🔍 Auto-Discovery: Find and watch AGENTS.md files with caching and real-time updates
- ⚡ Safe Execution: Sandboxed command execution with resource limits and quality gates
- 🎨 Generator: Create AGENTS.md from PMAT analysis with language-specific templates
- 🌉 MCP Bridge: Bidirectional translation between AGENTS.md and MCP protocols
- ✅ Quality Integration: Apply PMAT quality standards to all agent operations
- 📖 Full Documentation → | 📄 Example AGENTS.md → | 🚀 Quick Start →
🔬 WebAssembly Quality Assurance (NEW in v2.77.0)
Comprehensive WASM module analysis and verification! Analyze WebAssembly binaries for quality, security, and performance:
- 🔍 Streaming Analysis: Handle large WASM files with streaming parser pipeline
- 🔒 Formal Verification: Incremental verification with shadow stack analysis
- 🛡️ Security Scanning: Pattern-based vulnerability detection (buffer overflow, integer overflow, etc.)
- 📊 Performance Profiling: Instruction mix analysis and hot function identification
- 📈 Quality Baselines: Multi-anchor comparison with release/preview/experimental baselines
- 📝 Multiple Output Formats: Summary, JSON, Detailed, SARIF for CI/CD integration
- 📖 Full Documentation → | 🔧 Usage Guide → | 🚀 Examples →
🗄️ TDG Dogfooding Storage (NEW in v2.68.0)
Persistent file score storage for continuous quality improvement! PMAT now tracks its own quality metrics:
- 📊 Automatic Storage: Every TDG analysis automatically persists scores to disk
- ⚡ Smart Caching: Repeated analyses use stored scores for instant results
- 📈 Historical Tracking: Foundation for quality trend analysis and regression detection
- 💾 Tiered Storage: Hot/warm/cold storage optimization (3.6MB+ real data stored)
- 🔍 Storage Management:
pmat tdg storage stats
for monitoring and diagnostics - 🏭 True Dogfooding: PMAT eating its own dog food by tracking its own code quality
🎯 Pre-commit Hooks Management (New in v2.66.0)
Single source of truth configuration for quality gate enforcement! Eliminate configuration duplication with PMAT-managed pre-commit hooks:
- Dynamic Hook Generation: Hooks generated from
pmat.toml
configuration - Quality Gate Enforcement: Complexity, SATD, coverage checks at commit time
- Zero Configuration Duplication: One config file, all thresholds synchronized
- Easy Management:
pmat tdg hooks install --backup
to get started - 📖 Full Documentation →
🚀 v2.77.0 Release: WebAssembly Quality Assurance & Sprint 89 Technical Debt Elimination!
- 🔬 WASM Module: Complete WebAssembly analysis, verification, and security scanning
- 🔒 Formal Verification: Incremental verification with shadow stack analysis for WASM binaries
- 🛡️ Security Scanning: Pattern-based vulnerability detection for common WASM exploits
- 📊 Performance Profiling: Instruction mix analysis and hot function identification
- 🔧 Sprint 89 Complete: Eliminated 62% of complexity in WASM handler (26→10 cyclomatic)
- 📈 Quality Baselines: Multi-anchor baseline system for regression detection
🔧 v2.70.0 Clippy Automation: Intelligent Automatic Clippy Fixes
- 🎯 Confidence-Based: Only applies fixes above configurable thresholds (0.5-1.0)
- 🔄 Transactional Safety: Atomic changes with automatic rollback on failure
- ⚡ Performance: Cached AST analysis, parallel processing, <20s for 100K LOC
- 📊 CI/CD Ready: GitHub Actions, pre-commit hooks, MCP tool integration
- 🛡️ Risk Assessment: Identifies unsafe code, macros, lifetime changes before fixing
- 📊 Entropy Analysis: Actionable AST pattern-based entropy with fix suggestions and LOC reduction estimates
- 🧮 Advanced Algorithms: Winnowing, TF-IDF, Cosine Similarity, Jaccard Index, Levenshtein Distance
- 📄 Multi-Format Output: JSON, Markdown, CSV, SARIF, and Summary formats
- 🚀 Performance: Optimized for 100K+ LOC with parallel processing
- 🔧 Full Integration: CLI commands, MCP tools, and comprehensive examples
🚀 v2.39.0 Release: TDG System with MCP Integration & Advanced Monitoring! Production-ready technical debt analysis:
- 🌐 Web Dashboard: Real-time monitoring with Axum-based interface and Server-Sent Events
- 🛠️ 6 MCP Tools: Enterprise-grade external integration (tdg_analyze_with_storage, tdg_system_diagnostics, etc.)
- 📊 Advanced Analytics: Metrics aggregation, performance profiling, bottleneck detection
- 🚨 Alert System: Configurable thresholds with multi-channel notifications
- 📤 Multi-format Export: JSON, CSV, SARIF, HTML, Markdown, XML, Prometheus support
- 💾 Storage Flexibility: Pluggable backends (Sled, RocksDB, InMemory) with trait abstraction
🔧 v2.14.0 Release: Technical Debt Elimination via TDD! Major fixes using Test-Driven Development:
- ✅ Language Detection Fixed: Functions now properly detected (was 0, now detects all)
- 🚫 Zero Stub Implementations: All stub code eliminated with real implementations
- 📉 Complexity Reduced: Ruchy parser from 89 to ≤4 cyclomatic complexity (95% reduction)
- 🧪 TDD Coverage: 80%+ test coverage on critical language detection paths
- 🏭 Toyota Way Applied: ONE implementation principle, zero defect tolerance
🎯 v2.13.0: Technical Debt Grading (TDG) System! Complete code quality scoring with 6 orthogonal metrics:
- 📊 Comprehensive Scoring: Structural complexity, semantic complexity, code duplication, coupling analysis
- 📚 Documentation Coverage: Language-specific documentation pattern detection and scoring
- 🎨 Consistency Analysis: Naming conventions, indentation patterns, and code style consistency
- 🏆 Grade Classification: A+ through F grading system with detailed component breakdowns
- 🌍 Multi-Language Support: 10+ languages including Rust, Python, JavaScript, TypeScript, Go, Java, C/C++
- 🛠️ CLI & MCP Integration:
pmat analyze tdg
command and MCP tools for programmatic access- 📈 Project Analysis: Directory-level analysis with language distribution and aggregated scoring
🚀 v2.10.0: Claude Code Agent Mode - "Always Working" Achievement! Transform PMAT into a persistent background quality agent:
- 🤖 Claude Code Integration: Native MCP server for seamless Claude Code integration
- 💾 Persistent State: Monitoring state maintained across restarts with auto-save
- ⚙️ Production Ready: Environment-specific configs for dev, prod, and CI/CD
- 📊 Real-time Monitoring: Continuous quality tracking with file system watching
- 🏗️ Service Architecture: Systemd deployment with health checks and auto-restart
🎯 v2.9.0: Universal Demo "Just Works" Achievement! Complete AI-powered repository intelligence with multi-language analysis:
- 🤖 AI-Powered Recommendations: Framework-aware repository recommendations with complexity-based learning tiers
- 🌍 Multi-Language Intelligence: Advanced polyglot analysis with cross-language dependency detection
- 🏛️ Architecture Pattern Recognition: Microservices, Layered, Event-driven pattern detection with confidence scoring
- 📚 Repository Showcase Gallery: Curated collection of 8+ repositories across languages and complexity levels
- ⚡ Universal Demo: Any GitHub repository URL → Complete analysis with AI recommendations
- 🌐 Enhanced Web Demo: Interactive visualizations with 3 new API endpoints (/api/recommendations, /api/polyglot, /api/showcase)
- Toyota Way Excellence: Zero compilation defects maintained throughout development
Choose your preferred installation method - PMAT is available across all major package ecosystems:
cargo install pmat
# macOS/Linux - Homebrew
brew install pmat
# Windows - Chocolatey
choco install pmat
# Ubuntu/Debian - APT
sudo apt install pmat # (via PPA - coming soon)
# Arch Linux - AUR
yay -S pmat
# Node.js - npm (global)
npm install -g pmat-agent
# Latest version
docker run --rm -v $(pwd):/workspace paiml/pmat:latest pmat --version
# Interactive analysis
docker run --rm -v $(pwd):/workspace -w /workspace paiml/pmat:latest pmat context
git clone https://github.com/paiml/paiml-mcp-agent-toolkit
cd paiml-mcp-agent-toolkit
make build
# Linux/macOS Quick Install
curl -sSfL https://raw.githubusercontent.com/paiml/paiml-mcp-agent-toolkit/master/scripts/install.sh | sh
# Windows PowerShell
# Download from: https://github.com/paiml/paiml-mcp-agent-toolkit/releases
# Analyze current directory
pmat context
# Technical Debt Grading (TDG) - v2.39.0!
pmat tdg . --include-components
# Start TDG web dashboard
pmat tdg dashboard --port 8081 --open
# TDG analysis with automatic persistent storage (NEW - v2.68.0!)
pmat tdg server/src/tdg/analyzer_ast.rs
# Scores automatically stored in ~/.pmat/tdg-warm and ~/.pmat/tdg-cold
# View storage statistics and dogfooding progress
pmat tdg storage stats
# Get complexity metrics
pmat analyze complexity --top-files 10
# Find technical debt
pmat analyze satd
# Code similarity detection - v2.63.0! 🔍
pmat analyze duplicates --detection-type all # Find all types of duplicates
pmat analyze duplicates --format sarif # Export to SARIF format
pmat analyze duplicates --detection-type semantic --threshold 0.7
# Analysis with timeout control - NEW! 🔧
pmat analyze complexity --timeout 30 # 30-second timeout
pmat analyze dead-code --timeout 60 # 60-second timeout
pmat analyze satd --timeout 45 # 45-second timeout
# Run quality gates
pmat quality-gate --strict
# WebAssembly Analysis - NEW in v2.77.0! 🔬
pmat analyze wasm module.wasm # Basic analysis
pmat analyze wasm module.wasm --verify # With formal verification
pmat analyze wasm module.wasm --security # Security vulnerability scan
pmat analyze wasm module.wasm --profile # Performance profiling
pmat analyze wasm module.wasm --baseline ref.wasm # Quality comparison
pmat analyze wasm module.wasm --format sarif # CI/CD integration
# 📖 See full documentation: docs/wasm-features.md
# Start MCP server
pmat mcp
# Analyze any GitHub repository with AI recommendations
cargo run --example analyze_github_repo -- --url https://github.com/rust-lang/rust-clippy
# Compare multiple repositories across languages
cargo run --example compare_repos
# Run quality gates on GitHub repositories
cargo run --example quality_gate_github -- https://github.com/owner/repo
# Start interactive web demo
pmat demo --serve
# Then visit http://localhost:8080 for:
# • AI-powered repository recommendations
# • Multi-language project intelligence
# • Repository showcase gallery
# • Interactive analysis visualizations
# Setup quality enforcement (one-time)
make setup-quality
# Start development with quality checks
make dev
# Create quality-enforced commit
make commit
# Verify sprint quality
make sprint-close
- Technical Debt Grading (TDG): 6-metric orthogonal code quality scoring with A+ through F grading
- Real-time Dashboard: Web-based monitoring with live metrics and performance tracking
- Advanced Analytics: Metrics aggregation, trend detection, bottleneck analysis
- Performance Profiling: Flame graph generation, CPU/I/O/Memory analysis
- Alert Management: Configurable thresholds with notification channels
- Multi-format Export: 8 export formats (JSON, CSV, SARIF, HTML, Markdown, XML, Prometheus)
- Storage Flexibility: Pluggable backends with tiered Hot/Warm/Cold architecture
- MCP Integration: 6 enterprise tools for external system integration
- Complexity Analysis: McCabe cyclomatic & cognitive complexity with AST precision
- Dead Code Detection: Graph-based reachability analysis across 30+ languages
- SATD Detection: Self-admitted technical debt with severity classification
- Documentation Coverage: Language-specific pattern detection with scoring algorithms
- Consistency Analysis: Naming conventions and code style consistency measurement
- Deep Context Generation: Multi-dimensional analysis optimized for AI agents
- Smart Recommendations: Framework-aware repository suggestions with complexity matching
- Polyglot Analysis: Cross-language dependency detection and architecture pattern recognition
- Repository Showcase: Curated gallery with learning pathways from beginner to expert
- Integration Points: Risk assessment of multi-language project coupling with mitigation strategies
- Quality Gates: Zero-tolerance enforcement (complexity ≤20, SATD=0, coverage >80%)
- Quality Proxy: AI code interceptor with 7-stage validation pipeline
- PDMT Integration: Deterministic todo generation with embedded quality requirements
- Refactoring Engine: State machine-based code transformation with ACID snapshots
- MCP Protocol: 24 tools via unified pmcp SDK 1.3.0 server (includes 6 new TDG enterprise tools)
- TDG Web Dashboard: Axum-based real-time interface with SSE streaming
- HTTP API: RESTful with Server-Sent Events streaming
- CLI Interface: 50+ commands with POSIX-compliant exit semantics
- Complete Specification - Unified source of truth (36 sections)
- TDG Guide - NEW! Technical Debt Grading system documentation
- Transactional Hashed TDG - 🚀 v2.38.0! Enterprise-grade TDG with caching, scheduling, and resource control
- API Reference - Service APIs and integration patterns
- CLI Reference - Complete command documentation
- Toyota Way Guide - Development workflow and standards
- Sprint Management - Task tracking and execution DAG
- Quality Gates - Enforcement mechanisms
- MCP Integration - Model Context Protocol setup
- PDMT Guide - Deterministic todo generation
- CI/CD Integration - Pipeline integration
PMAT implements Toyota Production System principles through rigorous static analysis:
- Kaizen (改善): Iterative file-by-file improvement with measurable ΔQ metrics
- Genchi Genbutsu (現地現物): Direct AST traversal, no heuristics
- Jidoka (自働化): Automated quality gates with fail-fast semantics
- Zero SATD Policy: Compile-time enforcement of zero technical debt
// Unified service layer with dependency injection
pub trait Service: Send + Sync {
type Input: Serialize + DeserializeOwned;
type Output: Serialize + DeserializeOwned;
async fn process(&self, input: Self::Input) -> Result<Self::Output, Self::Error>;
}
// All protocols use unified request/response
#[derive(Serialize, Deserialize)]
pub struct UnifiedRequest {
pub operation: Operation,
pub params: Value,
pub context: RequestContext,
}
- Startup: 4ms hot, 127ms cold (mmap'd grammar cache)
- Analysis: 487K LOC/s single-thread, 3.9M LOC/s multi-core
- Memory: 47MB base + 312KB per KLOC
- SIMD: 43% vectorized paths, 2.7x AVX2 speedup
- Rust 1.80.0+
- Git (for repository analysis)
git clone https://github.com/paiml/paiml-mcp-agent-toolkit
cd paiml-mcp-agent-toolkit
# Setup Toyota Way quality enforcement
make setup-quality
# Build and test
make build
make validate
# Run examples
make examples
[dependencies]
pmat = "2.39.0"
use pmat::services::code_analysis::CodeAnalysisService;
#[tokio::main]
async fn main() -> Result<(), Box<dyn std::error::Error>> {
let service = CodeAnalysisService::new();
// Generate AI-optimized context
let context = service.generate_context(".", None).await?;
// Analyze complexity with Toyota Way standards
let complexity = service.analyze_complexity(".", Some(10)).await?;
Ok(())
}
- Rust: Full cargo integration with syn AST
- TypeScript/JavaScript: SWC-based parsing
- Python: RustPython AST analysis
- C/C++: Tree-sitter with goto tracking
- Ruchy: v1.5.0 support with advanced analysis
- Full AST parsing with 35+ token types
- Halstead metrics (volume, difficulty, effort, time, bugs)
- Dead code detection (unused functions/variables)
- Type inference for literals and binary operations
- Actor message flow analysis with deadlock detection
- Enhanced pattern matching complexity scoring
- Import/export dependency tracking
- Kotlin: Tree-sitter based analysis
- 30+ Languages: Via tree-sitter grammar support
PMAT provides 18 MCP tools via unified pmcp SDK server:
# Start MCP server (auto-detects transport)
pmat mcp
# Test with Claude Code
cargo run --example mcp_server_pmcp
cargo run --example test_pmcp_server
analyze_tdg
- Technical Debt Grading with 6-metric scoringanalyze_tdg_compare
- Compare TDG scores between files/projectstdg_analyze_with_storage
- NEW v2.39.0! TDG analysis with configurable storage backendstdg_system_diagnostics
- NEW v2.39.0! Comprehensive system health monitoringtdg_storage_management
- NEW v2.39.0! Storage operations and managementtdg_performance_profiling
- NEW v2.39.0! Performance analysis with flame graphstdg_alert_management
- NEW v2.39.0! Alert configuration and monitoringtdg_export_data
- NEW v2.39.0! Multi-format data export (8 formats)analyze_complexity
- Complexity metricsanalyze_satd
- Technical debt detectionanalyze_dead_code
- Unused code analysisquality_gate
- Comprehensive quality validationrefactor_start
- Begin refactoring workflowpdmt_deterministic_todos
- Generate quality todosgithub_create_issue
- Create GitHub issues- AI recommendation tools for intelligent repository analysis
- And 10 more...
Transform PMAT into a persistent background quality agent that continuously monitors your codebase:
# Start agent as MCP server for Claude Code
pmat agent mcp-server
# Configure in Claude Code settings.json:
{
"mcpServers": {
"pmat": {
"command": "pmat",
"args": ["agent", "mcp-server"],
"env": {}
}
}
}
# Start monitoring a project
pmat agent start --project-path /path/to/project
# Check monitoring status
pmat agent status
# Stop monitoring
pmat agent stop
- Real-time Monitoring: File system watching with instant quality feedback
- Persistent State: Maintains metrics across restarts with auto-save
- Toyota Way Compliance: Enforces ≤20 complexity with zero SATD tolerance
- Analysis Timeouts: Configurable timeouts prevent infinite hangs (NEW! 🔧)
- Production Ready: Systemd service with health checks and auto-restart
- MCP Native: Seamless Claude Code integration via stdio transport
start_quality_monitoring
- Begin monitoring a projectstop_quality_monitoring
- Stop monitoringget_quality_status
- Current quality metricsrun_quality_gates
- Execute quality checksanalyze_complexity
- Complexity analysishealth_check
- Agent health status
See Claude Code Agent Guide for detailed setup and deployment instructions.
# Real-time TDG metrics
GET /api/metrics
# System health status
GET /api/health
# Storage statistics
GET /api/storage/stats
# Run TDG analysis
GET /api/analysis?path=src/main.rs
# System diagnostics
GET /api/diagnostics
# Real-time metrics stream (SSE)
GET /api/events
# Storage operations
POST /api/storage/operation
# AI-powered repository recommendations
GET /api/recommendations
# Multi-language project intelligence
GET /api/polyglot
# Repository showcase gallery
GET /api/showcase
# Core analysis APIs
GET /api/summary
GET /api/metrics
GET /api/hotspots
GET /api/dag
PMAT enforces extreme quality standards:
- Complexity: ≤20 cyclomatic, ≤15 cognitive
- Technical Debt: 0 SATD comments allowed
- Test Coverage: >80% with property-based testing
- Code Quality: 0 lint warnings, 0 dead code
- Documentation: Synchronized with every commit
# Run comprehensive quality analysis
pmat quality-gate --strict
# CI/CD integration
pmat analyze complexity --fail-on-violation
pmat analyze satd --fail-on-violation
pmat quality-gate --strict --fail-on-violation
PMAT follows Toyota Way development principles:
- Setup quality enforcement:
make setup-quality
- Start development:
make dev
- Make changes with documentation updates
- Quality-enforced commit:
make commit
- Sprint verification:
make sprint-close
All contributions must meet:
- Zero SATD comments
- Complexity ≤20 per function
- Full test coverage
- Documentation updates
See CONTRIBUTING.md for detailed guidelines.
Licensed under the MIT License. See LICENSE for details.
Built with ❤️ by Pragmatic AI Labs