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Technical Debt Tracking with PMAT

Official

Quantify and manage TD with PMAT.

Software Engineering#code quality#analysis#technical debt#reporting#SATD#debt tracking
Authorpaiml
Version1.0.0
Installs0

System Documentation

What problem does it solve?

This Skill helps teams identify, quantify, and monitor technical debt using PMAT (Pragmatic AI Labs MCP Agent Toolkit). It detects Self-Admitted Technical Debt (SATD) annotations in code (TODO, FIXME, HACK, XXX, NOTE), estimates repayment effort in hours, tracks debt trends over time, and creates stakeholder-ready reports.

Core Features & Use Cases

  • SATD Detection: Identify and categorize self-admitted debt across the codebase.
  • Debt Quantification: Estimate hours required to resolve each debt item.
  • Trend Tracking: Baseline vs. current debt to monitor improvement or regression.
  • Reporting: Generate markdown or executive reports for stakeholders.

Quick Start

  1. Inventory SATD annotations: pmat analyze satd --path . --output satd_inventory.json
  2. Estimate repayment hours: pmat analyze tech-debt --path . --estimate-hours --output debt_estimates.json
  3. Track changes over time:
    • pmat analyze satd --path . --baseline satd_baseline.json
    • pmat compare-debt --baseline satd_baseline.json --current debt_current.json
  4. Create a debt report: pmat analyze satd --path . --format markdown --output TECH_DEBT_REPORT.md

Dependency Matrix

Required Modules

None required

Components

Standard package

💻 Claude Code Installation

Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.

Please help me install this Skill:
Name: Technical Debt Tracking with PMAT
Download link: https://github.com/paiml/paiml-mcp-agent-toolkit/archive/main.zip#technical-debt-tracking-with-pmat

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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