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Technical Debt Tracking with PMAT

Detect SATD annotations, estimate debt hours, and generate trend reports.

161|27|Updated May 25, 2025
Search Tags:#code quality#analysis#technical debt#reporting#SATD#debt tracking
One-click install
npx skills add https://github.com/paiml/paiml-mcp-agent-toolkit --skill technical-debt-tracking-with-pmat
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: Technical Debt Tracking with PMAT
Source: https://github.com/paiml/paiml-mcp-agent-toolkit/tree/main/.claude/skills/pmat-tech-debt
Command: npx skills add https://github.com/paiml/paiml-mcp-agent-toolkit --skill technical-debt-tracking-with-pmat

SYSTEM DOCUMENTATION & REQUIREMENTS

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

Frequently Asked Questions about Technical Debt Tracking with PMAT

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I detect and inventory self-admitted technical debt in my codebase?▼

SATD detection identifies TODO, FIXME, HACK, XXX, and NOTE annotations across your codebase. Run `pmat analyze satd --path . --output satd_inventory.json` to catalog all self-admitted debt items by type and location for baseline tracking.

Can I estimate how many hours it will take to fix technical debt?▼

Yes. Technical debt quantification estimates repayment effort in hours for each debt item. Use `pmat analyze tech-debt --path . --estimate-hours --output debt_estimates.json` to generate hour-based prioritization for sprint planning.

What's the best way to track whether technical debt is improving or getting worse?▼

Trend tracking compares baseline debt snapshots against current state to monitor improvement or regression. Establish a baseline with `pmat analyze satd --path . --baseline satd_baseline.json`, then run comparisons over time with `pmat compare-debt` to visualize debt trajectory.

How do I create a technical debt report for stakeholders?▼

Debt reporting generates markdown or executive-ready reports with inventories, hour estimates, and trend visualizations. Run `pmat analyze satd --path . --format markdown --output TECH_DEBT_REPORT.md` to produce stakeholder-focused documentation.

Does this work with codebases that don't have debt annotations yet?▼

SATD detection requires existing code annotations (TODO, FIXME, HACK, XXX, NOTE comments). If your codebase lacks these markers, you'll need to add them first before PMAT can inventory and quantify the debt.

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