Technical Debt Tracking with PMAT

Technical Debt Tracking with PMAT is a skill for Claude Code from paiml/paiml-mcp-agent-toolkit. It costs 123 tokens per session (3,543 once invoked), scanned A, original, MIT.

A guide for finding and organising technical debt, meaning postponed work, known problems, or temporary solutions in a codebase, using PMAT.

In plain words
What is it for?
Use it to detect self-admitted technical debt in files, plan debt-repayment work, and compare debt over time. It also covers code-quality assessments and prioritisation.
Why use it?
It turns scattered TODO, FIXME, HACK, and similar comments into information that can be reviewed and prioritised. This helps teams assess code-quality work during audits or sprint planning.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: installed under .agents/ (shared by several agents).

Good fit Use it to detect self-admitted technical debt in files, plan debt-repayment work, and compare debt over time. It also covers code-quality assessments and prioritisation.

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Install with agentmods
npx agentmods add skills/paiml/paiml-mcp-agent-toolkit/pmat-tech-debt
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add paiml/paiml-mcp-agent-toolkit --skill pmat-tech-debt
Clone the repo
git clone --depth 1 https://github.com/paiml/paiml-mcp-agent-toolkit

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for Technical Debt Tracking with PMAT

README.md
[![agentmods](https://agentmods.dev/badge/skills/paiml/paiml-mcp-agent-toolkit/pmat-tech-debt/github.svg)](https://agentmods.dev/skills/paiml/paiml-mcp-agent-toolkit/pmat-tech-debt)
Your own site
<a href="https://agentmods.dev/skills/paiml/paiml-mcp-agent-toolkit/pmat-tech-debt"><img src="https://agentmods.dev/badge/skills/paiml/paiml-mcp-agent-toolkit/pmat-tech-debt/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for Technical Debt Tracking with PMAT

Your own site · 80×15
<a href="https://agentmods.dev/skills/paiml/paiml-mcp-agent-toolkit/pmat-tech-debt"><img src="https://agentmods.dev/badge/skills/paiml/paiml-mcp-agent-toolkit/pmat-tech-debt.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 123 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,543 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00123 $0.03543
Opus 5 $0.00062 $0.01772
Sonnet 5 $0.00025 $0.00709
Haiku 4.5 $0.00012 $0.00354

Measured 11d ago against content hash 33a8836b807d, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

Technical Debt Tracking with PMAT scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.agents/skills/pmat-tech-debt/SKILL.md · 404 lines

How it starts

The opening of the file, as written. The whole thing — 404 lines — stays where its author put it; the contents beside it link to each section on GitHub.

PMAT Technical Debt Tracking Skill

You are an expert at identifying, quantifying, and managing technical debt using PMAT (Pragmatic AI Labs MCP Agent Toolkit).

When to Activate

This skill should automatically activate when:

  1. User mentions "technical debt", "tech debt", or "TD"
  2. User asks about TODO, FIXME, HACK comments in the codebase
  3. Planning sprint work and need debt repayment estimates
  4. Conducting code quality audits or assessments
  5. Tracking debt trends over time (sprint-to-sprint comparison)

Core Concept: SATD (Self-Admitted Technical Debt)

Definition: Comments explicitly admitting suboptimal implementation Types:

  • TODO: Deferred work, future enhancements
  • FIXME: Known bugs or issues requiring fixes
  • HACK: Temporary workarounds needing proper solutions
  • XXX: Critical issues requiring immediate attention
  • NOTE: Important context or warnings

Scientific Foundation: Based on research by Potdar & Shihab (2014) on self-admitted technical debt in code comments.

Available PMAT Commands

1. Detect Technical Debt

pmat analyze satd --path <file_or_directory> --output debt_report.json

Output: All SATD annotations with location, type, and context

2. Quantify Debt Hours

pmat analyze tech-debt --path <directory> --estimate-hours --output debt_hours.json

Output: Estimated hours to resolve each debt item

3. Track Debt Trends

# Baseline measurement
pmat analyze satd --path . --output debt_baseline.json

# After sprint work
pmat analyze satd --path . --output debt_current.json

# Compare trends
pmat compare-debt --baseline debt_baseline.json --current debt_current.json

4. Generate Debt Report

pmat analyze satd --path . --format markdown --output TECH_DEBT_REPORT.md

Output: Markdown report suitable for documentation or stakeholder review

Usage Workflow

Step 1: Initial Debt Assessment

Establish baseline understanding of technical debt:

Read the full file on GitHub · 404 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 11d ago First seen · 404 lines · 123 tokens per session scan A 33a8836b807d

Subscribe to this mod's changes

Technical Debt Tracking with PMAT is a skill published in the GitHub repository paiml/paiml-mcp-agent-toolkit (164 stars, last pushed yesterday), licensed MIT. It adds 123 tokens to every session and 3,543 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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