Agent skill

Tech Debt Tracker

by borghei in borghei/Claude-Skills

Scan codebases for technical debt with AST parsing, prioritize by impact, and generate trend dashboards.

MITAuto-check passedDevelopment

Install Tech Debt Tracker

skills CLI
$ npx skills add borghei/Claude-Skills --skill tech-debt-tracker -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install borghei/Claude-Skills tech-debt-tracker --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/borghei/Claude-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/engineering/tech-debt-tracker .claude/skills/tech-debt-tracker && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
tech-debt-tracker
GitHub stars
874
Token cost
~1.9k tokens
SKILL.md length
794 words
Files
22 (incl. scripts, references, assets)
Skills in repo
364
Repo updated
First seen
Licence
MIT

At a glance

Scan codebases for technical debt with AST parsing, prioritize by impact, and generate trend dashboards.

  • Tracking tech debt
  • SKILL.md covers Core Capabilities, When to Use, Clarify First and Tools, plus 3 more sections
  • Runs Python and JavaScript scripts from its folder; calls python
  • Prioritizing refactoring

What it does

Tech Debt Tracker is an agent skill from borghei/Claude-Skills. Scan codebases for technical debt with AST parsing, prioritize by impact, and generate trend dashboards. Use when tracking tech debt, prioritizing refactoring, calculating cost-of- delay, planning sprint debt, or reporting debt to execs.

Its SKILL.md is about 1.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 26 other files, including scripts, reference files and assets (for example `README.md`, `REFERENCE.md` and `assets/historical_debt_2024-01-15.json`).

It sits in Development, covering Technical debt. The repository describes itself as: 385 AI skills, 77 expert agents, and 900 stdlib Python tools for every team: engineering, PM, marketing, C-level, compliance, business ops, research, and a LinkedIn toolkit… The licence is MIT.

When your agent uses it

  • Tracking tech debt
  • Prioritizing refactoring
  • Calculating cost-of- delay
  • Planning sprint debt

Example prompts

  • “/tech-debt-tracker”

Requirements

  • Python 3
  • Node.js

What it can do on your machine

Read from SKILL.md and the folder at commit c9a1487. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/ (Python and JavaScript, from the files we listed), which the agent can run.

    Shell commands in SKILL.md call:

    • python

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Tech Debt Tracker loads about 1.9k tokens when it runs, and up to ~15k if it reads all its reference files. Until then it costs about 64 tokens; SKILL.md has 794 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~64
When it runs · the whole SKILL.md, loaded when a task matches
~1.9k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~15k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from borghei/Claude-Skills at commit c9a1487, republished under its MIT licence (© borghei). 794 words, ~1,945 tokens.

Download SKILL.mdSave it as .claude/skills/tech-debt-tracker/SKILL.md (or your agent's skills folder). This skill also uses 21 other files; get the full folder from GitHub.
name
tech-debt-tracker
description
Scan codebases for technical debt with AST parsing, prioritize by impact, and generate trend dashboards. Use when tracking tech debt, prioritizing refactoring, calculating cost-of- delay, planning sprint debt, or reporting debt to execs.
license
MIT + Commons Clause
metadata.version
1.1.0
metadata.author
borghei
metadata.category
engineering
metadata.domain
code-quality
metadata.tier
POWERFUL
metadata.updated
2026-06-17

Tech Debt Tracker

The agent identifies, scores, prioritizes, and tracks technical debt across codebases using AST parsing, cost-of-delay analysis, and trend dashboards.

Core Capabilities

  • Detection — AST parsing (Python) and regex pattern matching (all languages) across six debt categories: code, architecture, test, documentation, dependency, infrastructure.
  • Severity scoring — rate each item on velocity, quality, productivity, and business impact (1-10) plus effort sizing (XS-XL) and risk.
  • Cost-of-delay — compute interest rate (Impact x Frequency) and cost of delay (Interest x Sprints x Team Multiplier); also WSJF and RICE frameworks.
  • Prioritization — plot on the Cost-of-Delay vs Effort matrix (Immediate / Planned / Opportunistic / Backlog).
  • Sprint allocation — apply the Debt-to-Feature ratio by team velocity; reserve capacity for debt work.
  • Refactoring strategies — Strangler Fig, Branch by Abstraction, Feature Toggles, Parallel Run.
  • Reporting — executive and engineering dashboards, trend analysis, velocity tracking, and forecasts from scan snapshots.

When to Use

  • Tracking and quantifying technical debt across a repository.
  • Prioritizing refactoring work and calculating cost-of-delay.
  • Planning sprint capacity allocation between debt and features.
  • Reporting debt health, trends, and investment recommendations to execs.

Clarify First

Before scanning or reporting, confirm these inputs. If any is unknown or vague, ASK — do not assume:

  • Target codebase — the directory to scan (the subject of the debt inventory)
  • Prioritization framework & team size — cost-of-delay / WSJF / RICE and headcount (--framework, --team-size; changes the ranking and sprint allocation)
  • Report audience — exec dashboard vs engineering inventory (sets the report format and altitude)

Stop rule: ask only the 2-3 that most change the output. If the user says "just draft it," proceed and list your assumptions at the top of the artifact.

Tools

ToolPurposeCommand
debt_scanner.pyScan a directory for debt signals; output JSON inventory + text reportpython scripts/debt_scanner.py <dir> --output scan_results --format both
debt_prioritizer.pyEnrich inventory with cost-of-delay/WSJF/RICE and sprint allocationpython scripts/debt_prioritizer.py scan_results.json --framework wsjf --team-size 8
debt_dashboard.pyTrend analysis, velocity, forecasts, and exec summary across snapshotspython scripts/debt_dashboard.py --input-dir ./debt_scans/ --period quarterly

References

Load the reference that matches the task — keep this file lean and pull detail on demand:

  • references/methodology.md — the 7-step workflow, debt-classification table, severity scoring framework, interest-rate/cost-of-delay formulas, prioritization matrix, WSJF, sprint allocation ratios, the debt-item JSON schema, refactoring strategies, and quarterly planning. Read when scoring, prioritizing, or planning.
  • references/tool-reference.md — full parameter tables, examples, and output-format details for all three scripts plus the troubleshooting table. Read when running the scripts or debugging output.
  • references/dashboards-and-examples.md — executive and engineering dashboard layouts, a worked Python-microservice scan example, and the success-criteria bar. Read when generating reports or validating quality.
  • references/debt-classification-taxonomy.md — comprehensive taxonomy for classifying debt across dimensions with detection heuristics per category. Read when calibrating detection or labeling items.
  • references/prioritization-framework.md — deep prioritization approaches based on business value, risk, effort, and strategic alignment. Read when designing a prioritization rubric.
  • references/stakeholder-communication-templates.md — templates and guidelines for communicating debt status, impact, and recommendations to different stakeholder groups. Read when reporting to execs or product.

Also see the skill-root REFERENCE.md for the Technical Debt Quadrant (Fowler) and the implementation roadmap phases.

Show full SKILL.md (308 more words)Show less

Scope & Limitations

This skill covers:

  • Static detection of code-level, architecture, test, documentation, dependency, and infrastructure debt via AST parsing (Python) and regex pattern matching (all languages).
  • Quantitative prioritization of debt items using cost-of-delay, WSJF, and RICE frameworks with configurable team size and sprint capacity.
  • Historical trend analysis, health scoring, debt velocity tracking, and executive/engineering dashboard generation from multiple scan snapshots.
  • Sprint allocation planning with capacity-aware backlog scheduling and effort estimation by debt type.

This skill does NOT cover:

  • Runtime performance profiling or production monitoring -- see engineering/performance-profiler and engineering/observability-designer for those concerns.
  • Dependency vulnerability scanning (CVE detection) or software composition analysis -- see engineering/dependency-auditor for security-focused dependency review.
  • Automated refactoring or code transformation -- the skill identifies and prioritizes debt but does not modify source code.
  • Database schema debt, API contract drift, or infrastructure-as-code drift detection -- see engineering/database-schema-designer, engineering/api-design-reviewer, and engineering/migration-architect for those domains.

Integration Points

SkillIntegrationData Flow
engineering/dependency-auditorFeed dependency audit findings into the scanner as dependency_debt items to unify all debt in one inventory.Dependency audit JSON -> scanner config or manual merge into debt_inventory.json
engineering/performance-profilerCorrelate performance hotspots with high-complexity debt items to prioritize refactoring that yields both quality and speed gains.Profiler hotspot report -> cross-reference with scanner output by file path
engineering/ci-cd-pipeline-builderAdd debt_scanner.py as a CI pipeline step to fail builds when health score drops below a threshold or critical debt count increases.Scanner JSON output -> CI gate condition on summary.health_score
engineering/pr-review-expertSurface relevant debt items during code review by querying the debt inventory for files touched in a pull request.PR changed-files list -> filter debt_inventory.json by file_path
engineering/observability-designerMap infrastructure debt items (missing monitoring, env inconsistencies) to observability gaps identified by the observability skill.Dashboard category_distribution -> observability gap analysis
engineering/migration-architectUse the prioritized backlog to scope and sequence large-scale migration efforts, especially for architecture-category debt rated as planned initiatives.Prioritizer sprint_allocation -> migration planning timeline

© borghei, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 21 other files (scripts, references, assets) in engineering/tech-debt-tracker of borghei/Claude-Skills.

  • SKILL.md
  • README.md
  • REFERENCE.md
  • assets/historical_debt_2024-01-15.json
  • assets/historical_debt_2024-02-01.json
  • assets/sample_codebase/src/frontend.js
  • assets/sample_codebase/src/payment_processor.py
  • assets/sample_codebase/src/user_service.py
  • assets/sample_debt_inventory.json
  • expected_outputs/sample_dashboard_output.json
  • expected_outputs/sample_prioritization_output.json
  • expected_outputs/sample_scan_output.json
  • references/dashboards-and-examples.md
  • references/debt-classification-taxonomy.md
  • references/methodology.md
  • references/prioritization-framework.md
  • … and 6 more

Open the folder on GitHubat commit c9a1487

Compare with similar skills

Tech Debt Tracker next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

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Tech Debt Tracker this skillborghei/Claude-Skills874—~1.9kAutomated safety check: PassMIT
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Code Simplification for ego-litecitrolabs/ego-lite17k—~1.2kAutomated safety check: PassMIT
Code Refactoring Workflowluongnv89/claude-howto42k—~3.1kAutomated safety check: PassMIT
Cto AdvisorIbrahim-3d/orchestrator-supaconductor3804 repos~2.4kAutomated safety check: PassMIT
Tech Debt Analyzerailabs-393/ai-labs-claude-skills4542 repos~3.9kAutomated safety check: PassMIT

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Categories

Questions about Tech Debt Tracker

What does Tech Debt Tracker do?

Scan codebases for technical debt with AST parsing, prioritize by impact, and generate trend dashboards. Tech Debt Tracker is an agent skill from borghei/Claude-Skills. Scan codebases for technical debt with AST parsing, prioritize by impact, and generate trend dashboards.

When should I use Tech Debt Tracker?

Tech Debt Tracker fits situations like: tracking tech debt; prioritizing refactoring; calculating cost-of- delay; planning sprint debt.

How do I install Tech Debt Tracker in Claude Code?

Run `npx skills add borghei/Claude-Skills --skill tech-debt-tracker -a claude-code`. Or copy the skill folder (engineering/tech-debt-tracker in borghei/Claude-Skills) into .claude/skills/tech-debt-tracker in your project. Claude Code loads it when a task matches its description.

How do I install Tech Debt Tracker in Codex?

Run `npx skills add borghei/Claude-Skills --skill tech-debt-tracker -a codex`. Or copy the skill folder (engineering/tech-debt-tracker in borghei/Claude-Skills) into .agents/skills/tech-debt-tracker in your project. Codex loads it when a task matches its description.

Can I use Tech Debt Tracker in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add borghei/Claude-Skills --skill tech-debt-tracker -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/tech-debt-tracker, .gemini/skills/tech-debt-tracker, .github/skills/tech-debt-tracker and .opencode/skills/tech-debt-tracker in your project.

What does Tech Debt Tracker need to run?

Going by SKILL.md and its folder, Tech Debt Tracker needs Python and JavaScript for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3; Node.js.

Does Tech Debt Tracker access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Tech Debt Tracker safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Tech Debt Tracker use?

Tech Debt Tracker is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Tech Debt Tracker use?

About 1.9k tokens (SKILL.md is roughly 7.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 13k tokens, read only when the agent opens those files.

What are the alternatives to Tech Debt Tracker?

Skills that share tags, products or a category with Tech Debt Tracker: Systematic Code Refactoring (luongnv89/claude-howto, 42k stars), Code Simplification for ego-lite (citrolabs/ego-lite, 17k stars), Code Refactoring Workflow (luongnv89/claude-howto, 42k stars) and Cto Advisor (Ibrahim-3d/orchestrator-supaconductor, 380 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Tech Debt Tracker?

borghei (a GitHub user) maintains it in borghei/Claude-Skills, which has 874 GitHub stars. The repository holds 364 skills in this directory. The repository was last updated on October 7, 2026.

Source: borghei/Claude-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.