tech-debt-tracker

Productivity

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.

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Source SKILL.md: https://github.com/borghei/Claude-Skills/blob/HEAD/engineering/tech-debt-tracker/SKILL.md

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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

Tool	Purpose	Command
`debt_scanner.py`	Scan a directory for debt signals; output JSON inventory + text report	`python scripts/debt_scanner.py <dir> --output scan_results --format both`
`debt_prioritizer.py`	Enrich inventory with cost-of-delay/WSJF/RICE and sprint allocation	`python scripts/debt_prioritizer.py scan_results.json --framework wsjf --team-size 8`
`debt_dashboard.py`	Trend analysis, velocity, forecasts, and exec summary across snapshots	`python 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.

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

Skill	Integration	Data Flow
`engineering/dependency-auditor`	Feed 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-profiler`	Correlate 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-builder`	Add `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-expert`	Surface 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-designer`	Map infrastructure debt items (missing monitoring, env inconsistencies) to observability gaps identified by the observability skill.	Dashboard `category_distribution` -> observability gap analysis
`engineering/migration-architect`	Use 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