Tech Debt Tracker

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

References