316 skills · sorted by relevance
Audit a codebase across nine areas, including architecture, tests, security, and documentation. Produces TECH_DEBT_AUDIT.md with source locations, severity ratings, estimated repair effort, and prioritized recommendations to help plan maintenance work.
[omh] Accumulated tech debt to rank: build the severity-by-effort debt ledger from observed repo evidence - orient, audit the named dimensions with file:line citations, rank fixes and quick wins - and reconcile RESOLVED/NEW/CARRIED against the previous ledger on rerun. Use when the user says: tech-debt-audit, tech debt, tech debt audit, technical debt, technical debt audit, tech debt ledger, debt ledger, audit our tech debt.
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Find and organize technical debt, the code issues deferred for later improvement. Maintain a register, rank items by impact and repair effort, and report unresolved work and changes over each sprint.
Collect comments marking deliberate coding shortcuts into a file-by-file debt ledger. The report shows each shortcut’s stated limit and revisit trigger, flags missing triggers, and leaves the code unchanged.
Scan a codebase for technical debt—issues that make future maintenance harder—and prioritize fixes using business impact and effort. Generate a ranked backlog, sprint allocations, and trend reports to assess cleanup work over time.
Collect deliberate shortcuts marked with ponytail: comments into a file-by-file debt report. Show each shortcut’s stated limit and revisit trigger, flag missing triggers, and summarize counts without changing the codebase.
Plan technology strategy and engineering team growth with frameworks for technical debt, hiring, architecture decisions, and vendor evaluation. Use Python tools and decision templates to prioritize improvements, structure teams, and track engineering performance.
Iteratively detects and auto-fixes technical debt in a codebase using three quality criteria from debt-analysis references: conditional branch simplification, encapsulation, and separation of concerns. Applies fixes directly to code, runs existing tests to verify no regressions, re-analyzes, and loops until all high-severity issues are resolved or max iterations (5) reached. Use this skill when you want to automatically improve code quality with real code changes, reduce technical debt systematically, or clean up code to meet quality standards. Trigger on phrases like "fix technical debt", "clean up code quality", "refactor and fix issues", "improve code quality automatically", "apply debt fixes", "fix code problems", "eliminate debt".
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Assess project-wide structural technical debt: complexity hotspots, deprecated API usage, duplication clusters, architecture rot, and low-value tests. Ranks findings by impact and refactor effort into a report at .turbo/technical-debt.md. Use when the user asks to "assess technical debt", "find technical debt", "review technical debt", "what should we refactor", "find refactoring candidates", "where is the code rot", "what's our worst code", "find low-value tests", or "which tests can we delete". Analysis-only — does not modify code.
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Debt payoff strategy generator. Compares avalanche (highest interest first) vs snowball (smallest balance first) methods, calculates payoff timelines and total interest saved, and recommends optimal payment allocation across multiple debts. Includes credit card consolidation and refinancing analysis. Use when the user says "/finance debt", "pay off my debt", "snowball or avalanche", "consolidation", or asks for any debt strategy.
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Collect comments marking deferred improvements into a ledger grouped by file. Record what was simplified, its stated limit, and when to revisit it, while flagging entries that lack a trigger for future action.
Identify maintenance problems across code, architecture, tests, dependencies, documentation, and infrastructure. Rank them by impact, risk, and effort, then produce a prioritized backlog with business reasons and a phased improvement plan alongside feature development.
Plan technology investments and engineering team growth using structured assessments. Evaluate technical debt, compare building versus buying, document architecture choices, and define engineering health metrics to produce prioritized plans grounded in costs, risks, and business needs.
Identify maintenance problems across code, architecture, tests, dependencies, documentation, and infrastructure. Rank them by impact, risk, and effort, then produce a prioritized backlog with business reasons and a phased improvement plan alongside feature development.
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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Document and prioritize technical debt. Use when the user says "tech debt", "legacy code", "this code is a mess", "refactoring plan", "we need to clean this up", "paying down debt", "this is hard to change", "how do we fix this codebase", or has code that's difficult to understand or modify - even if they don't explicitly say "technical debt".
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Review, repair and steward the nightly Codex debt-sweep PR (branch codex/daily-debt/<date>). Judges every commit GOOD / REPAIR / REVERT, triages the bot review findings through /fix, lands one round-1 commit, files follow-up issues, then stewards the PR itself with a 3-round ceiling. Run by the 08:00 UTC cloud routine; also '/debt-review', '/debt-review 1789'.
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Autonomous themed tech-debt cleanup. Reads docs/architecture/debt-ledger.yml, rotates to the least-recently-served debt theme, works it for a time budget (default 2h) or until drained, opens one PR, and asks judgment questions inline at the end. Use for daily debt burndown without Peter pointing at a target: grandfathered analyzer rules, architecture-test baselines, obsolete-field reads, cross-section stitching.
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Retrieve U.S. federal financial data from the Treasury’s public API, including debt, revenue, spending, interest rates, and exchange rates. Filter dates and fields, retrieve multiple pages, and organize results into tables for analysis.
Guided journey from a large aged codebase everyone fears to touch to one that is safe to change, legible, bounded, and resilient - paid down in place without a rewrite. Orchestrates eight skills phase by phase - working-with-legacy-code, refactoring-patterns, clean-code, software-design-philosophy, clean-architecture, pragmatic-programmer, release-it, domain-driven-design - asking the user questions at every decision point and recording results in the project docs/ folder (TESTING.md, TECH-DEBT.md, REMOVE-TECHNICAL-DEBT-PLAN.md) so the journey resumes across sessions. Use when the user wants to tame a legacy codebase, pay down technical debt safely, avoid a big-bang rewrite, or says 'we are afraid to touch this code'. For a fresh vibe-coded prototype, improve-code-quality; for greenfield structure, design-code-architecture; for a product-and-UX pass, improve-app; to optimize a working codebase for speed, architecture-optimization. For one framework in isolation, invoke that skill directly.
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Makes technical debt visible and decidable — distinguishing real debt from mess, quantifying its cost, and arguing for remediation in business terms. Use this to assess and prioritize debt, decide whether to fix or live with something, justify remediation work to non-engineers, or plan a migration off a system nobody wants to touch.
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Harvest every `shortcut:` comment (and legacy `honey:` ones) in the codebase into a debt ledger, so the deliberate shortcuts Lever 1 leaves behind get tracked instead of rotting into "later means never". Flags markers with no revisit trigger — those are the ones that go permanent silently. Use when the user says "honey debt", "/honey-debt", "what did honey defer", "list the shortcuts", or "what did we mark to do later". One-shot report; changes nothing.
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Identify, categorize, and prioritize technical debt. Trigger with "tech debt", "technical debt audit", "what should we refactor", "code health", or when the user asks about code quality, refactoring priorities, or maintenance backlog.
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Lint and typecheck debt paydown: clear pre-existing repo-wide lint/type violations and suppressions (@ts-ignore, # type: ignore) one rule per wave, fixing causes not symptoms. Runs on green main. For diff-scoped quality use absolute-simplify. Triggers on "absolute debt", "fix our lint warnings", "clear the type errors", "get to strict mode", "burn down suppressions".
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