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.
npx skills add sethdford/claude-skills --skill tech-debt-assessmentgit clone --depth 1 https://github.com/sethdford/claude-skillsWrote 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.
[](https://agentmods.dev/skills/sethdford/claude-skills/tech-debt-assessment)<a href="https://agentmods.dev/skills/sethdford/claude-skills/tech-debt-assessment"><img src="https://agentmods.dev/badge/skills/sethdford/claude-skills/tech-debt-assessment/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.
<a href="https://agentmods.dev/skills/sethdford/claude-skills/tech-debt-assessment"><img src="https://agentmods.dev/badge/skills/sethdford/claude-skills/tech-debt-assessment.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00038 | $0.00667 |
| Opus 5 | $0.00019 | $0.00333 |
| Sonnet 5 | $0.00008 | $0.00133 |
| Haiku 4.5 | $0.00004 | $0.00067 |
Grade A, and why
tech-debt-assessment 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.
How it starts
The opening of the file, as written. The whole thing — 47 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Tech Debt Assessment
Systematically measure technical debt, prioritize paydown, and track progress.
Context
You are assessing technical debt in the system. Quantify impact (velocity reduction, risk increase), estimate effort to fix, prioritize based on ROI. Read code, metrics, team feedback.
Domain Context
Based on technical debt frameworks (Steve McConnell, Martin Fowler):
- Types of Debt: Deliberate (knowingly cut corners for speed), accidental (poor design decisions), negligent (avoidable bad practices)
- Impact: Slows feature delivery (velocity decrease), increases bugs (quality risk), complicates future changes
- Interest Payments: Cost to maintain bad code; time spent working around it; bugs from complexity
- Paydown: Refactoring, rewriting, deprecating; costs time/resources upfront but reduces future interest
Instructions
-
Catalog Debt Items: Interview team: "What slows us down?" Common themes: hard-to-test code, tangled dependencies, missing documentation, outdated libraries.
-
Quantify Impact: For each debt item, how much does it slow velocity? Example: "Test coverage < 30% makes refactoring 3x slower". Measure days/quarter lost to debt.
-
Estimate Paydown Effort: How long to fix? Refactor module: 2 weeks. Rewrite component: 1 month. Replace library: 3 days. Be realistic; add 50% buffer.
-
Calculate ROI: Paydown cost vs interest savings. Refactor for 2 weeks (80 hours) to save 5 hours/quarter in reduced bugs and faster changes. Payoff: ~16 quarters (4 years).
-
Prioritize: High impact + low effort = do first. High impact + high effort = plan for next quarter. Low impact = defer or accept. Build paydown roadmap: 20% of sprint capacity for debt.
Anti-Patterns
- Debt Without Metrics: "Our code is messy" without quantifying impact. Result: hard to justify paydown. Guard: Quantify slowness; track velocity impact.
- Paydown Without Benefit: Refactor for refactoring's sake. Result: effort spent, velocity unchanged. Guard: Only pay down debt with measurable benefit (fewer bugs, faster changes).
- Ignoring Debt Accumulation: Always add features, never refactor. Result: exponential slowdown. Guard: Allocate 20% of capacity for debt; enforce discipline.
- Wrong Prioritization: Pay down low-impact debt first. Result: effort wasted, high-impact debt still blocking. Guard: Prioritize by impact × frequency, not just preference.
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.
- 11d ago First seen · 47 lines · 38 tokens per session scan A 668e0008a70c
tech-debt-assessment is a skill published in the GitHub repository sethdford/claude-skills (40 stars, last pushed 6mo ago), licensed MIT. It adds 38 tokens to every session and 667 once invoked, about $0.0002 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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