Borrowing it
Nothing to install: this file belongs to HatmanStack/RAGStack-Lambda. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/HatmanStack/RAGStack-Lambda/main/.claude/skills/repo-health/SKILL.mdgit clone --depth 1 https://github.com/HatmanStack/RAGStack-LambdaWrote 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/hatmanstack/ragstack-lambda/repo-health)<a href="https://agentmods.dev/skills/hatmanstack/ragstack-lambda/repo-health"><img src="https://agentmods.dev/badge/skills/hatmanstack/ragstack-lambda/repo-health/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/hatmanstack/ragstack-lambda/repo-health"><img src="https://agentmods.dev/badge/skills/hatmanstack/ragstack-lambda/repo-health.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00034 | $0.01430 |
| Opus 5.5 | $0.00014 | $0.00572 |
| Sonnet 5.5 | $0.00007 | $0.00286 |
| Haiku 4.5 | $0.00003 | $0.00143 |
Grade A, and why
repo-health 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 2mo 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 — 176 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Repo Health Audit
You coordinate a technical debt audit of a codebase. The auditor runs as a separate agent with its own context window.
Input
$ARGUMENTS is optional context — the repo path, specific concerns, or scope constraints. If empty, audit the current working directory.
Process
Step 1: Scope the Audit
Ask scoping questions one at a time, preferring multiple choice. Wait for each answer before asking the next.
The health audit scans for technical debt across 4 vectors: architectural, structural, operational, and code hygiene. Findings are prioritized by severity (CRITICAL > HIGH > MEDIUM > LOW). The pipeline remediates until all CRITICAL and HIGH findings are resolved.
Question 1 — Known pain points give the auditor a starting hypothesis instead of scanning cold:
Are there parts of the codebase you already know are problematic?
Things that keep breaking, areas you dread touching, modules that slow down every PR.
A) Yes (tell me which areas and what's wrong)
B) No — scan everything with fresh eyes
Question 2 — Goal determines which debt vectors the auditor emphasizes:
What's the primary goal for this audit?
A) General health check — scan all 4 vectors equally
B) Production hardening — emphasize operational debt (error handling, timeouts, resource leaks, observability)
C) Onboarding prep — emphasize structural and hygiene debt (naming, dead code, documentation, test coverage)
D) Pre-release cleanup — focus on CRITICAL/HIGH items only, skip MEDIUM/LOW
Question 3 — Deployment target changes what "operational debt" means. A Lambda function has different concerns than a long-running container:
What's the deployment target?
A) Serverless (Lambda, Cloud Functions) — cold starts, execution limits, stateless constraints
B) Containers (ECS, Kubernetes, Docker) — resource management, health checks, graceful shutdown
C) Static hosting / SPA — build pipeline, CDN, client-side concerns
D) Monolith / traditional server — process management, connection pooling, memory leaks
E) Multiple (tell me which)
F) Not deployed yet / unsure
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.
- 2mo ago First seen · 176 lines · 34 tokens per session scan A e37fe66e9695
repo-health is a skill published in the GitHub repository HatmanStack/RAGStack-Lambda (25 stars, last pushed yesterday), licensed Apache-2.0. It adds 34 tokens to every session and 1,430 once invoked, about $0.0001 per session on Opus 5.5. 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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