Borrowing it
Nothing to install: this file belongs to hoangsonww/PetSwipe-Match-App. 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/hoangsonww/PetSwipe-Match-App/master/.agents/skills/deployment-claims-audit/SKILL.mdgit clone --depth 1 https://github.com/hoangsonww/PetSwipe-Match-AppWrote 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/hoangsonww/petswipe-match-app/deployment-claims-audit)<a href="https://agentmods.dev/skills/hoangsonww/petswipe-match-app/deployment-claims-audit"><img src="https://agentmods.dev/badge/skills/hoangsonww/petswipe-match-app/deployment-claims-audit/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/hoangsonww/petswipe-match-app/deployment-claims-audit"><img src="https://agentmods.dev/badge/skills/hoangsonww/petswipe-match-app/deployment-claims-audit.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 | $0.00048 | $0.00209 |
| Opus 5 | $0.00024 | $0.00105 |
| Sonnet 5 | $0.00010 | $0.00042 |
| Haiku 4.5 | $0.00005 | $0.00021 |
Grade A, and why
deployment-claims-audit 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.
What it actually says
Use this skill when a task involves strong readiness or deployability claims.
Workflow
- Gather repo evidence first: manifests, scripts, preflight checks, docs, and operator templates.
- Separate repo-side capability from environment-side prerequisites.
- Remove or qualify claims that the repo does not yet support end to end.
- Prefer exact blockers over vague caution language.
- Update all affected docs consistently.
PetSwipe Guidance
- This repo has strong deployment artifacts, but still depends on real operator inputs for full deployment.
- Distinguish "renderable and preflighted" from "fully deployable in a real environment."
- Strong language like "enterprise-grade" should only appear with matching evidence.
Read references/readiness-rubric.md.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 23 lines · 48 tokens per session scan A 9579c4b4d1b6
deployment-claims-audit is a skill published in the GitHub repository hoangsonww/PetSwipe-Match-App (26 stars, last pushed 3d ago), licensed MIT. It adds 48 tokens to every session and 209 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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