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 joao-aires/agent-skills-public --skill supply-chain-risk-auditorgit clone --depth 1 https://github.com/joao-aires/agent-skills-publicWrote 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/joao-aires/agent-skills-public/supply-chain-risk-auditor)<a href="https://agentmods.dev/skills/joao-aires/agent-skills-public/supply-chain-risk-auditor"><img src="https://agentmods.dev/badge/skills/joao-aires/agent-skills-public/supply-chain-risk-auditor/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/joao-aires/agent-skills-public/supply-chain-risk-auditor"><img src="https://agentmods.dev/badge/skills/joao-aires/agent-skills-public/supply-chain-risk-auditor.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 | $0.00074 | $0.01564 |
| Opus 5.5 | $0.00030 | $0.00626 |
| Sonnet 5.5 | $0.00015 | $0.00313 |
| Haiku 4.5 | $0.00007 | $0.00156 |
Grade A, and why
supply-chain-risk-auditor 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 yesterday.
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.
Copies of this mod
1 near-identical copy found in the catalogue:
- supply-chain-risk-auditor — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 123 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Supply Chain Risk Auditor
Generates a supply-chain risk report for a project's direct dependencies (npm, PyPI, Go), plus an advisory sweep of everything its lockfile resolves. Two deterministic scripts do the measuring; your job is the judgment they refuse to automate.
Why the scripts do the measuring, not you
Every figure in this report is a claim about somebody else's project, and hand-collected
figures were measured wrong before this skill was rebuilt around scripts: GitHub
contributor counts said five-plus people maintain lodash where npm's ACL says one, and
gh saw zero downloads for a package that moves 164 million a week. Do not estimate
maintainer counts, downloads, staleness, or CVE history from gh, web search, or
memory — run the collector, and quote what it measured.
The scripts enforce two rules worth knowing before you read their output:
- Unavailable data is never evidence of risk. Every criterion resolves to assessed-clean, assessed-flagged, or unassessable-with-a-reason.
- An absent measurement is never a clean verdict. A run that measured nothing exits non-zero instead of printing a report that finds nothing.
Workflow
- Confirm the target directory has manifests:
package.json,pyproject.toml,requirements*.txt, orgo.mod. If none exist, say so and stop — do not audit an ecosystem this collector does not parse by hand. Lockfiles read for exact versions and the transitive sweep:package-lock.json/npm-shrinkwrap.json,uv.lock, and a go 1.17+go.mod.yarn.lock,pnpm-lock.yaml, andpoetry.lockare not read — the report says so when they are present, and versions fall back to pins or the latest release. - Check
gh auth status. Unauthenticated GitHub allows 60 requests/hour against 5,000, and the collector makes several per dependency; expect repository criteria to come back unassessable without it. Say so rather than fixing it silently. - Collect, then render. Put outputs somewhere outside the audited repository unless asked otherwise:
What ships with it
13 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.
- agents/openai.yaml 252 B
- assets/trail-of-bits-mark.svg 3.0 KB
- scripts/collect.py 64 KB runs code
- scripts/model.py 17 KB runs code
- scripts/pyproject.toml 683 B
- scripts/render.py 34 KB runs code
- scripts/sources.py 29 KB runs code
- scripts/test_collect.py 37 KB runs code
- scripts/test_model.py 7.7 KB runs code
- scripts/test_render.py 14 KB runs code
- scripts/test_sources.py 10 KB runs code
- scripts/uv.lock 337 B
- UPSTREAM-LICENSE.txt 20 KB
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.
- yesterday First seen · 123 lines · 74 tokens per session scan A a1254b7f8d3a
supply-chain-risk-auditor is a skill published in the GitHub repository joao-aires/agent-skills-public (2 stars, last pushed yesterday), licensed MIT. It adds 74 tokens to every session and 1,564 once invoked, about $0.0003 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 2026-10-21.
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