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 UnboundCompute/security-agent-skills --skill vetting-skills-before-installgit clone --depth 1 https://github.com/UnboundCompute/security-agent-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/unboundcompute/security-agent-skills/vetting-skills-before-install)<a href="https://agentmods.dev/skills/unboundcompute/security-agent-skills/vetting-skills-before-install"><img src="https://agentmods.dev/badge/skills/unboundcompute/security-agent-skills/vetting-skills-before-install/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/unboundcompute/security-agent-skills/vetting-skills-before-install"><img src="https://agentmods.dev/badge/skills/unboundcompute/security-agent-skills/vetting-skills-before-install.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 | $0.00151 | $0.01664 |
| Opus 5.5 | $0.00060 | $0.00666 |
| Sonnet 5.5 | $0.00030 | $0.00333 |
| Haiku 4.5 | $0.00015 | $0.00166 |
Grade A, and why
vetting-skills-before-install 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 1mo 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 — 133 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Vetting skills before install: decide install, constrain, or deny with evidence
Installing a skill or an MCP server hands untrusted instructions and untrusted code to an agent that acts on your behalf. Popularity and a clean README are not a review. This is the checklist that turns "it looks fine" into a verdict backed by evidence: what the artifact tells the model, what it is allowed to do, and what its code actually does on install and at runtime. It composes three audits and adds the code inspection that ties them together.
When to use
- You are about to add a third-party skill, MCP server, or marketplace entry.
- You are re-reviewing an artifact after an update changed its code or manifest.
- You need a defensible install decision, not a gut call.
Scope check
Vet artifacts you intend to run on your own agent, in a contained environment. Inspect bundled code statically before executing anything. If you can't name the authorization, stop.
The loop
-
Pin the exact artifact. Record the source, the author, and the precise version or content hash. You vet one frozen artifact, not "the skill": a later version is a new review. Everything below refers to this pinned state, so an auto-update that replaces it voids the verdict.
-
Audit the instruction surface. Run the instruction-text lint over every field the model reads: hidden or invisible text, override and role-spoofing phrases, concealment directives, and instructions that steer the agent to exfiltrate. A planted instruction here is a deny on its own.
-
Diff declared versus used permissions. Compare what the artifact requests against what its code exercises, both directions: over-broad grants it never uses, and capabilities it uses without declaring. An undeclared network or process reach is a deny; an over-grant is at least a constraint.
-
Inspect the bundled code for exfiltration. Trace whether it reads sensitive material (environment variables, credential files, dotfiles, private keys) into a flow that leaves the machine: a network call, an outbound tool, or embedding the data in output. A read that reaches an egress sink is the exfil finding; trace the flow rather than grepping for either end alone.
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.
- 1mo ago First seen · 133 lines · 151 tokens per session scan A 9cc3166c70d6
vetting-skills-before-install is a skill published in the GitHub repository UnboundCompute/security-agent-skills (5 stars, last pushed 1mo ago), licensed MIT. It adds 151 tokens to every session and 1,664 once invoked, about $0.0006 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 2026-09-05.
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