agentleFS
martinholovskymartinholovsky/SOTA-skills/skills/sota-skill-security/SKILL.md

sota-skill-security

Skill27 starsChanged 2 months agoCC-BY-4.0View on GitHub

Security for AI agent skills, plugins and instruction bundles (2026) — the supply chain of things that tell an agent what to do. Use when installing, authoring, reviewing, updating or auditing any skill, plugin, ruleset or agent file an agent loads as instructions, including your own; when a repository you do not fully trust contains agent-readable instruction files; and when deciding what an installed skill may reach. Covers provenance and pinning, review-before-install, the instruction trust boundary, precedence and shadowing between overlapping skills, capability minimisation, revocation, and auditing a skill for guidance that is confidently wrong. Not for prompt injection arriving in ordinary application data — use sota-code-security rules/08. Trigger keywords: skill, agent skill, SKILL.md, AGENTS.md, CLAUDE.md, .cursorrules, instruction file, plugin, marketplace, skill install, skill provenance, skill pinning, malicious skill, skill shadowing, agent trust boundary.

The file

We split this skill into the rules it gives an agent

6 rules. About 0 are common, 2 are distinctive, and 4 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈2

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 4

    Very specific

    Tied to their project's names, files or tools. Probably skip.

Licensed with conditions — read it at the source. We count its rules but don't quote them. Read them on GitHub.

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.