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/agent-use

@3323bc9
by Tristan Manchestertristanmanchester/agent-skills3 stars
2
Run it yourself

Audit or design agent-facing product capabilities: action/context parity, discoverable contracts, safe mutations, verifiable outcomes, and recovery. Use for explicit agent-readiness reviews of apps, repos, CLIs, APIs, MCP/A2A integrations, or Agent Skills; not every general code or documentation task.

Use this Skill: https://skilld.dev/gh/tristanmanchester/agent-skills/agent-use

Nothing lands on disk. Nothing to clean up.

Fork this Skill

Edit a local copy. It keeps the author and licence.

AGENTS.md

≈378 tokens on demand. Your agent reads this file only when SKILL.md points to it.

Maintaining agent-use

Read SKILL.md and the reference for the surface being changed. Preserve the capability/parity audit method and existing MIT licence. Prefer a focused fix to a new general framework or another copy of an upstream protocol catalogue.

Run from this skill directory with Python 3.10+ and PyYAML >=6.0.3,<7:

python scripts/validate_agent_assets.py --skill-dir .
python -m unittest discover -s tests -v
python scripts/test_agent_use_scanners.py

The validator reads YAML/JSON/Python/Markdown; it never runs inspected scripts or writes bytecode. Test execution is separate and must be authorised for the code under review. Network probes, generated files, installations, and output writes are not passive reads. Use explicit target/output paths and do not replace an existing project's instructions as an audit side effect.

The generator previews selected surfaces and writes only to a new draft directory with --write. Do not restore universal .well-known claims or broad --force/default-all behaviour. Validate the actual current A2A/MCP/API schema and runtime when making protocol claims; local fixture checks establish only their stated subset.

Files in examples are historical heuristic scanner outputs unless explicitly regenerated. Their scores are not present-day release evidence. Keep new regression tests, supported command examples, source links/review dates, and runtime limitations aligned. Use caller-provided installation paths; never embed a user's home path.

Source: SKILL.md on GitHub

Skill behaviors

skilld matched fixed text patterns in SKILL.md and file names. Patterns miss obfuscated code.

skilld run checks every file with the same patterns. It asks for approval before it loads a Skill with a behavior marked Needs approval.

Third-party checks

1 warning1mo3 checks · Risk SAFE
  • Gen Agent Trust Hub1mo

    The skill 'agent-use' is a comprehensive toolkit for auditing and designing agent-ready systems. It includes documentation, templates, and Python scripts for scanning repositories and websites. Security analysis found no malicious intent; identified network and command execution patterns are aligned with the skill's primary purpose as an auditing tool.

  • Socket1mo

    1 alert: gptAnomaly

  • Snyk1mo

    Risk: LOW · No issues

Provenance

Signed by skilld at 3323bc9. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

Last checked against GitHub 2 weeks ago.

Steadyupdated last month

Capability

metadata
{
  "version": "3.0.0",
  "reviewed": "2026-09-13"
}
Other metadata
compatibility
Local helper scripts require Python 3.10+; structural validation also requires PyYAML 6.0.3 or later in major 6. Network and execution checks need separately authorised tools and environments.

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