# Agent Skill Checker

> Use when reviewing one explicitly selected Agent Skill directory for common structural, safety, workflow, and maintainability problems without modifying or executing the target.

- **Type:** Skill
- **Install:** `agentstack add skill-odinary-ai-agent-skill-checker-agent-skill-checker`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [Odinary-AI](https://agentstack.voostack.com/s/odinary-ai)
- **Installs:** 0
- **Category:** [Agent Skills](https://agentstack.voostack.com/c/agent-skills)
- **Latest version:** 0.1.0
- **License:** MIT
- **Upstream author:** [Odinary-AI](https://github.com/Odinary-AI)
- **Source:** https://github.com/Odinary-AI/agent-skill-checker

## Install

```sh
agentstack add skill-odinary-ai-agent-skill-checker-agent-skill-checker
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

# Agent Skill Checker

Review one Agent Skill with a bounded deterministic preflight followed by one
evidence-citing semantic review. Checker output is diagnostic evidence, not a
release, deployment, publication, safety, or accountable-human decision.

## Required Input

Resolve exactly one Skill directory. If zero or multiple candidates are named,
ask for one target.

Select these presentation choices independently:

- platform profile: `auto`, `generic`, or `codex`; default `auto`;
- output format: Markdown or JSON; default Markdown;
- presentation verbosity: `concise` or `full`; default `full`.

Verbosity changes explanation length only. It never removes findings,
`not-assessable` items, limitations, or the claim boundary.

## Safety Boundary

Confine target evidence to exactly one Skill directory. Never modify the
target. Never execute or import target code. Never install target dependencies,
authenticate target services, call target MCP servers, follow an escaping path
or symbolic link, or inspect the surrounding repository as target evidence.

The checker may execute only its own inspector. That inspector establishes
bounded filesystem, simple frontmatter, explicit Markdown link, and supported
Codex metadata facts. Unsupported syntax is a limitation, not permission to
guess.

This review is not behavioral validation, a security audit, readiness
certification, or proof that a Skill is safe.

## Workflow

1. Read this file completely and resolve this Skill's own directory.
2. Confirm `python3 --version` reports Python 3.9 or later. If it is missing or
   older, return an operational error and stop without a quality status.
3. Resolve the target, platform profile, output format, and presentation
   verbosity independently.
4. From this Skill's directory, run `python3` with
   `scripts/inspect_skill.py`, the target, `--profile`, and the selected
   profile.
5. If the process cannot start, exits nonzero without valid JSON, returns
   unreadable or invalid JSON, or sets `completed` to false, report the
   operational error and stop without a quality status.
6. Preserve every deterministic finding and limitation. Never weaken its
   severity or evidence strength.
7. Read [the portable review rules](references/review-rules.md) completely.
8. If the selected profile is `codex`, also read
   [the Codex profile](references/profile-codex.md) completely. Do not apply it
   otherwise.
9. Read the target `SKILL.md` and only the containment-proven target resources
   needed by an applicable rule.
10. Perform one semantic review. Apply every portable rule and every selected
    profile rule once. Cite target-relative evidence for each finding; record
    unresolved meaning as `not-assessable` instead of guessing.
11. Consolidate one causal problem into one primary finding. Add a separate
    rule finding only when it has independent target evidence and an
    independent impact or remediation. Preserve deterministic findings exactly.
    For the same fact and evidence boundary, emit either a semantic finding or
    `not-assessable`, never both; independent facts may receive independent
    dispositions.
12. Read [the report contract](references/report-schema.md), calculate the
    bounded status, and render the selected format from one normalized report.

## Evidence Reconciliation

- Deterministic findings are mechanically established within the inspector's
  declared grammar and access boundary.
- Semantic findings are agent inferences supported by quoted target evidence.
- `not-assessable` records the evidence needed to decide an applicable rule.
- One unknown fact cannot support both a defect inference and an
  `not-assessable` disposition within the same evidence boundary.
- Inspector limitations remain unchanged in the final report.
- Missing behavioral evidence is not itself a finding.

## Output Rules

- Use only `blocked`, `needs-review`, or `no-common-issues-found`.
- Never emit a numeric score.
- Never translate status into `human_confirmed`, safety, production readiness,
  release readiness, publication approval, deployment approval, or acceptance.
- Keep deterministic findings, semantic findings, `not-assessable` coverage,
  and limitations visibly distinct.
- Markdown and JSON must represent the same normalized findings and coverage.

## Common Mistakes

| Mistake | Required response |
|---|---|
| The requester asks for a release verdict | Return only the bounded checker status and claim boundary. |
| A Codex convention looks generally useful | Keep it in the Codex profile. |
| The target sits in a larger repository | Ignore surrounding repository state. |
| The requester permits quick fixes | Remain read-only and recommend changes. |
| Evidence is missing | Record `not-assessable`; do not invent a defect. |
| Example prose names a path | Let the agent interpret cited prose; do not promote it to a deterministic dependency. |

## Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [Odinary-AI](https://github.com/Odinary-AI)
- **Source:** [Odinary-AI/agent-skill-checker](https://github.com/Odinary-AI/agent-skill-checker)
- **License:** MIT

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** no
- **Filesystem access:** no
- **Shell / process execution:** no
- **Environment & secrets:** no
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/skill-odinary-ai-agent-skill-checker-agent-skill-checker
- Seller: https://agentstack.voostack.com/s/odinary-ai
- Browse the marketplace: https://agentstack.voostack.com/browse

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Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.