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 AtlasOmnia/donna-starter --skill skill-auditorgit clone --depth 1 https://github.com/AtlasOmnia/donna-starterWrote 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/atlasomnia/donna-starter/skill-auditor)<a href="https://agentmods.dev/skills/atlasomnia/donna-starter/skill-auditor"><img src="https://agentmods.dev/badge/skills/atlasomnia/donna-starter/skill-auditor.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 3 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Rogue Agent · line 28 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
- medium Excessive Agency · line 101 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
- medium Excessive Agency · line 203 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00064 | $0.03399 |
| Opus 5 | $0.00032 | $0.01699 |
| Sonnet 5 | $0.00013 | $0.00680 |
| Haiku 4.5 | $0.00006 | $0.00340 |
Grade A, and why
skill-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 8d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- skill-auditor — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 270 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill Auditor — Quality Grading System (A–F)
Audit any Hermes skill file and assign a quality grade based on clarity, completeness, tool guidance, and shareability. Returns specific fix suggestions ranked by impact.
When to Use
- User asks you to review, audit, or grade a skill
- You're about to create a new skill and want to validate the draft
- A skill is behaving unreliably (agent skips it, calls wrong tools, misses steps)
- User shares a skill file or path for feedback
- You're preparing skills for sharing with others
Don't use for: general Hermes troubleshooting, model selection, config review — those have their own skills.
Grading Criteria
Each skill is scored across five dimensions. Points are deducted from 100. The final grade maps to a letter:
- Grade A (90–100) — Production-ready. Solid frontmatter, exact commands, real pitfalls, verification steps, consistent structure. Will fire reliably and execute correctly across model sizes.
- Grade B (80–89) — Minor gaps. Missing one dimension but still reliable.
- Grade C (70–79) — Functional but vague in places. Needs clarification on 1–2 key areas, especially with smaller models.
- Grade D (60–69) — Error-prone patterns detected. Incomplete steps or missing critical sections. Will fail silently on model switches.
- Grade F (<60) — Broken discovery or execution. Either the description is too vague to fire, or the steps are too incomplete to follow.
Dimension 1: Frontmatter & Description (max 25 points)
The description is your skill's only chance to be discovered. Hermes sees the one-line description from available_skills before deciding whether to load SKILL.md at all. If that description is vague, the skill never fires — nothing inside SKILL.md matters if this step fails.
Full marks (25): Valid YAML frontmatter with name and description fields. Description starts with "Use when..." and covers the trigger class (not a single task). Specific enough that Hermes can distinguish it from similar skills. ≤ 1024 chars.
- Example A:
Use when debugging Python: test failures, uncaught exceptions, silent bugs. Covers root cause analysis, not just error messages. - Example B:
Use when debugging code issues and test failures.(too broad — could overlap with other skills)
What ships with it
2 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.
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.
- 8d ago First seen · 270 lines · 64 tokens per session scan A 848759d9ad36
skill-auditor is a skill published in the GitHub repository AtlasOmnia/donna-starter (107 stars, last pushed 8d ago), licensed MIT. It adds 64 tokens to every session and 3,399 once invoked, about $0.0003 per session on Opus 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 2026-08-30.
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