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 uwuclxdy/agenticat --skill skill-routing-auditgit clone --depth 1 https://github.com/uwuclxdy/agenticatWrote 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/uwuclxdy/agenticat/skill-routing-audit)<a href="https://agentmods.dev/skills/uwuclxdy/agenticat/skill-routing-audit"><img src="https://agentmods.dev/badge/skills/uwuclxdy/agenticat/skill-routing-audit/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/uwuclxdy/agenticat/skill-routing-audit"><img src="https://agentmods.dev/badge/skills/uwuclxdy/agenticat/skill-routing-audit.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 | $0.00025 | $0.00875 |
| Opus 5 | $0.00013 | $0.00438 |
| Sonnet 5 | $0.00005 | $0.00175 |
| Haiku 4.5 | $0.00003 | $0.00088 |
Grade A, and why
skill-routing-audit 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 2d 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 — 58 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill Routing Audit
A skill can hold the right answer and still fail, because routing buries it. Happy-path "how do I X" questions route to the right reference. Boundary and negative questions ("can it even do X?", "what can't it do?", "is Y possible?") route to that same "how to do X" reference, which only lists what the subject can do, so the real "no" sits in another file or nowhere. The reader lands where the routing points and never sees it.
This skill hunts that failure with boundary probes and a skill-only simulation.
When to Use
- After authoring or editing a skill, before relying on it.
- To sweep every installed skill for the same class of gap.
- When a skill that should cover a question gave a vague or wrong answer.
Not for creating a skill from scratch or folding the user's manual edit back into a skill.
Out of scope too: cross-skill misselection (the top-level router picking a different skill entirely) and pairwise overlap between competing skills. This audits burial inside an already-selected skill. A skill that never fires at all has a description/triggering problem; that routes to fixing the skill's description field, not here.
Method
Point it at a skill's directory. Audit one named skill, or every subdirectory that has a SKILL.md.
Fan out one read-only subagent per skill (parallel for an all-skills sweep). Each agent:
- Read the skill's
SKILL.md, then its reference and bundled files, to learn what it covers and what it says the user can and cannot do. - Derive 4 to 6 boundary/negative probes a real user would ask at the edge of the skill's scope: plausibly-impossible actions, off-limits operations, common misconceptions. Not happy-path "how do I X". Ground each in the skill's own subject.
- Answer each probe using only this skill: start from
SKILL.md, follow the skill's own routing table and pointers to whichever reference an agent would naturally open. Read nothing outside the skill dir; use no prior knowledge of the underlying tool. - Classify each probe:
- OK:
SKILL.mdor the naturally-routed reference answers it confidently. - ROUTING GAP: the answer exists in the skill, but natural routing sends you to a file that lacks it. Name the wrong-turn file and where the answer actually lives.
- CONTENT GAP: the answer is not anywhere in the skill.
- OK:
- Return a table:
probe | verdict | wrong-turn file | where the answer lives | one-line fix. Read-only, edit nothing.
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.
- 2d ago Changed d16804b12c95
- 10d ago First seen · 58 lines · 25 tokens per session scan A f45f72615399
skill-routing-audit is a skill published in the GitHub repository uwuclxdy/agenticat (5 stars, last pushed 2d ago), licensed MIT. It adds 25 tokens to every session and 875 once invoked, about $0.0001 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 2026-08-31.
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