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 Neeeophytee/finding-unknowns-skills --skill context-auditgit clone --depth 1 https://github.com/Neeeophytee/finding-unknowns-skillsWrote 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/neeeophytee/finding-unknowns-skills/context-audit)<a href="https://agentmods.dev/skills/neeeophytee/finding-unknowns-skills/context-audit"><img src="https://agentmods.dev/badge/skills/neeeophytee/finding-unknowns-skills/context-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/neeeophytee/finding-unknowns-skills/context-audit"><img src="https://agentmods.dev/badge/skills/neeeophytee/finding-unknowns-skills/context-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 | $0.00076 | $0.00669 |
| Opus 5.5 | $0.00030 | $0.00268 |
| Sonnet 5.5 | $0.00015 | $0.00134 |
| Haiku 4.5 | $0.00008 | $0.00067 |
Grade A, and why
context-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 1mo 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 — 30 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Context audit
A prompt is written for one task; context is reused across every task, so it can never be as specific. That gap is where instructions rot: rules written for a worst case that no longer happens, guidance duplicated across three layers, two layers quietly telling the model opposite things. The model can resolve all of it — by spending thinking budget on it before it starts your actual work. This skill finds what to delete.
Steps
- Inventory every layer that reaches the model: root and nested
CLAUDE.md/AGENTS.md, each skill's description and body, hooks, tool and MCP server descriptions, and any harness prompt the user controls. Report each layer's size. The layer the user forgot they wrote is usually the loudest one. - Read them together, the way the model receives them — not one file at a time. Contradictions only exist between layers.
- Classify every instruction as one of five things:
- Conflict — two layers pulling opposite ways ("document as appropriate" against "never add comments"). Quote both sides verbatim. These are the most expensive finding and go first.
- Duplicate — the same instruction in two places. Keep the copy nearest the point of use; behavior of a tool belongs in that tool's description, not in the global preamble.
- Obvious — restates what the file tree, the language, or the surrounding code already shows.
- Judgement-now — a blanket rule written to prevent a worst case, wrong for some real subset of requests, and the kind of call a current model makes well on its own.
- Gotcha — non-obvious, specific to this repo, load-bearing. This is what should survive; most repos are mostly the other four.
- Propose the cut as a diff: conflicts resolved first, then duplicates, then the rest. For anything that is worth keeping but only sometimes needed, propose relocating it into a skill or a linked file loaded on demand rather than deleting it.
- Close with before/after line counts and the single deletion you are least confident about, named explicitly so a human decides that one.
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.
- 1mo ago First seen · 30 lines · 76 tokens per session scan A 585463aca005
context-audit is a skill published in the GitHub repository Neeeophytee/finding-unknowns-skills (356 stars, last pushed 1mo ago), licensed MIT. It adds 76 tokens to every session and 669 once invoked, about $0.0003 per session on Opus 5.5. 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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