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 ayeshakhalid192007-dev/graph-engineering-crash-course --skill audit-sweepgit clone --depth 1 https://github.com/ayeshakhalid192007-dev/graph-engineering-crash-courseWrote 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/ayeshakhalid192007-dev/graph-engineering-crash-course/audit-sweep)<a href="https://agentmods.dev/skills/ayeshakhalid192007-dev/graph-engineering-crash-course/audit-sweep"><img src="https://agentmods.dev/badge/skills/ayeshakhalid192007-dev/graph-engineering-crash-course/audit-sweep.svg" alt="Measured on agentmods" 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 | $0.00047 | $0.00938 |
| Opus 5 | $0.00023 | $0.00469 |
| Sonnet 5 | $0.00009 | $0.00188 |
| Haiku 4.5 | $0.00005 | $0.00094 |
Grade A, and why
audit-sweep 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.
How it starts
The opening of the file, as written. The whole thing — 93 lines — stays where its author put it; the contents beside it link to each section on GitHub.
audit-sweep
Reads every output the main loop produced over a review window as one set, rather than one at a time, and checks for patterns that only become visible once multiple outputs are held in view together — reporting each pattern found, and naming which items it spans.
Instructions
You are a Claude Code skill implementing the audit-loop pattern. Follow
these steps in order:
- Read the main loop's full output set for the review window as a
single batch, not item by item. Default to the claims in this kit's
README.mdunless the user gives you a different window. Holding the whole set in view at once is the entire point — this step is what the main loop structurally cannot do from inside its own one-item scope. - Do not re-check any single item against its own governing rule. The main loop already checked each item against the rule meant for it (e.g., a claim against its own policy terms); re-litigating that isn't this skill's job and duplicates work the main loop already did correctly.
- Look specifically for cross-item patterns: repeated values, repeated actors, or repeated structures that recur across otherwise unconnected items in the set. In this kit's scenario, that means near-identical repair line-item breakdowns from the same shop recurring across claims filed by different, unrelated policyholders.
- Require the recurring detail to actually match, not merely the surface actor. Two items sharing a vendor or shop name is not itself the pattern — the line items, amounts, or structure have to line up closely enough that coincidence is implausible. A third item from the same shop with an unrelated breakdown is not part of the pattern; note it as checked and cleared, not swept in because the shop name matched.
- Name every item the pattern spans, not just the first one noticed. A flag that only cites one claim isn't useful to whoever reviews it next — cite all of them, with the specific matching detail that ties them together.
- Do not resolve the pattern. This skill's job is to surface it with enough specificity for a human or a downstream process to act on — it does not deny a claim, reverse an approval, or contact the shop itself.
- Report every pattern found, and separately report which items in the set were reviewed and cleared, so a reader can tell "reviewed, no pattern" apart from "not reviewed."
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 · 93 lines · 47 tokens per session scan A bd153f8c5d51
audit-sweep is a skill published in the GitHub repository ayeshakhalid192007-dev/graph-engineering-crash-course (5 stars, last pushed 13d ago), licensed MIT. It adds 47 tokens to every session and 938 once invoked, about $0.0002 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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