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 AgentEvalHQ/AgentEval --skill expense-reportgit clone --depth 1 https://github.com/AgentEvalHQ/AgentEvalWrote 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/agentevalhq/agenteval/expense-report)<a href="https://agentmods.dev/skills/agentevalhq/agenteval/expense-report"><img src="https://agentmods.dev/badge/skills/agentevalhq/agenteval/expense-report/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/agentevalhq/agenteval/expense-report"><img src="https://agentmods.dev/badge/skills/agentevalhq/agenteval/expense-report.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00061 | $0.00322 |
| Opus 5.5 | $0.00024 | $0.00129 |
| Sonnet 5.5 | $0.00012 | $0.00064 |
| Haiku 4.5 | $0.00006 | $0.00032 |
Grade A, and why
expense-report 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.
What it actually says
Expense Report Skill
You help employees understand and comply with the company's expense-report policy for meals.
When to use this skill
- The user asks what the meal expense policy or per-meal cap is.
- The user asks whether a specific dollar amount is within policy.
- The user asks you to compute exactly how much a meal expense is over the policy cap.
How to use this skill
- To answer a general policy question (e.g. "what's the per-meal cap?"), call
read_skill_resourcewithskillName="expense-report"andresourceName="resources/policy.md"to read the full policy text. - To compute an EXACT overage amount for a specific dollar figure, call
run_skill_scriptwithskillName="expense-report",scriptName="scripts/summarize.csx", andarguments={"amount": <the dollar amount as a number>}. Only run the script when the user asks for an exact computed overage — do not run it for a general policy question. - Never run the script for tasks that only need the policy text; that is unnecessary code execution for a read-only question.
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.
- 1mo ago First seen · 27 lines · 61 tokens per session scan A 5a0e3469466f
expense-report is a skill published in the GitHub repository AgentEvalHQ/AgentEval (157 stars, last pushed 3d ago), licensed MIT. It adds 61 tokens to every session and 322 once invoked, about $0.0002 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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