Borrowing it
Nothing to install: this file belongs to ZimoLiao/scholaraio. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/ZimoLiao/scholaraio/main/.claude/skills/metrics/SKILL.mdgit clone --depth 1 https://github.com/ZimoLiao/scholaraioWrote 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/zimoliao/scholaraio/metrics)<a href="https://agentmods.dev/skills/zimoliao/scholaraio/metrics"><img src="https://agentmods.dev/badge/skills/zimoliao/scholaraio/metrics/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/zimoliao/scholaraio/metrics"><img src="https://agentmods.dev/badge/skills/zimoliao/scholaraio/metrics.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 | $0.00027 | $0.00201 |
| Opus 5 | $0.00014 | $0.00101 |
| Sonnet 5 | $0.00005 | $0.00040 |
| Haiku 4.5 | $0.00003 | $0.00020 |
Grade A, and why
metrics 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 11d 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
查看指标统计
查看 LLM token 用量、API 调用耗时等运行指标。
执行逻辑
查看最近 LLM 调用详情：
scholaraio metrics --last 20
查看汇总统计：
scholaraio metrics --summary
查看特定时间段：
scholaraio metrics --since 2026-03-01
查看其他类别事件：
scholaraio metrics --category api --last 50
示例
用户说："我用了多少 token"
→ 执行 metrics --summary
用户说："看看最近的 LLM 调用"
→ 执行 metrics --last 10
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.
- 11d ago First seen · 38 lines · 27 tokens per session scan A a1a25008afb0
metrics is a skill published in the GitHub repository ZimoLiao/scholaraio (570 stars, last pushed 11d ago), licensed MIT. It adds 27 tokens to every session and 201 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 2026-08-30.
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