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/scientific-tool-onboarding/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/scientific-tool-onboarding)<a href="https://agentmods.dev/skills/zimoliao/scholaraio/scientific-tool-onboarding"><img src="https://agentmods.dev/badge/skills/zimoliao/scholaraio/scientific-tool-onboarding/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/scientific-tool-onboarding"><img src="https://agentmods.dev/badge/skills/zimoliao/scholaraio/scientific-tool-onboarding.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 | $0.00049 | $0.04183 |
| Opus 5 | $0.00024 | $0.02091 |
| Sonnet 5 | $0.00010 | $0.00837 |
| Haiku 4.5 | $0.00005 | $0.00418 |
Grade A, and why
scientific-tool-onboarding 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 12d 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 — 334 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Scientific Tool Onboarding
Overview
先判断一个科学工具是否值得进入 ScholarAIO；只有通过 2.x integration gate 后，接入目标才是形成这三个层次的闭环，而不是“写一份长教程”：
toolref能查官方接口和参数- 对应
skill能指导 agent 何时使用、如何验证 - CLI 在真实使用中足够稳，不只是测试能过
规范参考：
- 公开接入说明统一参照 docs/guide/toolref-onboarding.md
- 产品边界与准入门统一参照 docs/design-docs/2.x-public-contract.md
- 运行时行为统一参照
scientific-runtimeskill
When to Use
适用于：
- 新增一个科学计算工具到
scholaraio toolref - 升级某个工具的官方文档源或版本策略
- 发现现有 scientific skill 过重，需要改成
toolref-first
不适用于：
- 只写一篇一次性笔记
- 只修一个小 typo
Core Workflow
0. 先过 2.x integration gate
不要因为用户提到一个项目、它很热门，或官方文档可抓取，就默认把它接入 ScholarAIO。先逐项确认：
- 它解决的是已经出现的核心学术任务，而不是增加一个新的平台类别
- 当前 agent 原生能力与已有 ScholarAIO 路径不能充分完成这个任务
- 没有另一套重叠适配器在做同一件事，并且有明确维护责任
- 依赖、凭据和运行时可以保持可选并与 core install 隔离
- 可以设计固定语料或端到端 smoke 来证明用户任务确实改善
- 缺凭据、断网、上游漂移或服务不可用时，能给出可执行错误或 fallback
任何一项不满足时，优先采用外部 recipe、用户自管工具或 sidecar；不要继续下面的内置接入流程。升级既有工具时也要重新过门，不因历史存在而自动保留。
1. 再定“官方真源”
优先级：
- 官方文档站
- 官方源码仓库中的文档目录
- 官方维护的 README / man page / PDF
不要优先用：
- 博客
- 第三方教程
- 论坛帖子
要求：
- 记录文档 URL、版本策略、格式（RST / HTML / man / Markdown / PDF）
- 判断适合
git抓取还是manifest抓取
经验判断：
- 如果官方文档天然按源码版本演进、结构稳定、页面很多，优先
git - 如果官方文档是独立文档站、页面总数可控、但抓取噪音和网络波动明显，优先
manifest - 不要为了“理论更完整”强行选
git；用户在乎的是 agent 能不能顺手查到 - 如果文档站有“总目录页 / 命令索引页 / 手册页目录”，优先把它作为自动发现种子，而不是手写所有子页面
当前项目里的经验：
QE / LAMMPS / GROMACS更适合git + parserOpenFOAM / Bioinformatics更适合manifest + curated entry pages
2. 再定“接入粒度”
问自己三个问题：
- 用户会按什么名词来查：求解器、命令、参数、字典、子工具？
page_name应该怎么命名，未来最稳？program / section / title该怎样存，show/search才顺手？
经验规则：
page_name要服务 CLI 使用体验，不要只服务抓取方便- 一个大页面如果天然包含很多独立参数，应该拆页
- 如果工具本来就是多子工具工具链，允许一个 top-level tool 下挂多个
program program要优先贴近用户会说出的名字，而不是内部类名或目录名section要反映用户排查问题时的思路，例如solver/dictionary/variant-calling
从现有工具得到的粒度经验：
QE：程序名 + namelist + 参数名，这样show qe pw ecutwfc才顺LAMMPS：命令家族一定要做 alias 聚合，不然fix npt这种自然输入会漂走GROMACS：mdp参数页必须尽量保留 options，不然会变成只有变量名的空页OpenFOAM：不要一上来想抓完整站点，先抓 solver / dictionary / post-processing 关键页Bioinformatics：要承认它是 toolchain，不是单软件；先解决“路由到哪个子工具”
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.
- 12d ago First seen · 334 lines · 49 tokens per session scan A 4a009e4f74aa
scientific-tool-onboarding is a skill published in the GitHub repository ZimoLiao/scholaraio (570 stars, last pushed 12d ago), licensed MIT. It adds 49 tokens to every session and 4,183 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 2026-08-30.
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