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AI EngineeringHTML

Bear Onboard

by xuzhougeng

Bear Onboard is an AI Engineering skill for Claude Code, published by xuzhougeng in wisp-science.

1K stars106 forkson xuzhougeng/wisp-scienceAdded 2026/08/21+1% in starsRepository updated 2026/08/21
agent-skillsai-agentai-assistantai-for-scienceai4sciencebioinformaticscomputational-biologydesktop-appllmlocal-firstmcpmodel-context-protocolpythonreproducible-researchresearch-assistantrstatsrustscientific-computingscientific-workflowtauri
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Install Bear Onboard
Copy Bear Onboard into your Claude Code skills folder. Run the command in your terminal, or review the source on GitHub before installing.
terminal
npx degit https://github.com/xuzhougeng/wisp-science/tree/main/skills/bear-onboard ~/.claude/skills/bear-onboard

Requires Node.js. Downloads this skill only — not the rest of the repository — into your Claude Code skills folder.

Without Node.js

git clone https://github.com/xuzhougeng/wisp-science.git

Clones the whole repository, then copy the skill’s own directory into your skills folder yourself.

In this catalog

Source file
skills/bear-onboard/SKILL.md in xuzhougeng/wisp-science
Installs to
~/.claude/skills/bear-onboard
Collection
One of 25 skills cataloged from this repository
Category
AI Engineering2451 skills

What Bear Onboard does

Bear Onboard 生成一份综合报告,把陌生领域的概念版图和演化脉络一起梳理出来,帮助快速建立认知框架。它适合想快速入门一个方向、理解核心概念和发展历史时使用。

Bear Onboard is cataloged under AI Engineering on DirSkills. Bear Onboard comes from a repository tagged agent-skills, ai-agent, ai-assistant, ai-for-science and ai4science.

Documentation

README

bear-onboard · 领域快速入门

一个工作流:把概念版图(空间)和演化脉络(时间)同时摆出来,让你在最短的时间内建立对一个陌生领域的立体认知。单独看地图不知道哪个概念重要;单独看脉络不知道现在的技术版图长什么样。两者交叉,才能定位自己在哪里、该从哪里进入。

先读 references/sci-cli.md——CLI 检测步骤、用法和铁律。 再读 references/output-system.md——HTML 外壳规范和设计 token。

步骤(固定顺序)

Step 0 — 确认 CLI 可用 运行 sci --version。未安装就给安装命令并停止;认证错误就提示 sci init 并停止。

Step 1 — 锚定领域,执行多维检索(概念版图侧) 以输入术语为中心概念,执行主检索(--mode low--limit 20),再做至少 2 个补充检索(方法邻居、应用场景、对照概念等角度)。从摘要里挖出 5–8 个邻近概念,每个概念写出:它是什么(2–3 句)+ 与中心的连接(1 句)+ 支撑文献 ID。

告知用户本次将执行约 8–10 次检索,然后直接开始,不等待确认。

Step 2 — 锚定演化脉络,执行溯源检索(脉络侧) 以同一术语为主题,先找当前标志性工作作为锚点,再逐层向前追溯(默认 3 层),最后补充近 1–2 年的最新进展。每条传承边标注关系类型(方法来源 / 问题来源 / 证据来源 / 领域转折)。

Step 3 — 交叉识别枢纽节点 对比两侧的检索结果,找出同时出现在概念版图和演化脉络中的概念——这些是枢纽节点,是理解这个领域最优先需要掌握的概念。枢纽节点通常既是地图上的核心邻居,也是脉络上的关键转折点。

This is the opening of the README. Read the full README on GitHub.

Frequently asked about Bear Onboard

  • What else does xuzhougeng publish alongside Bear Onboard?

    Bear Onboard is one of 25 skills that DirSkills catalogs from xuzhougeng/wisp-science, the repository it ships in. Its siblings there include Agent Infini, Bear Counter and Bear Map. Each one is a separate skill with its own page in this directory, installs the same way Bear Onboard does, and is maintained by xuzhougeng in that same repository. The rest of the collection is listed on the xuzhougeng/wisp-science page.

  • How does Bear Onboard compare to other AI Engineering skills?

    Bear Onboard ranks #1352 by stars among the 2451 AI Engineering skills in this catalog. The most-starred ones next to it are Architecture Decision Records, AI-First Engineering and Agentic OS. DirSkills ranks by the star count of the repository each skill ships in, so that order reflects how popular those repositories are rather than any review of Bear Onboard against them. Open each page to compare what they document and how they install.

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Bear Onboard is one of 25 skills cataloged on DirSkills from xuzhougeng/wisp-science.

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