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Install in OpenClaw
/install kuanshu-tiku
Description
宽数题库项目入口，涵盖四套量化题库来源、仓库结构、常用命令与当前公网部署信息。
README (SKILL.md)
宽数题库
用途
当你需要查看、运行、扩展或部署“宽数题库”这个多来源量化题库项目时，使用这个技能。
适合这些场景：
- 需要快速理解项目是什么、当前公开站点是什么
- 需要确认仓库中已经接入了哪些题库来源
- 需要知道原始抓取、标准化数据和页面代码分别放在哪里
- 需要重新抓取、构建或检查部署前置条件
项目资源
- GitHub 仓库：https://github.com/aznikline/kuanshu-tiku
- 当前公开站点：https://quantics-bank.vercel.app
当前接入的题库来源
- OpenQuant：
openquant.co/questions - Brainstellar：
brainstellar.com/puzzles - QuantQuestion：
quantquestion.com - Jane Street：
janestreet.com/puzzles
当前总题量：1304 道。
目录结构
data/raw/说明：四套来源的原始索引与详情数据data/translations/说明：中文翻译与分批翻译产物src/data/questions.json说明：OpenQuant 标准化数据src/data/brainstellar-questions.json说明：Brainstellar 标准化数据src/data/quantquestion-questions.json说明：QuantQuestion 标准化数据src/data/janestreet-questions.json说明：Jane Street 标准化数据src/pages/index.astro说明：首页src/pages/questions/[slug].astro说明：统一详情页scripts/说明：抓取、构建、翻译和部署检查脚本
常用命令
安装依赖：
npm install
抓取与构建：
npm run data:index
npm run data:details
npm run data:brainstellar:index
npm run data:brainstellar:details
npm run data:brainstellar:build
npm run data:quantquestion:fetch
npm run data:janestreet:index
npm run data:janestreet:details
npm run data:janestreet:translate
npm run data:janestreet:build
npm run data:validate
npm run data:build
本地开发与验证：
npm run dev
npm run test
npm run check
npm run build
托管与发布
- GitHub 仓库保持 private
- 公网托管走 Vercel
Vercel 常用命令：
npx vercel whoami
npx vercel deploy dist --prod --yes
工作建议
如果你是第一次接手这个项目，建议按这个顺序：
- 读
README.md - 跑
npm run data:validate - 跑
npm run build - 看
src/pages/index.astro与src/pages/questions/[slug].astro - 如果改抓取链，再读
scripts/
什么时候用这个技能
- 想快速知道这个项目现在有哪些题库来源
- 想确认某道题属于哪个来源
- 想重新拉取 Brainstellar / Jane Street 等来源
- 想把本地最新内容重新部署到 Vercel
Usage Guidance
This skill is an instructions-only helper for a repo; it appears coherent. Before running any commands it recommends, review the repository (especially scripts/ and package.json) to confirm what network requests and shell commands the data-fetch/build scripts perform. Running npm install and the data scripts will fetch external data and dependencies; run them in a controlled environment (container/VM) if you are concerned. If you plan to deploy to Vercel, be aware that npx vercel deploy will use your Vercel account and credentials — do not expose secrets to any unreviewed scripts. In short: the skill itself is benign and aligns with its description, but exercise standard caution and inspect the repo code before executing build/fetch/deploy commands.
Capability Analysis
Type: OpenClaw Skill
Name: kuanshu-tiku
Version: 0.1.1
The skill bundle serves as a documentation and operational guide for a quantitative finance question bank project. It contains standard project metadata, directory structures, and common development/deployment commands (npm, Vercel) consistent with its stated purpose. No malicious code, data exfiltration patterns, or harmful prompt injections were found in SKILL.md or _meta.json.
Capability Assessment
Purpose & Capability
Name/description match SKILL.md content: it documents repository structure, data sources, common commands and deployment info. It does not request unrelated credentials, binaries, or system access.
Instruction Scope
Runtime instructions are limited to repository navigation, npm scripts, and Vercel deploy commands. They reference repo files and external data sources (the four listed providers) which is consistent with the stated purpose. Note: following the documented commands will execute project scripts and network fetches (expected for a data-scraping/build workflow).
Install Mechanism
No install spec or code files are included — the skill is instruction-only, so nothing is written to disk by an installer. This is the lowest-risk install model.
Credentials
The skill declares no required environment variables or credentials. However, practical use (npm install, running data-fetch scripts, or npx vercel deploy) typically requires network access and, for deployment, Vercel/GitHub credentials — those are not requested by the skill itself, which is appropriate.
Persistence & Privilege
always:false and normal model invocation settings. The skill does not request persistent system-level privileges or modify other skills' configs.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install kuanshu-tiku - After installation, invoke the skill by name or use
/kuanshu-tiku - Provide required inputs per the skill's parameter spec and get structured output
Version History
v0.1.1
Refresh project metadata for four-source puzzle sync and Vercel hosting.
v0.1.0
- Initial release of kuanshu-tiku skill.
- Provides concise entry instructions and usage scenarios for the Kuanshu Tiku Chinese quantitative interview question bank project.
- Lists project resources, including GitHub repository and Pages site.
- Details directory structure and describes the purpose of key folders and files.
- Includes common commands for data fetching, validation, site development, and deployment.
- Offers workflow conventions and step-by-step suggestions for new contributors.
Metadata
Frequently Asked Questions
What is 宽数题库?
宽数题库项目入口，涵盖四套量化题库来源、仓库结构、常用命令与当前公网部署信息。 It is an AI Agent Skill for Claude Code / OpenClaw, with 94 downloads so far.
How do I install 宽数题库?
Run "/install kuanshu-tiku" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is 宽数题库 free?
Yes, 宽数题库 is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does 宽数题库 support?
宽数题库 is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created 宽数题库?
It is built and maintained by Mason (@aznikline); the current version is v0.1.1.
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