目标：把“给我一个 URL → 产出可读 Markdown + 可追溯入口”变成一个统一入口，供后续所有业务 skill（github-explorer、写作类 skills、日报等）复用。
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versioncontent-extractExecute the skills CLI command in your project's root directory to begin installation:
Fetches content-extract from blessonism/openclaw-search-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate content-extract. Access via /content-extract in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
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目标：把“给我一个 URL → 产出可读 Markdown + 可追溯入口”变成一个统一入口，供后续所有业务 skill（github-explorer、写作类 skills、日报等）复用。
核心原则（来自你发的 Excel Skill 拆解文章的启发）：
输入：url
references/domain-whitelist.mdmodel_version=MinerU-HTMLweb_fetch(url)references/heuristics.md）包括：
skills/mineru-extract/scripts/mineru_parse_documents.pymodel_version=MinerU-HTML无论用 probe 还是 MinerU，都返回同一套结构：
{
"ok": true,
"source_url": "...",
"engine": "web_fetch" ,
"markdown": "...",
"artifacts": {
"out_dir": "...",
"markdown_path": "...",
"zip_path": "..."
},
"sources": [
"原文URL",
"（如使用MinerU）MinerU full_zip_url",
"（如使用MinerU）本地markdown_path"
],
"notes": ["任何重要限制/失败原因/下一步建议"]
}
注意：
engine可能是web_fetch或mineru。
当需要 MinerU 时，用这个命令（返回 JSON，且可把 markdown 内联进 JSON，便于下游总结）：
python3 mineru-extract/scripts/mineru_parse_documents.py \
--file-sources "<URL>" \
--model-version MinerU-HTML \
--emit-markdown --max-chars 20000
路径说明: 上述命令假设你在 skills 安装根目录下执行。如果 mineru-extract 安装在其他位置，请替换为实际路径。
sources（原文入口 + 解析产物入口）。markdown_path（本地路径）写进 sources，方便复查。Prerequisites
Time Estimate
15-45 minutes depending on use case complexity
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
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Useful defaults in content-extract — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
content-extract fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
I recommend content-extract for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
content-extract is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Useful defaults in content-extract — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
content-extract is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Registry listing for content-extract matched our evaluation — installs cleanly and behaves as described in the markdown.
Keeps context tight: content-extract is the kind of skill you can hand to a new teammate without a long onboarding doc.
I recommend content-extract for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Keeps context tight: content-extract is the kind of skill you can hand to a new teammate without a long onboarding doc.
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