用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt;运行前请先检查来源。
npx skills add https://github.com/drn/dots --skill notion命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地?可下载 SkillsMP 当前能够提供的文件。
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基于 SOC 职业分类
| name | notion |
| description | Read Notion pages and databases using MCP tools. Use when looking up Notion content, reading pages, or querying databases. |
Read Notion pages and databases via MCP tools. This skill covers reading operations only.
| Tool | Use For |
|---|---|
mcp__notion__notion-fetch | Read page content as Notion-flavored markdown |
ReadMcpResourceTool with notion://docs/enhanced-markdown-spec | Get the full markdown spec (useful for understanding page structure) |
If mcp__notion__notion-fetch is not available (e.g., in environments using Keystone), use these tools instead:
| Tool | Use For |
|---|---|
mcp__plugin_thanx_keystone__notion_get_page | Read page metadata (title, properties, dates) |
mcp__plugin_thanx_keystone__notion_get_page_content | Read page blocks (raw Notion API JSON) |
mcp__plugin_thanx_keystone__notion_search | Search for pages by title |
mcp__plugin_thanx_keystone__notion_query_database | Query a database with filters |
mcp__plugin_thanx_keystone__notion_get_database | Get database schema and metadata |
The blocks API returns raw JSON. To extract readable text, parse each block's rich_text[].plain_text fields. Use ToolSearch to discover and load these tools before calling them.
You are helping read Notion data. Use the MCP tools above for all operations.
mcp__notion__notion-fetch with the page URL or ID
The tool returns Notion-flavored markdown. Key things to know about the format:
```ruby){toggle="true"} attribute<table> syntax[d.date](http://d.date))Use mcp__notion__notion-fetch with the page URL.
Use mcp__notion__notion-fetch on the database URL to see its schema and entries.
If a page has mangled content in the markdown output:
#, ##)<table or --- dividersThese indicate sections that were absorbed into code blocks during a bad edit.
Notion pages can return very large responses (100K+ characters) that exceed token limits. When this happens:
python3 -c or jq to extract block text rather than reading raw JSON directlyjq -r '.. | .rich_text? // empty | .[].plain_text' < temp_file.jsonnotion-address-comments skill instead.