feishu-folder-summary

Extract summaries from all documents in a Feishu folder. Use when the user needs to recursively scan a Feishu wiki space or drive folder, read all documents and sub-documents, and generate a comprehensive summary report in Markdown format. Triggers on requests like "extract summaries from Feishu folder", "generate document summary report", "recursively scan Feishu documents", or when given a feishu.cn/wiki/ or feishu.cn/drive/ URL.

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Install skill "feishu-folder-summary" with this command: npx skills add henryjing96/feishu-folder-summary

Feishu Folder Summary

This skill extracts summaries from all documents in a Feishu folder (wiki or drive), recursively scanning sub-folders and generating a comprehensive Markdown report.

Overview

The skill performs the following operations:

  1. Parses the Feishu folder URL to extract space_id and node_token
  2. Recursively traverses the folder structure using feishu_wiki API
  3. Reads each document's content using feishu_doc API
  4. Generates structured summaries for each document
  5. Compiles a comprehensive Markdown report with:
    • Complete directory tree
    • Document summaries organized by folder
    • Statistics and status overview
    • Links to original documents

Supported URL Formats

  • Wiki folders: https://{domain}.feishu.cn/wiki/{node_token}
  • Drive folders: https://{domain}.feishu.cn/drive/folder/{folder_token}

Workflow

Step 1: Extract Folder Information

Parse the provided Feishu URL to identify:

  • Document type (wiki or drive)
  • Space ID (for wiki)
  • Node token or folder token

Step 2: Recursive Traversal

Use feishu_wiki API to traverse the folder structure:

feishu_wiki action="get" token="{node_token}"         # Get folder info
feishu_wiki action="nodes" space_id="{space_id}"      # List child nodes

For folders with has_child: true, recursively process child nodes.

Step 3: Document Reading

For each document node, read its content:

feishu_doc action="read" doc_token="{obj_token}"

Step 4: Generate Summary

Extract from each document:

  • Title: Document title
  • Type: Document or Folder
  • Status: Complete, In Progress, or Empty
  • Core Content: Key points, main topics, important information
  • Child Documents: If folder, list contained documents

Step 5: Compile Report

Generate a Markdown report with:

  1. Header (source URL, generation time, document count)
  2. Directory tree visualization
  3. Hierarchical summaries (by folder level)
  4. Statistics table
  5. Related links

Output Format

The generated report includes:

# {Folder Name} Document Summary Report

**Source:** {URL}  
**Generated:** {Timestamp}  
**Total Documents:** {Count}

---

## Directory Structure

{Tree visualization}

---

## Level 1 Summaries

### 1. {Document Name}
- **Type:** {docx/folder}
- **Status:** {Complete/In Progress/Empty}
- **Summary:** {Core content description}

### 2. {Folder Name}/
- **Type:** folder
- **Documents:** {Count}
- **Summary:** {Folder description}

#### 2.1 {Child Document}
- **Type:** docx
- **Summary:** {Content summary}

---

## Statistics

| Category | Count | Status |
|----------|-------|--------|
| Total | X | - |
| Complete | X | ✅ |
| In Progress | X | 🚧 |
| Empty | X | ⚠️ |

---

*Report generated by feishu-folder-summary skill*

Example Usage

User Request:

"Extract summaries from https://caz6yhvgk5z.feishu.cn/wiki/BzslwD3Nei1Dggkvin5cV2hDnob"

Skill Execution:

  1. Parse URL → Wiki folder, node_token=BzslwD3Nei1Dggkvin5cV2hDnob
  2. Get folder info → space_id=7593876306731732193, title="AI云平台"
  3. Recursively traverse → Found 14 level-1 nodes, 30+ child documents
  4. Read each document → Extract content and generate summaries
  5. Compile report → Generate comprehensive Markdown summary

Output:

  • Complete directory tree
  • Hierarchical summaries for all 44 documents
  • Status tracking (✅ Complete, 🚧 In Progress, ⚠️ Empty)
  • Statistics overview

Key Considerations

  • Recursive Depth: Process all levels of nested folders
  • Document Types: Handle docx (documents) and folder (containers)
  • Error Handling: Continue processing if individual document read fails
  • Content Length: Generate concise but informative summaries
  • Status Detection: Identify empty or placeholder documents
  • Token Efficiency: Summarize long documents appropriately

API Reference

See references/feishu_api.md for detailed API documentation.

Source Transparency

This detail page is rendered from real SKILL.md content. Trust labels are metadata-based hints, not a safety guarantee.

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