Feishu Chat Extractor

Extract and analyze historical messages from Feishu group chats.

When to Use This Skill

• Extract full chat history from a Feishu group
• Filter messages by time range
• Extract OpenClaw/Clawdbot-related discussions
• Analyze user feedback and issues
• Generate reports from chat data

Quick Start

1. Get Chat ID

# Use existing chat_id or get from group
CHAT_ID = "oc_b05242fd39d405d022fccab873d7df1b"  # Example

2. Extract Messages

# Run extraction script
python3 scripts/extract_chat.py --chat-id <CHAT_ID> --output chat_data.json

3. Analyze Content

# Extract OpenClaw-related messages
python3 scripts/analyze_content.py --input chat_data.json --keywords openclaw,clawdbot,cron,mcp

Core Workflow

Step 1: Plan (P)

1. Identify target group and time range
2. Determine extraction scope (all messages or filtered)
3. Define analysis criteria (keywords, topics)

Step 2: Do (D)

1. Run extraction script with appropriate parameters
2. Handle pagination for large message volumes
3. Save raw data to workspace

Step 3: Check (C)

1. Verify message count matches expected
2. Check time range coverage
3. Validate data completeness
4. Review sample messages for quality

Step 4: Act (A)

1. Re-extract if data incomplete
2. Filter and categorize messages
3. Generate structured report
4. Update documentation

Key Techniques

Time Range Extraction (Critical)

Problem: Default pagination may miss messages due to retention policies.

Solution: Use start_time and end_time parameters:

params = {
    "container_id": chat_id,
    "container_id_type": "chat",
    "start_time": 1700000000,  # Unix timestamp (seconds)
    "end_time": 1700100000,
    "page_size": 50
}

This ensures complete message retrieval across any time span.

Pagination Handling

all_messages = []
page_token = None

while True:
    params["page_token"] = page_token
    result = fetch_messages(params)
    all_messages.extend(result["items"])
    
    if not result["has_more"]:
        break
    page_token = result["page_token"]

Content Filtering

Filter by message type:

• text - Text messages
• post - Rich text posts
• image - Images
• vote - Polls

Scripts

extract_chat.py

Main extraction script. See scripts/extract_chat.py for full implementation.

Key features:

• Automatic pagination
• Time range filtering
• Progress logging
• Error retry logic

analyze_content.py

Content analysis script. See scripts/analyze_content.py for full implementation.

Key features:

• Keyword extraction
• Topic categorization
• Report generation

API Reference

Get Chat History

GET https://open.feishu.cn/open-apis/im/v1/messages

Parameters:

• container_id (required): Chat ID
• container_id_type: "chat"
• start_time: Start timestamp (seconds)
• end_time: End timestamp (seconds)
• page_size: 1-50 (default 50)
• page_token: For pagination

Common Error Codes

• 232006: Invalid chat_id
• 232011: Not in group
• 232025: Bot capability not enabled

Best Practices

1. Always use time ranges for complete extraction
2. Check has_more and paginate properly
3. Save intermediate results to avoid re-extraction
4. Validate data before analysis
5. Document extraction parameters for reproducibility

Output Format

{
  "chat_id": "oc_xxx",
  "extraction_time": "2026-02-06T17:00:00Z",
  "total_messages": 953,
  "time_range": {
    "start": "2026-01-27",
    "end": "2026-02-06"
  },
  "messages": [
    {
      "message_id": "om_xxx",
      "create_time": 1769500000000,
      "msg_type": "text",
      "content": "...",
      "sender": "..."
    }
  ]
}