Group Deduplication Skill

Automatically searches for community groups (WeChat, QQ, industry groups) and filters out duplicates using memory-cache with MD5-based keys and 30-day TTL.

Workflow

1. Search: Find groups using multi-search-engine across platforms
2. Deduplicate: Check memory-cache for existing group records using MD5 hashes
3. Filter: Return only new groups not previously discovered
4. Push: Output new groups for user consumption
5. Cache: Automatically store discovered groups in memory-cache with TTL 30 days

Key Features

• MD5-based deduplication: Uses mema:groups:{群名MD5} key format
• 30-day TTL: Cached entries automatically expire after 30 days
• Zero duplicates: Only returns genuinely new group discoveries
• Multi-platform: Searches WeChat, QQ, and industry groups
• Memory efficient: Uses existing memory-cache skill for storage

Requirements

• memory-cache skill must be installed
• REDIS_URL environment variable configured for memory-cache
• multi-search-engine skill available (bundled with OpenClaw)

Usage

Basic Search

Search for new groups in a specific industry or topic:

# Search for new AI industry groups
python3 $WORKSPACE/skills/group-deduplicate/scripts/search_groups.py --query "AI 人工智能 群" --max-results 10

# Search for new WeChat groups about blockchain
python3 $WORKSPACE/skills/group-deduplicate/scripts/search_groups.py --query "区块链 区块链技术 微信群" --platform wechat --max-results 5

Check Cache Status

View current cached groups or clear cache:

# See all cached groups
python3 $WORKSPACE/skills/group-deduplicate/scripts/cache_manager.py list

# Clear expired cache entries
python3 $WORKSPACE/skills/group-deduplicate/scripts/cache_manager.py cleanup

# Check specific group existence
python3 $WORKSPACE/skills/group-deduplicate/scripts/cache_manager.py check "群名称"

Installation

This skill assumes memory-cache is already installed. If not:

openclaw clawhub install memory-cache

Scripts Included

scripts/search_groups.py

Main search script with deduplication logic:

• --query: Search query (required)
• --platform: Target platform (wechat, qq, industry, all) - default: all
• --max-results: Maximum results to return - default: 10
• --use-cache: Enable deduplication (default: true)
• --ttl-days: Cache TTL in days (default: 30)

scripts/cache_manager.py

Cache management interface:

• list: Show all cached groups
• check <group-name>: Check if group exists in cache
• add <group-name>: Manually add group to cache
• remove <group-name>: Remove group from cache
• cleanup: Remove expired entries
• stats: Show cache statistics

Technical Details

Cache Key Format

mema:groups:{md5_hash_of_group_name}

• Uses MD5 hash of normalized group name for consistent keys
• TTL defaults to 30 days (2592000 seconds)
• Stored in memory-cache namespace

Search Process

1. Normalize group name (trim whitespace, lowercase for hashing)
2. Generate MD5 hash for cache key lookup
3. Check memory-cache for existing entry
4. If not found, return as new group and cache it
5. If found, skip as duplicate

Supported Platforms

• WeChat: Searches WeChat groups/channels
• QQ: Searches QQ groups
• Industry: Searches industry forums, Tieba, professional networks
• All: Searches across all platforms (default)

Example Output

When running a search, you'll get:

Found 3 new groups:
1. AI技术交流群 (WeChat) - https://...
2. Machine Learning论坛 (Industry) - https://...
3. Deep Learning实战QQ群 (QQ) - https://...

Cached 3 new groups with 30-day TTL.

Notes

• The skill respects search engine rate limits (1-2 second delays)
• Only session cookies are used temporarily (no persistence)
• Results include group name, platform, and link when available
• Cache survives OpenClaw restarts via Redis persistence
• Manual cache management available for administrative control

Troubleshooting

If you see "Redis connection failed":

1. Ensure REDIS_URL is set in your environment
2. Verify Redis server is running
3. Check memory-cache skill installation

If searches return no results:

1. Try broader or different search queries
2. Verify multi-search-engine skill is functional
3. Check network connectivity to search engines