Check Pattern Discovery
Monitor Qdrant pattern collections and discovery performance.
What It Checks
- Collection sizes and vector counts
- Recent pattern retrievals
- Pattern quality distribution
- Collection health status
- Search performance
How to Use
python3 ${CLAUDE_PLUGIN_ROOT}/skills/system_status/check_pattern_discovery/execute.py
Arguments
--detailed: Include collection-specific statistics
Output Formats
Non-Detailed Mode (Default)
Returns basic collection statistics with full field names. Suitable for programmatic parsing and data processing.
python3 ${CLAUDE_PLUGIN_ROOT}/skills/system_status/check_pattern_discovery/execute.py
JSON Structure:
{
"success": true,
"total_patterns": 15689,
"collection_count": 4,
"collections": {
"archon_vectors": {
"vectors_count": 7118,
"indexed_vectors_count": 7118,
"status": "green"
},
"code_generation_patterns": {
"vectors_count": 8571,
"indexed_vectors_count": 8571,
"status": "green"
},
"archon-intelligence": {
"vectors_count": 0,
"indexed_vectors_count": 0,
"status": "green"
},
"quality_vectors": {
"vectors_count": 0,
"indexed_vectors_count": 0,
"status": "green"
}
},
"timestamp": "2025-11-21T14:30:00.123456+00:00"
}
Fields:
success(boolean): Whether the operation succeededtotal_patterns(integer): Sum of all vectors across collectionscollection_count(integer): Number of collections foundcollections(object): Per-collection statistics with full field namesvectors_count(integer): Total vectors in collectionindexed_vectors_count(integer): Vectors that are indexedstatus(string): Collection health status ("green", "yellow", "red")
timestamp(string): ISO 8601 timestamp in UTC
When to use: Scripts, automation, data pipelines, JSON parsing
Detailed Mode
Returns collection statistics with simplified field names for better readability. Suitable for human consumption and dashboards.
python3 ${CLAUDE_PLUGIN_ROOT}/skills/system_status/check_pattern_discovery/execute.py --detailed
JSON Structure:
{
"success": true,
"total_patterns": 15689,
"collection_count": 4,
"collections": {
"archon_vectors": {
"vectors": 7118,
"status": "green",
"indexed_vectors": 7118
},
"code_generation_patterns": {
"vectors": 8571,
"status": "green",
"indexed_vectors": 8571
},
"archon-intelligence": {
"vectors": 0,
"status": "green",
"indexed_vectors": 0
},
"quality_vectors": {
"vectors": 0,
"status": "green",
"indexed_vectors": 0
}
},
"timestamp": "2025-11-21T14:30:00.123456+00:00"
}
Fields:
success(boolean): Whether the operation succeededtotal_patterns(integer): Sum of all vectors across collectionscollection_count(integer): Number of collections foundcollections(object): Per-collection statistics with simplified field namesvectors(integer): Total vectors in collectionindexed_vectors(integer): Vectors that are indexedstatus(string): Collection health status ("green", "yellow", "red")
timestamp(string): ISO 8601 timestamp in UTC
When to use: Human-readable output, dashboards, reports, debugging
Error Response Format
When an error occurs (Qdrant unreachable, connection timeout, etc.):
{
"success": false,
"error": "Connection error: Not Found",
"timestamp": "2025-11-21T14:30:00.123456+00:00"
}
Fields:
success(boolean): Alwaysfalsefor errorserror(string): Error descriptiontimestamp(string): ISO 8601 timestamp in UTC
Exit Codes
Exit codes enable reliable scripting and automation:
0: Success - Pattern collections retrieved successfully
- All collections accessible
- Statistics retrieved without errors
- Qdrant connection healthy
1: Error - Failed to retrieve pattern statistics
- Qdrant connection failed (unreachable, timeout, refused)
- Collection query error (invalid response, permission denied)
- Network error or configuration issue
- Check
errorfield in JSON output for details