Documentation Index Fetch the complete documentation index at: https://mintlify.com/timepoint-ai/timepoint-clockchain/llms.txt
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Endpoint Returns aggregate statistics about the entire knowledge graph, including total counts and breakdowns by layer, edge type, and source type.
Authentication Requires service key authentication via X-Service-Key header.
Response Total number of nodes in the graph
Total number of edges in the graph
Node count grouped by layer level Keys are layer numbers (as strings), values are node counts. Layers represent data quality/completeness tiers:
"0" - Draft or incomplete nodes"1" - Basic public nodes"2+" - Enhanced nodes with additional metadata Example: { "0" : 1250 , "1" : 3400 , "2" : 890 , "3" : 120 }
Edge count grouped by relationship type Keys are edge types, values are edge counts:
causes - Causal relationships (manually curated)contemporaneous - Temporal proximity relationships (auto-generated)same_location - Geographic co-location relationships (auto-generated)thematic - Shared tag/theme relationships (auto-generated) Example: { "causes" : 450 , "contemporaneous" : 12500 , "same_location" : 3200 , "thematic" : 8900 }
Node count grouped by data source type Keys are source type identifiers, values are node counts:
historical - Manually curated historical datawikipedia - Imported from Wikipediaflash - User-generated flash timepointsOther custom source identifiers
Example: { "historical" : 5600 , "wikipedia" : 2300 , "flash" : 890 }
Example Request curl -X GET "https://api.timepointclockchain.com/stats" \ -H "X-Service-Key: your_service_key"
Example Response { "total_nodes" : 8790 , "total_edges" : 25050 , "layer_counts" : { "0" : 1250 , "1" : 5200 , "2" : 1890 , "3" : 450 }, "edge_type_counts" : { "causes" : 450 , "contemporaneous" : 15600 , "same_location" : 4200 , "thematic" : 4800 }, "source_type_counts" : { "historical" : 6200 , "wikipedia" : 1800 , "flash" : 790 } }
Use Cases Show Monitoring graph growth
Track total_nodes and total_edges over time to monitor ingestion pipeline performance and graph expansion.
Use layer_counts to understand the distribution of data quality across the graph. Higher layers indicate more complete and curated data.
Show Relationship analysis
Analyze edge_type_counts to understand the composition of relationships. A healthy graph should have a mix of manual causal edges and auto-generated contextual edges.
Monitor source_type_counts to ensure diverse data sources and identify gaps in coverage.
Error Responses Missing or invalid service key { "detail" : "Unauthorized" }
Database error { "detail" : "Internal server error" }
Notes
Statistics are computed in real-time from the database
All counts reflect the current state of the graph
Layer counts use string keys for consistency with JSON serialization
Source types default to "historical" if not explicitly set on nodes