Learning Graph Quality Metrics Report¶
Overview¶
- Total Concepts: 496
- Foundational Concepts (no prerequisites, other concepts depend on them): 8
- Terminal Nodes (nothing depends on them, but have prerequisites): 269
- Orphaned Nodes (completely disconnected, no edges): 0
- Concepts with Dependencies: 488
- Average Dependencies per Concept: 1.51
Graph Structure Validation¶
- Valid DAG Structure: ✅ Yes
- Self-Dependencies: None detected ✅
- Cycles Detected: 0
Foundational Concepts¶
These concepts have no prerequisites:
- 4: Node
- 5: Edge
- 56: Data Lake
- 81: Metadata
- 132: Event Log
- 157: LLM Context Window
- 164: Tacit Knowledge
- 457: Large Language Model
Dependency Chain Analysis¶
- Maximum Dependency Chain Length: 14
Longest Learning Path:¶
- Node (ID: 4)
- Node Label (ID: 6)
- Graph Schema (ID: 9)
- Knowledge Graph (ID: 1)
- Enterprise Knowledge Graph (ID: 26)
- Context Problem (ID: 156)
- Context Graph Definition (ID: 176)
- LLM Integration Pattern (ID: 262)
- AI Agent Loop (ID: 312)
- Agent Evaluation (ID: 334)
- Decision Quality Metric (ID: 400)
- Success Criteria Definition (ID: 403)
- ROI Measurement (ID: 404)
- Context Graph ROI Model (ID: 496)
Terminal Nodes Analysis¶
Terminal nodes are concepts that nothing else depends on but have prerequisites. They represent natural endpoints of learning paths — culminating or specialized concepts.
- Total Terminal Nodes: 269 (54.2% of all concepts)
- Healthy Range: 5-40% of total concepts
Concepts at the end of learning paths:
- 15: Path Query
- 18: RDF Lacks Scalability
- 19: Open World Assumption
- 20: Closed World Assumption
- 21: Graph vs Relational Model
- 22: Graph vs Vector Store
- 24: GraphML
- 25: GraphSON
- 30: Canonical Entity Model
- 31: Hub-and-Spoke Graph Architecture
- 32: Federated Graph Architecture
- 35: Stale Edge Detection
- 36: Missing Provenance
- 37: HR Data Graph
- 38: Finance Data Graph
- 39: CRM Graph Integration
- 40: ERP Graph Integration
- 41: Product Catalog Graph
- 42: Operational Log Graph
- 44: Graph ETL Pipeline
...and 249 more
Orphaned Nodes Analysis¶
Orphaned nodes are completely disconnected concepts with no inbound AND no outbound edges. These indicate a quality problem — every concept should connect to the graph.
- Total Orphaned Nodes: 0
✅ No orphaned nodes detected. All concepts are connected to the graph.
Connected Components¶
- Number of Connected Components: 1
✅ All concepts are connected in a single graph.
Indegree Analysis¶
Top 10 concepts that are prerequisites for the most other concepts:
| Rank | Concept ID | Concept Label | Indegree |
|---|---|---|---|
| 1 | 176 | Context Graph Definition | 56 |
| 2 | 26 | Enterprise Knowledge Graph | 29 |
| 3 | 177 | Decision Trace | 20 |
| 4 | 185 | Context Graph Schema | 20 |
| 5 | 58 | Semantic Layer | 17 |
| 6 | 312 | AI Agent Loop | 16 |
| 7 | 3 | Graph Database | 15 |
| 8 | 81 | Metadata | 14 |
| 9 | 157 | LLM Context Window | 14 |
| 10 | 196 | Decision Trace Anatomy | 12 |
Outdegree Distribution¶
| Dependencies | Number of Concepts |
|---|---|
| 0 | 8 |
| 1 | 273 |
| 2 | 187 |
| 3 | 20 |
| 4 | 8 |
Recommendations¶
- ℹ️ High terminal node percentage (54.2%): Consider if some terminal concepts should be prerequisites for advanced concepts
- ✅ DAG structure verified: Graph supports valid learning progressions
Report generated by learning-graph-reports/analyze_graph.py