Guidance for deep knowledge graph traversal across memories, entities, and relationships. Use when needing comprehensive context before planning, investigating connections between concepts, or answering "what do you know about X" questions.
Data & Analytics
98 Stars
7 Forks
Updated Jan 15, 2026, 04:34 PM
Why Use This
This skill provides specialized capabilities for ScottRBK's codebase.
Use Cases
Developing new features in the ScottRBK repository
Refactoring existing code to follow ScottRBK standards
Understanding and working with ScottRBK's codebase structure
---
name: exploring-knowledge-graph
description: Guidance for deep knowledge graph traversal across memories, entities, and relationships. Use when needing comprehensive context before planning, investigating connections between concepts, or answering "what do you know about X" questions.
---
# Exploring the Knowledge Graph
Forgetful stores knowledge as an interconnected graph: memories link to other memories, entities link to memories, and entities relate to each other. Deep exploration reveals context that simple queries miss.
## When to Explore
Explore the knowledge graph when:
- Starting complex work that spans multiple topics
- User asks "what do you know about X"
- Planning requires understanding existing decisions/patterns
- Investigating how concepts connect across projects
- Need comprehensive context, not just top search results
## Exploration Phases
Track visited IDs to prevent cycles. Execute phases sequentially.
### Phase 1: Semantic Entry Point
```
execute_forgetful_tool("query_memory", {
"query": "<topic>",
"query_context": "Exploring knowledge graph for comprehensive context",
"k": 5,
"include_links": true,
"max_links_per_primary": 5
})
```
Collect: `primary_memories` + `linked_memories` (1-hop connections).
### Phase 2: Expand Memory Details
For key memories, get full details:
```
execute_forgetful_tool("get_memory", {"memory_id": <id>})
```
Extract: `document_ids`, `code_artifact_ids`, `project_ids`, additional `linked_memory_ids`.
### Phase 3: Entity Discovery
Find entities linked to discovered projects:
```
execute_forgetful_tool("list_entities", {
"project_ids": [<discovered project ids>]
})
```
You can also explicitly link entities to projects for organizational grouping:
```
execute_forgetful_tool("link_entity_to_project", {
"entity_id": <id>,
"project_id": <id>
})
```
### Phase 4: Entity Relationships
For relevant entities, map relationship graph:
```
execute_forgetful_tool("get_entity_relationships", {
"entity_id": <id>,
"direction": "both"
})
```
Relationship types: works_for, owns, manages, collaborates_with, etc.
### Phase 5: Entity-Linked Memories
For each entity, find all linked memories:
```
execute_forgetful_tool("get_entity_memories", {
"entity_id": <id>
})
```
Returns `{"memory_ids": [...], "count": N}`. Fetch any new memories not already visited.
## Presenting Results
Group findings by type:
**Memories**: Primary (direct matches) -> Linked (1-hop) -> Entity-linked (via entities)
**Entities**: Name, type, relationship count, linked memory count
**Artifacts**: Documents and code snippets found via memory links
**Graph Summary**: Total nodes, key themes, suggested follow-up queries
## Depth Control
- **Shallow** (phases 1-2): Quick context, ~5-15 memories
- **Medium** (phases 1-4): Include entities and relationships
- **Deep** (all phases): Full graph traversal, comprehensive context
Match depth to task complexity. Start shallow, go deeper if context insufficient.
## Efficiency Tips
- Check `truncated` flag from query_memory (8000 token budget)
- Skip Phase 3-5 if no entities exist in discovered projects
- Use `project_ids` filter to scope exploration
- Stop expanding when hitting diminishing returns