exploring-knowledge-graph

Solid

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.

AI & Automation 38 stars 13 forks Updated today MIT

Install

View on GitHub

Quality Score: 80/100

Stars 20%
53
Recency 20%
100
Frontmatter 20%
70
Documentation 15%
100
Issue Health 10%
50
License 10%
100
Description 5%
100

Skill Content

# 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. ## Triggers | Trigger Phrase | Operation | |----------------|-----------| | `what do you know about X` | Full knowledge graph traversal | | `how do I explore the knowledge graph` | Graph exploration workflow | | `how are these concepts connected` | Entity relationship traversal | | `give me comprehensive context on X` | Deep multi-phase exploration | | `map out related knowledge for X` | Entity discovery and memory linking | --- ## 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 ```javascript 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: ```javascri...

Details

Author
rjmurillo
Repository
rjmurillo/ai-agents
Created
7 months ago
Last Updated
today
Language
Markdown
License
MIT

Integrates with

Similar Skills

Semantically similar based on skill content — not just same category