Search and record institutional knowledge in Graphiti memory graphs.
npx skills add https://github.com/Shakudo-io/opencode-skills --skill graphiti-memory
Please help me install this Agent Skill. Skill: graphiti-memory Source: https://github.com/Shakudo-io/opencode-skills/tree/main/graphiti-memory Command: npx skills add https://github.com/Shakudo-io/opencode-skills --skill graphiti-memory
Graphiti memory enables unified search and persistent recording of institutional knowledge, reducing time spent hunting for context and duplicating solutions.
Query Graphiti to search for relevant knowledge before solving problems and then record verified solutions.
High-intent search queries and answers about installing and using this skill.
Semantic search recording captures verified solutions and architectural decisions by using the add_memory function to store context within platform-wide or project-specific memory graphs. This enables persistent retrieval of institutional knowledge.
Searching a knowledge graph for past incident diagnoses involves using semantic search functions like search_nodes and search_memory_facts to retrieve relevant context from Graphiti memory graphs. This reduces time spent hunting for historical solutions.
Yes, FalkorDB is required as the backend for Graphiti memory. You must have FalkorDB configured with vector indexes to enable semantic search and memory recording functions for capturing customer insights and architectural decisions.
Yes, semantic memory supports documenting verified solutions across multiple project-specific memory graphs like monorepo-project-memory or business-automation-project-memory. You can link knowledge to specific projects and search across them.
The get_episodes function retrieves recorded memory episodes from Graphiti memory graphs, allowing you to access chronological context of previously documented architectural decisions, customer insights, and incident diagnoses.
A knowledge graph provides semantic search and unified persistent recording, linking architectural decisions and verified solutions across project memories. This reduces duplicating solutions and context hunting compared to standard document search.
FalkorDBCreate and query HNSW vector indexes in FalkorDB graph databases.
eykdDocument technical problems, causes, solutions, and prevention measures in categorized directories.
madeinoz67Manage a personal knowledge graph with Graphiti and Neo4j/FalkorDB backends.
felipeganameImplement semantic vector search with AgentDB for document retrieval and similarity matching.
