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Found 97 Skills
Builds and queries code knowledge graph for dependency analysis, references, implementations, and architecture overview. Use when starting work on unfamiliar codebase or before refactoring.
This skill should be used when the user asks to "implement agent memory", "persist state across sessions", "build knowledge graph", "track entities", or mentions memory architecture, temporal knowledge graphs, vector stores, entity memory, or cross-session persistence.
Expert in aggregating, processing, and synthesizing information from multiple sources into coherent insights. Use when building knowledge graphs, ontologies, RAG systems, or extracting insights across documents. Triggers include "knowledge graph", "ontology", "synthesize information", "GraphRAG", "insight extraction", "cross-document analysis".
Advanced RAG with Self-RAG, Corrective-RAG, and knowledge graphs. Use when building agentic RAG pipelines, adaptive retrieval, or query rewriting.
Typed knowledge graph for structured agent memory and composable skills. Use when creating/querying entities (Person, Project, Task, Event, Document), linking related objects, enforcing constraints, planning multi-step actions as graph transformations, or when skills need to share state. Trigger on "remember", "what do I know about", "link X to Y", "show dependencies", entity CRUD, or cross-skill data access.
Implement GraphRAG patterns combining knowledge graphs with retrieval for complex reasoning. Use this skill when building RAG over interconnected data or needing relationship-aware retrieval. Activate when: GraphRAG, knowledge graph, graph retrieval, entity relationships, Neo4j RAG, graph database, connected data.
Comprehensive skill for Graphiti and Zep - temporal knowledge graph framework for AI agents with dynamic context engineering
Intelligent multi-store memory system with human-like encoding, consolidation, decay, and recall. Use when setting up agent memory, configuring remember/forget triggers, enabling sleep-time reflection, building knowledge graphs, or adding audit trails. Replaces basic flat-file memory with a cognitive architecture featuring episodic, semantic, procedural, and core memory stores. Supports multi-agent systems with shared read, gated write access model. Includes philosophical meta-reflection that deepens understanding over time. Covers MEMORY.md, episode logging, entity graphs, decay scoring, reflection cycles, evolution tracking, and system-wide audit.
Manage Draxarp Intelligence — projects, tasks, specs, docs, memories, sprints, knowledge graph, context captures, and task decomposition via orbit CLI
Analyze a complete literary work into a structured Basic Memory knowledge graph. Covers schema design, entity seeding, chapter-by-chapter processing, cross-referencing, validation, and visualization.
Automatically find relevant context from knowledge graph and code relationships while coding. Detects when context would be helpful (new files, unfamiliar code, architectural decisions) and surfaces related entities, prior decisions, and code dependencies.
CLI for Limitless.ai Pendant with lifelog management, FalkorDBLite semantic graph, vector embeddings, and DAG pipelines. Use for personal memory queries, semantic search across lifelogs/chats/persons/topics, entity extraction, and knowledge graph operations. Triggers include "lifelog", "pendant", "limitless", "personal memory", "semantic search", "graph query", "extraction".