Loading...
Loading...
Found 97 Skills
Work with ArcGIS Knowledge graphs for storing and querying connected data. Use for graph databases, relationship visualization, and openCypher queries.
Manages persistent Knowledge Graph for specifications. Caches agent discoveries and codebase analysis to remember findings across sessions. Validates task dependencies, stores patterns, components, and APIs to avoid redundant exploration. Use when: you need to cache analysis results, remember findings, reuse previous discoveries, look up what we found, spec-to-tasks needs to persist codebase analysis, task-implementation needs to validate contracts, or any command needs to query existing patterns/components/APIs.
Use when designing and building knowledge graphs from unstructured data. Invoke when user mentions entity extraction, schema design, LPG vs RDF, graph data model, ontology alignment, knowledge graph construction, or building a KG for RAG. Provides extraction pipelines, schema patterns, and data model selection guidance.
Turn any codebase into an interactive knowledge graph using Claude Code skills — explore, search, and ask questions about any project visually.
Implements knowledge graphs for AI-enhanced relational knowledge. Covers ontology design, graph database selection (Neo4j, Neptune, ArangoDB, TigerGraph), entity extraction, hybrid graph-vector architecture, query patterns, and AI integration. Use when implementing knowledge graphs, designing ontologies, extracting entities and relationships, selecting a graph database, or building hybrid graph-vector search. Use for knowledge graph, ontology design, entity resolution, graph RAG, hallucination detection. For architecture selection and governance, use the knowledge-base-manager skill. For document retrieval pipelines, use the rag-implementer skill.
Organize research, discussions, and exploratory content into systematic knowledge documents, or collect and organize research information about companies/products. Use this skill when users request knowledge summarization, note organization, knowledge base document generation, or structuring discussion content into formal documents. It also applies to collecting and organizing research information about AI companies, startups, and products. Even if users don't explicitly mention "knowledge graph" or "knowledge base", this skill should be used for any workflow that involves sorting scattered information into systematic documents.
9 knowledge graphs skills. Trigger: building knowledge graphs, connecting concepts, ontology design. Design: graph construction, traversal, and visualization for research knowledge.
Knowledge graph specialist for entity and causal relationship modelingUse when "knowledge graph, graph database, falkordb, neo4j, cypher query, entity resolution, causal relationships, graph traversal, graph-database, knowledge-graph, falkordb, neo4j, cypher, entity-resolution, causal-graph, ml-memory" mentioned.
Build a graph-structured dossier on a seed entity via parallel fan-out + recursive expansion across web, memory, knowledge-graph, codebase, ADR index, and git intel
Inspect and debug KGF (Knowledge Graph Framework) specs — tokenize, parse, and extract edges from source files. Use when the user wants to debug language parsing, inspect how indexion processes a file, or verify KGF spec behavior.
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.
Hybrid memory strategy combining OpenClaw's built-in QMD vector memory with Graphiti temporal knowledge graph. Use for all memory recall requests.