Loading...
Loading...
Found 57 Skills
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.
How to write well-structured Basic Memory notes: frontmatter, observations with semantic categories, relations with wiki-links, and best practices for building a rich knowledge graph. Use when creating or improving notes.
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.
Advanced RAG with Self-RAG, Corrective-RAG, and knowledge graphs. Use when building agentic RAG pipelines, adaptive retrieval, or query rewriting.
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.
Manage Draxarp Intelligence — projects, tasks, specs, docs, memories, sprints, knowledge graph, context captures, and task decomposition via orbit CLI
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".
Use when saving or retrieving important patterns, decisions, and learnings across sessions. Triggers on keywords like "remember", "save pattern", "recall", "memory", "persist", "knowledge base", "learnings".
Deep code analysis for pplx-sdk — parse Python AST, build dependency graphs, extract knowledge graphs, detect patterns, and generate actionable insights about code structure, complexity, and relationships. Use when analyzing code quality, mapping dependencies, or building understanding of the codebase.