knowledge-base-manager

Installation
SKILL.md

Knowledge Base Manager

Overview

Provides a structured methodology for selecting, designing, and governing knowledge bases. Covers architecture decisions (document-based vs entity-based vs hybrid), content curation, quality metrics, versioning strategies, and maintenance governance. Use when choosing a KB architecture, establishing curation workflows, or building governance processes for organizational knowledge.

When NOT to use: Static documentation suffices, fewer than 50 FAQ items cover all questions, or no maintenance resources are available. For implementing retrieval pipelines (chunking, embeddings, vector stores), use the rag-implementer skill. For implementing knowledge graphs (ontology, entity extraction, graph databases), use the knowledge-graph-builder skill.

Quick Reference

Aspect Options Key Considerations
Architecture Document-based (RAG), Entity-based (Graph), Hybrid Match to query patterns; start simple, add complexity when needed
Document-based Vector DB (Pinecone, Weaviate, pgvector) Best for docs, FAQs, manuals; semantic search; easy to add content
Entity-based Graph DB (Neo4j, ArangoDB) Best for org charts, catalogs, networks; relationship traversal
Hybrid Both + linking layer Enterprise, medical, legal; combined queries; highest complexity
When to skip KB Static docs, <50 FAQ items No maintenance resources, information never changes
Implementation 6 phases Audit, Curation, Storage, Quality, Versioning, Governance
Accuracy target >90% on test questions Create 100+ test questions with known correct answers
Related skills
Installs
40
GitHub Stars
11
First Seen
Feb 24, 2026