vector-database
vector-database is a RAG & retrieval skill for AI agents, published by kumaran-is in the claude-code-onboarding repository on GitHub. Skillspace rates vector-database C (70/100) and it passed the safety scan; the rating is based on static analysis only.
Use for all vector database work — pgvector schema design, Weaviate collection creation, RAG pipeline scaffolding, embedding model selection, index tuning (HNSW vs IVFFlat), and embedding model migration. Triggers on: 'vector search', 'pgvector', 'weaviate', 'embedding', 'RAG pipeline', 'semantic search', 'hybrid search', 'nearest neighbor', 'vector index', 're-embedding', 'ANN index'. Use whenever vectors, embeddings, or similarity search are involved, even if not explicitly named.
- Grade
- C
- Quality
- 70 / 100
- Safety
- Passed
- GitHub stars
- 32
Unproven: rated by static analysis only, not yet compared head-to-head.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 100 / 100
- Maturity
- Structured: ships references or scripts
- Security scan
- Low-risk patterns
- License
- MIT
- Adoption
- Adopted by 0 other repositories, in 0 collections
What the scanner flagged
- mentions secrets in text
Not checked yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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