Databases · pgvector

Gives the agent Postgres rules to consult before writing or changing tables, queries, indexes, RLS policies or migrations, and when diagnosing slow queries.

supabase/agent-skills

A skill your agent uses for setting up vector similarity search with pgvector for AI/ML embeddings, RAG applications, or semantic search.

timescale/pg-aiguide

A skill your agent uses to implement hybrid search combining BM25 keyword search with semantic vector search using Reciprocal Rank Fusion (RRF).

timescale/pg-aiguide

GAIK toolkit overview and reference. An agent skill from GAIK-project/gaik-toolkit.

GAIK-project/gaik-toolkit

Build retrieval-augmented generation systems: pick a vector database and embedding model, choose retrieval and reranking strategies, and start from a LangGraph pipeline.

wshobson/agents

Smart retrieval from Ogham shared memory. An agent skill from ogham-mcp/ogham-mcp.

ogham-mcp/ogham-mcp

A skill your agent uses for any PostgreSQL database work — table design, indexing, data types, constraints, extensions (pgvector, PostGIS, TimescaleDB), search, and migrations.

timescale/pg-aiguide

Tunes and administers PostgreSQL: EXPLAIN-driven query tuning, index choice, JSONB, extensions, streaming or logical replication, VACUUM and pg_stat monitoring.

Jeffallan/claude-skills

Guides database architecture for PostgreSQL, DuckDB, Parquet, PGVector, and Neo4j.

rileyhilliard/claude-essentials

Hunt vector-store / embedding-layer weaknesses in RAG pipelines (OWASP LLM08 Vector and Embedding Weaknesses) — persistent corpus poisoning that survives across sessions and users (distinct from…

elementalsouls/Claude-BugHunter

Deploy, manage, and optimize vector databases for AI applications.

sickn33/agentic-awesome-skills

Vector database implementation for AI/ML applications, semantic search, and RAG systems.

ancoleman/ai-design-components

Self-hosted semantic memory for AI agents via MCP. An agent skill from sickn33/agentic-awesome-skills.

sickn33/agentic-awesome-skills

Build production RAG pipelines and persistent agent memory using Pinecone as the vector database backend.

github/awesome-copilot

Security-first SOP for multi-tenant RAG systems. An agent skill from agentsope/SkillAlchemy.

agentsope/SkillAlchemy

Expert in vector databases, embedding strategies, and semantic search implementation.

aiskillstore/marketplace

Amazon Aurora PostgreSQL — creates, modifies, and advises on Aurora PostgreSQL clusters specifically (PostgreSQL-compatible engine, Aurora serverless, express configuration, pgvector, Babelfish).

aws/agent-toolkit-for-aws

Connect to Supabase for database operations, vector search, and storage.

sundial-org/awesome-openclaw-skills

A skill your agent uses when operating a vector store as a data layer — choosing or migrating between Pinecone, Qdrant, Weaviate and pgvector; designing a collection or index (distance metric…

ericrisco/rsc-harness

Provides configuration patterns for LangChain4J vector stores in RAG applications.

giuseppe-trisciuoglio/developer-kit

Administrative operations on the Knowledge base: connect new pgvector servers, check health, view stats, export data, install parser models.

evolution-foundation/evo-nexus