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pgvector · Embeddings

13 skills found.
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1

Persistent compounding memory for AI agents. An agent skill from Goldentrii/AgentRecall-X.

Goldentrii/AgentRecall-X371—~5.2kAutomated safety check: NotesMIT13 days ago
2

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

timescale/pg-aiguide1.9k—~3.8kAutomated safety check: PassApache-2.03 days ago
3

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

wshobson/agents40k9 repos~1.1kAutomated safety check: PassMIT6 days ago
4

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-aiguide1.9k—~941Automated safety check: PassApache-2.03 days ago
5

Builds and debugs retrieval with the gaik toolkit — PgVectorStore, Ranker, FinnishTextProcessor, RelevanceGate — as hybrid search: pgvector similarity plus Postgres full-text, fused by rank, and the…

GAIK-project/gaik-toolkit100—~4.2kAutomated safety check: PassMIT2 days ago
6

Designs retrieval-augmented generation systems: document chunking, embeddings, vector store setup, hybrid search, reranking and retrieval evaluation, with checks at each step.

Jeffallan/claude-skills12k—~2kAutomated safety check: PassMIT8 days ago
7

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-BugHunter4.8k—~2.6kAutomated safety check: PassMITyesterday
8

Probes Retrieval-Augmented Generation pipelines for indirect prompt injection via poisoned retrieved documents and embedding-space manipulation, using NVIDIA garak, Promptfoo red-team plugins, and…

mukul975/Anthropic-Cybersecurity-Skills34k—~3.3kAutomated safety check: PassApache-2.01 mo ago
9

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

aiskillstore/marketplace4337 repos~563Automated safety check: PassNo licenceyesterday
10

RAG: embeddings, chunking, hybrid search (BM25+vector), reranking, CRAG, multi-hop.

softspark/ai-toolkit179—~1.8kAutomated safety check: PassApache-2.03 days ago
11

Build and query vector stores with LangChain 1.0 without getting burned by flipped score semantics, embedding-dim mismatches, reranker quirks, and chunk-splitter bugs.

jeremylongshore/tons-of-skills-marketplace2.8k—~2.6kAutomated safety check: PassMITyesterday
12

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-harness180—~2.8kAutomated safety check: PassMIT2 days ago
13

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

sundial-org/awesome-openclaw-skills663—~1.6kAutomated safety check: PassNo licence7 mo ago