Database
Pinecone agent skills for Claude Code, Codex and other agents.
- skills
- 27
- official
- 2
- Type
- Database
- Website
- pinecone.io
- Official GitHub
- pinecone-io
- Reviews
- See Pinecone on Enlisted
Pinecone skills, ranked
Ranked by score. Sort bymost stars,trending,newest,recently updated
Official (2 skills)
| # | Skill | Repository | Stars | Used in | Tokens | Auto-check | Licence | Updated |
|---|---|---|---|---|---|---|---|---|
| 1 | INVOKE THIS SKILL when building ANY retrieval-augmented generation (RAG) system. | langchain-ai/ | 1.3k | 1 repo | ~3.9k | Automated safety check: Pass | MIT | yesterday |
| 2 | Build production RAG pipelines and persistent agent memory using Pinecone as the vector database backend. | github/ | 40k | — | ~2.4k | Automated safety check: Pass | Apache-2.0 | today |
Community
| # | Skill | Repository | Stars | Used in | Tokens | Auto-check | Licence | Updated |
|---|---|---|---|---|---|---|---|---|
| 3 | Fetches current documentation for third-party APIs and SDKs with the chub CLI before the agent writes code against them, instead of relying on remembered API shapes. | andrewyng/ | 14k | 2 repos | ~775 | Automated safety check: Pass | MIT | 4 mo ago |
| 4 | Guide to using and contributing cognee community packages: database adapters, data-source connectors, custom tasks and retrievers, and Keywords AI observability. | topoteretes/ | 32k | — | ~1.2k | Automated safety check: Pass | Apache-2.0 | today |
| 5 | Shows how to use Pinecone, a managed vector database, for production RAG, semantic search and recommendations: indexes, upserts, queries, filters and namespaces. | Orchestra-Research/ | 13k | 6 repos | ~2k | Automated safety check: Pass | MIT | 3 mo ago |
| 6 | A skill your agent uses when you need documentation for a third-party library, SDK, or API before writing code that uses it — for example, "use the OpenAI API", "call the Stripe API", "use the… | sudomakes/ | 162 | — | ~1k | Automated safety check: Pass | MIT | 3 mo ago |
| 7 | Designs retrieval-augmented generation systems: document chunking, embeddings, vector store setup, hybrid search, reranking and retrieval evaluation, with checks at each step. | Jeffallan/ | 12k | 1 repo | ~2k | Automated safety check: Pass | MIT | 3 days ago |
| 8 | Build retrieval-augmented generation systems: pick a vector database and embedding model, choose retrieval and reranking strategies, and start from a LangGraph pipeline. | wshobson/ | 40k | 9 repos | ~1.1k | Automated safety check: Pass | MIT | 2 days ago |
| 9 | Memory is the cornerstone of intelligent agents. An agent skill from omer-metin/skills-for-antigravity. | omer-metin/ | 162 | — | ~731 | Automated safety check: Pass | Apache-2.0 | 8 mo ago |
| 10 | Vector database implementation for AI/ML applications, semantic search, and RAG systems. | ancoleman/ | 526 | 1 repo | ~3.5k | Automated safety check: Pass | MIT | 10 mo ago |
| 11 | 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/ | 4.8k | — | ~2.6k | Automated safety check: Pass | MIT | yesterday |
| 12 | 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/ | 34k | — | ~3.3k | Automated safety check: Pass | Apache-2.0 | 1 mo ago |
| 13 | Security-first SOP for multi-tenant RAG systems. An agent skill from agentsope/SkillAlchemy. | agentsope/ | 457 | — | ~9.8k | Automated safety check: Pass | MIT | 1 mo ago |
| 14 | Agent RAG and long-term memory with Pinecone. An agent skill from Luciole-Studio/Misaka-Agent. | Luciole-Studio/ | 125 | 1 repo | ~763 | Automated safety check: Pass | MIT | today |
| 15 | Expert in vector databases, embedding strategies, and semantic search implementation. | aiskillstore/ | 430 | 7 repos | ~563 | Automated safety check: Pass | No licence | today |
| 16 | Provides configuration patterns for LangChain4J vector stores in RAG applications. | giuseppe-trisciuoglio/ | 355 | 1 repo | ~2.7k | Automated safety check: Notes | MIT | 27 days ago |
| 17 | 17.Pinecone Managed vector DB for production RAG and search. An agent skill from Luciole-Studio/Misaka-Agent. | Luciole-Studio/ | 125 | 1 repo | ~2.1k | Automated safety check: Pass | MIT | today |
| 18 | Deploy, manage, and optimize vector databases for AI applications. | majiayu000/ | 666 | 3 repos | ~2.1k | Automated safety check: Pass | MIT | today |
| 19 | Save a single piece of brand knowledge — a campaign learning, guideline, competitive finding, performance insight, or approved asset — to the persistent memory layer with SHA-256 deduplication… | indranilbanerjee/ | 854 | 1 repo | ~2.2k | Automated safety check: Pass | MIT | 3 days ago |
| 20 | Build GraphRAG retrieval pipelines on Neo4j using the neo4j-graphrag Python package (v1.22.0+). | neo4j-contrib/ | 114 | — | ~4.2k | Automated safety check: Notes | MIT | today |
| 21 | 21.RAG Patterns RAG: embeddings, chunking, hybrid search (BM25+vector), reranking, CRAG, multi-hop. | softspark/ | 179 | — | ~1.8k | Automated safety check: Pass | Apache-2.0 | today |
| 22 | 22.Vector DB 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/ | 156 | — | ~2.8k | Automated safety check: Pass | MIT | today |
| 23 | 23.Pinecone Managed vector database for production RAG — serverless and pod-based deployment, hybrid search, namespaces, and metadata filtering. | AlexAI-MCP/ | 135 | — | ~954 | Automated safety check: Pass | MIT | 6 mo ago |
| 24 | 24.Pp Pinecone Every Pinecone API feature, plus local sync, snapshot history, and text-first search no other Pinecone tool has. | mvanhorn/ | 2.1k | — | ~9.7k | Automated safety check: Notes | Apache-2.0 | yesterday |
| 25 | Hybrid search combining semantic and keyword retrieval for RAG pipelines. | majiayu000/ | 666 | 1 repo | ~1.9k | Automated safety check: Notes | MIT | today |
| 26 | Semantic search over critical minerals PDF corpus — rare earth, lithium, cobalt, nickel supply chain, trade policy, extraction, and materials research via Pinecone | lamm-mit/ | 244 | — | ~776 | Automated safety check: Pass | Apache-2.0 | 1 mo ago |
| 27 | RAG system design covering document chunking strategies, embedding model selection, vector database selection (Pinecone, Weaviate, Chroma, pgvector), retrieval strategies (hybrid search… | FerroxLabs/ | 608 | — | ~4.2k | Automated safety check: Pass | Apache-2.0 | yesterday |
Questions, answered from the data.
What is the best Pinecone skill?
Langchain RAG (official) from langchain-ai/langchain-skills ranks first of the 27 Pinecone skills listed here, with the highest score: its repository has 1.3k GitHub stars, 1 other GitHub owner carry a copy, its SKILL.md loads about 3.9k tokens and it passes the automated safety check with no findings. Next come Pinecone RAG and Get API Docs with chub.
Is there an official Pinecone skill?
2 of the 27 Pinecone skills are official, published by the vendor's own GitHub organization: Langchain RAG and Pinecone RAG.
How are these skills ranked?
By Skill Navigator score, which combines the GitHub stars of the skill's repository (shared across that repo's skills and discounted for large collections), how many other GitHub owners carry a copy of the skill, and automated SKILL.md quality checks, minus penalties for safety-check warnings and for each further skill from the same repository. Skills that fail the safety check are not listed.