Search private knowledge
Use these skills to ingest documents, index knowledge, retrieve relevant context, and make agents better at answering with grounded sources.
Try this task
I need my agent to build a RAG workflow over documents and retrieve reliable context.
Agent should be able to
Resolve
Returns the best skill, alternatives, install handoff, risk summary, and safety gate.
Text plan
Plain text version for Codex, Claude Code, Cursor, and custom agent runtimes.
Browse
Open the filtered registry view for this workflow and compare candidates manually.
Recommended workflow
Workflow map
Index documents
Search a knowledge base
Summarize source material
Ground answers in retrieved context
Best first installs
Open-source LLM knowledge platform: turn raw documents into a queryable RAG, an autonomous reasoning agent, and a self-maintaining Wiki.
Install
Human review before install
Risk
Safe to try
Agent fit
CLI + Codex
Updated
Jun 18, 2026
$ npx skills add Tencent/WeKnora📑 PageIndex: Document Index for Vectorless, Reasoning-based RAG
Install
Agent install candidate
Risk
Safe to try
Agent fit
CLI + Codex
Updated
Jul 18, 2026
$ npx skills add VectifyAI/PageIndexQdrant - High-performance, massive-scale Vector Database and Vector Search Engine for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
Install
Agent install candidate
Risk
Safe to try
Agent fit
CLI + Codex
Updated
Jul 18, 2026
$ npx skills add qdrant/qdrantSkill shortlist
A multi-modal vector database that supports upserts and vector queries using unified SQL (MySQL-Compatible) on structured and unstructured data, while meeting the requirements of high concurrency and ultra-low latency.
Low metadata risk · Review the audit page, then allow agent install in a sandboxed workflow.
This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. Each technique has a detailed notebook tutorial.
Review before production · Review the audit page, then allow agent install in a sandboxed workflow.
local-first semantic code search engine
Review before production · Review the audit page, then allow agent install in a sandboxed workflow.
Weaviate is an open-source vector database that stores both objects and vectors, allowing for the combination of vector search with structured filtering with the fault tolerance and scalability of a cloud-native database.
Low metadata risk · Review the audit page, then allow agent install in a sandboxed workflow.
Private AI platform for agents, assistants and enterprise search. Built-in Agent Builder, Deep research, Document analysis, Multi-model support, and API connectivity for agents.
Low metadata risk · Review the audit page, then allow agent install in a sandboxed workflow.
💡 All-in-one AI framework for semantic search, LLM orchestration and language model workflows
Low metadata risk · Review the audit page, then allow agent install in a sandboxed workflow.
Developer-friendly OSS embedded retrieval library for multimodal AI. Search More; Manage Less.
Low metadata risk · Review the audit page, then allow agent install in a sandboxed workflow.
21 Lessons, Get Started Building with Generative AI
Review before production · Review the audit page, then allow agent install in a sandboxed workflow.
Find related notes and excerpts while writing. Your link building copilot displays relevant content in graph + list view. A local embedding model powers semantic search. Zero setup. No API key.
Review before production · Require human approval before installing into a real workspace.
The AI-native database built for LLM applications, providing incredibly fast hybrid search of dense vector, sparse vector, tensor (multi-vector), and full-text.
Low metadata risk · Review the audit page, then allow agent install in a sandboxed workflow.
Semantic search over videos using Gemini Embedding 2 or Qwen3-VL.
Review before production · Review the audit page, then allow agent install in a sandboxed workflow.
Local persistent memory store for LLM applications including claude desktop, github copilot, codex, antigravity, etc.
Low metadata risk · Review the audit page, then allow agent install in a sandboxed workflow.
Fast Open-Source Search & Clustering engine × for Vectors & Arbitrary Objects × in C++, C, Python, JavaScript, Rust, Java, Objective-C, Swift, C#, GoLang, and Wolfram 🔍
Low metadata risk · Review the audit page, then allow agent install in a sandboxed workflow.
Stop renting your intelligence. Own it with AnythingLLM. Everything you need for a powerful local-first agent experience
Low metadata risk · Review the audit page, then allow agent install in a sandboxed workflow.
A lightning-fast search engine API bringing AI-powered hybrid search to your sites and applications.
Review before production · Review the audit page, then allow agent install in a sandboxed workflow.
FAQ
These answers are written for both human builders and agents consuming the Registry API.
Start by comparing WeKnora, PageIndex, Qdrant. OpenAgentSkill ranks them by workflow fit, GitHub adoption, trust score, safety gate, and install readiness.
Yes. Use the linked Registry API prompt to query /api/skills/search with the task: "I need my agent to build a RAG workflow over documents and retrieve reliable context." and retrieve install handoff links for the top results.
No. Start with the highest-fit skill, test it in a sandbox workflow, and add companion skills only when the task needs extra coverage.
Search private knowledge
Use these skills to ingest documents, index knowledge, retrieve relevant context, and make agents better at answering with grounded sources.
Try this task
I need my agent to build a RAG workflow over documents and retrieve reliable context.
Agent should be able to
Resolve
Returns the best skill, alternatives, install handoff, risk summary, and safety gate.
Text plan
Plain text version for Codex, Claude Code, Cursor, and custom agent runtimes.
Browse
Open the filtered registry view for this workflow and compare candidates manually.
Recommended workflow
Workflow map
Index documents
Search a knowledge base
Summarize source material
Ground answers in retrieved context
Best first installs
Open-source LLM knowledge platform: turn raw documents into a queryable RAG, an autonomous reasoning agent, and a self-maintaining Wiki.
Install
Human review before install
Risk
Safe to try
Agent fit
CLI + Codex
Updated
Jun 18, 2026
$ npx skills add Tencent/WeKnora📑 PageIndex: Document Index for Vectorless, Reasoning-based RAG
Install
Agent install candidate
Risk
Safe to try
Agent fit
CLI + Codex
Updated
Jul 18, 2026
$ npx skills add VectifyAI/PageIndexQdrant - High-performance, massive-scale Vector Database and Vector Search Engine for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
Install
Agent install candidate
Risk
Safe to try
Agent fit
CLI + Codex
Updated
Jul 18, 2026
$ npx skills add qdrant/qdrantSkill shortlist
A multi-modal vector database that supports upserts and vector queries using unified SQL (MySQL-Compatible) on structured and unstructured data, while meeting the requirements of high concurrency and ultra-low latency.
Low metadata risk · Review the audit page, then allow agent install in a sandboxed workflow.
This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. Each technique has a detailed notebook tutorial.
Review before production · Review the audit page, then allow agent install in a sandboxed workflow.
local-first semantic code search engine
Review before production · Review the audit page, then allow agent install in a sandboxed workflow.
Weaviate is an open-source vector database that stores both objects and vectors, allowing for the combination of vector search with structured filtering with the fault tolerance and scalability of a cloud-native database.
Low metadata risk · Review the audit page, then allow agent install in a sandboxed workflow.
Private AI platform for agents, assistants and enterprise search. Built-in Agent Builder, Deep research, Document analysis, Multi-model support, and API connectivity for agents.
Low metadata risk · Review the audit page, then allow agent install in a sandboxed workflow.
💡 All-in-one AI framework for semantic search, LLM orchestration and language model workflows
Low metadata risk · Review the audit page, then allow agent install in a sandboxed workflow.
Developer-friendly OSS embedded retrieval library for multimodal AI. Search More; Manage Less.
Low metadata risk · Review the audit page, then allow agent install in a sandboxed workflow.
21 Lessons, Get Started Building with Generative AI
Review before production · Review the audit page, then allow agent install in a sandboxed workflow.
Find related notes and excerpts while writing. Your link building copilot displays relevant content in graph + list view. A local embedding model powers semantic search. Zero setup. No API key.
Review before production · Require human approval before installing into a real workspace.
The AI-native database built for LLM applications, providing incredibly fast hybrid search of dense vector, sparse vector, tensor (multi-vector), and full-text.
Low metadata risk · Review the audit page, then allow agent install in a sandboxed workflow.
Semantic search over videos using Gemini Embedding 2 or Qwen3-VL.
Review before production · Review the audit page, then allow agent install in a sandboxed workflow.
Local persistent memory store for LLM applications including claude desktop, github copilot, codex, antigravity, etc.
Low metadata risk · Review the audit page, then allow agent install in a sandboxed workflow.
Fast Open-Source Search & Clustering engine × for Vectors & Arbitrary Objects × in C++, C, Python, JavaScript, Rust, Java, Objective-C, Swift, C#, GoLang, and Wolfram 🔍
Low metadata risk · Review the audit page, then allow agent install in a sandboxed workflow.
Stop renting your intelligence. Own it with AnythingLLM. Everything you need for a powerful local-first agent experience
Low metadata risk · Review the audit page, then allow agent install in a sandboxed workflow.
A lightning-fast search engine API bringing AI-powered hybrid search to your sites and applications.
Review before production · Review the audit page, then allow agent install in a sandboxed workflow.
FAQ
These answers are written for both human builders and agents consuming the Registry API.
Start by comparing WeKnora, PageIndex, Qdrant. OpenAgentSkill ranks them by workflow fit, GitHub adoption, trust score, safety gate, and install readiness.
Yes. Use the linked Registry API prompt to query /api/skills/search with the task: "I need my agent to build a RAG workflow over documents and retrieve reliable context." and retrieve install handoff links for the top results.
No. Start with the highest-fit skill, test it in a sandbox workflow, and add companion skills only when the task needs extra coverage.