59.5KGitHub
OPENAGENTSKILL / DIRECTORY
AI Agent Skills
Find a skill for your next task. Explore tools for Codex, Claude Code, Cursor and more.
Results · “pdf-optimizer”
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Candidates in this shortlist, not the full registry. GitHub stars belong to repositories, not individual skills.
Results: 270
Llm App
pathwaycom
Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data. 🐳Docker-friendly.⚡Always in sync with Sharepoint, Google Drive, S3, Kafka, Pos…
DataSkill source unconfirmed
59.3KGitHub
Meilisearch
meilisearch
A lightning-fast search engine API bringing AI-powered hybrid search to your sites and applications.
ResearchSkill source unconfirmed
58.6KGitHub
53.6KGitHub
Milvus
milvus-io
Milvus is a high-performance, cloud-native vector database built for scalable vector ANN search
DataSkill source unconfirmed
44.8KGitHub
Tidb
pingcap
TiDB is built for agentic workloads that grow unpredictably, with ACID guarantees and native support for transactions, analytics, and vector search. No data silos. No no…
DataSkill source unconfirmed
40.2KGitHub
36.8KGitHub
Trilium
TriliumNext
Build your personal knowledge base with Trilium Notes
ResearchSkill source unconfirmed
36.5KGitHub
Khoj
khoj-ai
Your AI second brain. Self-hostable. Get answers from the web or your docs. Build custom agents, schedule automations, do deep research. Turn any online or local LLM int…
35.3KGitHub
33.9KGitHub
Qdrant
qdrant
Qdrant - 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/
ResearchSkill source unconfirmed
33.4KGitHub
Searxng
searxng
SearXNG is a free internet metasearch engine which aggregates results from various search services and databases. Users are neither tracked nor profiled.
ResearchSkill source unconfirmed
32.2KGitHub
30.3KGitHub
Sim
simstudioai
Build, deploy, and orchestrate AI agents. Sim is the central intelligence layer for your AI workforce.
29.1KGitHub
RAG Techniques
NirDiamant
This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. Each technique has a detailed notebook tutorial.
28.1KGitHub
27.7KGitHub