Annuaire de skills

Découvrez des skills réutilisables pour les AI agents.

Recherchez de vrais skills GitHub par tâche et vérifiez Stars, confiance, audit, catégorie et chemin d’installation avant de les utiliser.

Chaque recommandation reste clairement reliée à son dépôt, son audit et son chemin d’installation.

Résultats de recherche: bedrock

Annuaire en anglais

This repository contains examples for customers to get started using the Amazon Bedrock Service. This contains examples for all available foundational models

1.4K
Stars
85/100
Confiance
Catégorie: rag-knowledgeAudit

A modular and comprehensive solution to deploy a Multi-LLM and Multi-RAG powered chatbot (Amazon Bedrock, Anthropic, HuggingFace, OpenAI, Meta, AI21, Cohere, Mistral) using AWS CDK on AWS

1.4K
Stars
85/100
Confiance
Catégorie: rag-knowledgeAudit

AWS-native chatbot using Bedrock

1.3K
Stars
77/100
Confiance
Catégorie: support-automationAudit

High-performance, resource-efficient Minecraft Java + Bedrock reverse proxy and library with multi-version support. Scalable Velocity/BungeeCord alternative, suitable for both development and large-scale deployments. Proven in production environments, powering our global Connect edge proxy network.

1.0K
Stars
80/100
Confiance
Catégorie: devopsAudit

🚀 AI-powered code review tool for GitHub, GitLab, Bitbucket Cloud, Bitbucket Server, Azure DevOps and Gitea — built with LLMs like OpenAI, Claude, Gemini, Ollama, Bedrock, OpenRouter and Azure OpenAI

475
Stars
70/100
Confiance
Catégorie: developmentAudit

Generative AI Application Builder on AWS facilitates the development, rapid experimentation, and deployment of generative artificial intelligence (AI) applications without requiring deep experience in AI. The solution includes integrations with Amazon Bedrock and its included LLMs, such as Amazon Titan, and pre-built connectors for 3rd-party LLMs.

347
Stars
70/100
Confiance
Catégorie: support-automationAudit

Curated collection of 39 agent skills for healthcare and life sciences workflows, installable via the Agent Skills standard.

10
Stars
66/100
Confiance
Catégorie: researchAudit

Ingests unstructured and semi-structured documents into Neo4j as a knowledge graph.

101
Stars
69/100
Confiance
Catégorie: automationAudit

Opinionated sample on how to build/deploy a RAG web app on AWS powered by Amazon Bedrock and PGVector (on Amazon RDS)

102
Stars
66/100
Confiance
Catégorie: rag-knowledgeAudit