Alternatives
Compare similar skills by workflow fit, trust score, quality, GitHub adoption, maintenance, and install readiness.
Current skill
This sample has the full End2End process of creating RAG application with Prompty and Azure AI Foundry. It includes GPT-4 LLM application code, evaluations, deployment automation with AZD CLI, GitHub actions for evaluation and deployment and intent mapping for multiple LLM task mapping.
The open source AI engineering platform for agents, LLMs, and ML models. MLflow enables teams of all sizes to debug, evaluate, monitor, and optimize production-quality AI applications while controlling costs and managing access to models and data.
$ npx skills add mlflow/mlflow🪢 Open source AI engineering platform: LLM evals, observability, metrics, prompt management, playground, datasets. Integrates with OpenTelemetry, LangChain, OpenAI SDK, LiteLLM, and more. 🍊YC W23
$ npx skills add langfuse/langfuseDebug, evaluate, and monitor your LLM applications, RAG systems, and agentic workflows with comprehensive tracing, automated evaluations, and production-ready dashboards.
$ npx skills add comet-ml/opikPython SDK for Agent AI Observability, Monitoring and Evaluation Framework. Includes features like agent, llm and tools tracing, debugging multi-agentic system, self-hosted dashboard and advanced analytics with timeline and execution graph view
$ npx skills add raga-ai-hub/RagaAI-CatalystRun any open-source LLMs, such as DeepSeek and Llama, as OpenAI compatible API endpoint in the cloud.
$ npx skills add bentoml/OpenLLMBuild, Manage and Deploy AI/ML Systems
$ npx skills add Netflix/metaflowThe easiest way to serve AI apps and models - Build Model Inference APIs, Job queues, LLM apps, Multi-model pipelines, and more!
$ npx skills add bentoml/BentoMLOpen-source observability for your GenAI or LLM application, based on OpenTelemetry
$ npx skills add traceloop/openllmetryShip AI Agents to Google Cloud in minutes, not months. Production-ready templates with built-in CI/CD, evaluation, and observability.
$ npx skills add GoogleCloudPlatform/agent-starter-pack⚙️🦀 Build modular and scalable LLM Applications in Rust
$ npx skills add 0xPlaygrounds/rigEvidently is an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics.
$ npx skills add evidentlyai/evidentlyPlano is an AI-native proxy and data plane for agentic apps — with built-in orchestration, safety, observability, and smart LLM routing so you stay focused on your agents core logic.
$ npx skills add katanemo/planoAI Observability & Evaluation
$ npx skills add Arize-ai/phoenix🧊 Open source LLM observability platform. One line of code to monitor, evaluate, and experiment. YC W23 🍓
$ npx skills add Helicone/heliconeNext-generation AI Agent Optimization Platform: Cozeloop addresses challenges in AI agent development by providing full-lifecycle management capabilities from development, debugging, and evaluation to monitoring.
$ npx skills add coze-dev/coze-loopThe LLM's practical guide: From the fundamentals to deploying advanced LLM and RAG apps to AWS using LLMOps best practices
$ npx skills add PacktPublishing/LLM-Engineers-HandbookHow to choose
Use an alternative when it has a clearer install path, higher trust score, fresher maintenance, or better platform fit for your current agent stack. Keep Contoso Chat if it already passes your workflow test and repository review.
Next step
Open the compare page, test the install commands in a sandbox, and check each repository before using a skill in production.