{"name":"ART","description":"Train LLMs to be better agents using RL","url":"https://art.openpipe.ai/","version":"1.0.0","protocolVersion":"0.3","preferredTransport":"HTTP+JSON","supportedInterfaces":[{"url":"https://art.openpipe.ai/","protocolBinding":"HTTP+JSON","protocolVersion":"0.3"}],"provider":{"url":"https://art.openpipe.ai/","organization":"ART"},"documentationUrl":"https://art.openpipe.ai/","capabilities":{"streaming":false,"pushNotifications":false},"defaultInputModes":["text/plain"],"defaultOutputModes":["text/plain"],"skills":[{"id":"openpipe","name":"Openpipe","description":"Use when training LLM-based agents to improve performance and reliability through reinforcement learning. Reach for this skill when building agents that need to learn from experience, fixing specific behaviors, or optimizing multi-turn agentic workflows. Apply ART when you have a task that open-source models can already complete 30% of the time, can be run repeatedly without side effects, and has a quantifiable reward signal.","tags":[],"url":"https://art.openpipe.ai/.well-known/agent-skills/openpipe/skill.md"}]}