Optimize AI Agents with Cozeloop
Cozeloop streamlines AI agent development by providing a full-lifecycle management platform for development, debugging, evaluation, and monitoring of AI agents.
- •When building a complex AI system that requires multi-stage development and testing
- •When needing to monitor and evaluate AI agent performance in real-time
- •When requiring a unified platform for AI agent development, debugging, and deployment
cozeloop agent create --name my_agent --type reinforcement_learning --env cartpole
Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.
Expect 20–40 minutes in a terminal — or let your AI agent drive it.
mkdir -p ~/.claude/skills/coze-loop && curl -fsSL https://workflowstacks.com/api/skills/coze-loop/claude-skill -o ~/.claude/skills/coze-loop/SKILL.mdOpens the app with this repo with the prompt ready to go — no copy-paste needed.
Optimize AI Agents with Cozeloop is a very large Go project (~914k lines across 4444 code files, plus 65 test files). It is a full software project: use it through its install path rather than reading it end to end. Last commit this month, Apache-2.0 license, has a test suite.
Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.
Expect 20–40 minutes in a terminal — or let your AI agent drive it.
mkdir -p ~/.claude/skills/coze-loop && curl -fsSL https://workflowstacks.com/api/skills/coze-loop/claude-skill -o ~/.claude/skills/coze-loop/SKILL.mdOpens the app with this repo with the prompt ready to go — no copy-paste needed.
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