Raven: AI Agent Harness
Raven creates self-improving AI agents that utilize EverOS and MiroThinker for deep research and reasoning, enabling founders to build advanced AI models
- •When you need AI agents that can learn and improve over time
- •When you're working with EverOS and want to integrate MiroThinker's deep research capabilities
- •When you want to build AI models that can reason and make decisions based on complex data
python raven.py --prompt 'Design a marketing strategy for a new sustainable energy startup'
Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.
A prompt/skill package — nothing to install beyond adding it to your AI tool.
mkdir -p ~/.claude/skills/raven && curl -fsSL https://workflowstacks.com/api/skills/raven/claude-skill -o ~/.claude/skills/raven/SKILL.mdOpens the app with this repo with the prompt ready to go — no copy-paste needed.
Raven: AI Agent Harness is a very large Python project (~201k lines across 881 code files, plus 440 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.
- 1README.mdStart here — what it does and how to install it
- 2AGENTS.mdThe instructions the AI actually follows
- 3raven/__main__.pyWhere the program starts running
- 4package.jsonDependencies and the commands it exposes
- 5raven/__init__.pyInside raven/ — the main logic begins here
Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.
A prompt/skill package — nothing to install beyond adding it to your AI tool.
mkdir -p ~/.claude/skills/raven && curl -fsSL https://workflowstacks.com/api/skills/raven/claude-skill -o ~/.claude/skills/raven/SKILL.mdOpens the app with this repo with the prompt ready to go — no copy-paste needed.
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