by intelligencedev · Agent Tool · ★ 496
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Manifold Manifold is an experimental platform for long-horizon workflow automation with teams of AI assistants. It supports OpenAI, Google, and Anthropic models, along with OpenAI-compatible APIs for self-hosted open-weight models served through llama.cpp or vLLM. [!WARNING] Manifold is an experimental frontier AI platform. Do not deploy it in production environments that require strong stability guarantees unless this README explicitly states otherwise. What Manifold does Manifold is built for workflows that go beyond one-shot prompts. It gives you a workspace where specialists, tools, projects, and workflows can work together on multi-step objectives over extended periods. Features Agent chat Use a traditional chat interface to assign objectives to specialists. Agent specialists can be configured to render visualizations in addition to text responses. Specialists can collaborate across multiple turns. Manifold is designed to take advantage of the long-horizon capabilities of frontier models and can work on complex objectives for hours.
| Stars | 496 |
| Forks | 30 |
| Language | Go |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 67.6470045334137/100 |
| Open Issues | 2 |
| Last Updated | 2026-06-29 |
| Created | 2025-02-04 |
| Platforms | go |
| Est. Tokens | ~17k |
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manifold is Manifold is an experimental platform for enabling long horizon workflow automation using teams of AI assistants.. It is categorized as a Agent Tool with 496 GitHub stars.
manifold is primarily written in Go. It covers topics such as agents, ai-agents, ai-assistant.
You can find installation instructions and usage details in the manifold GitHub repository at github.com/intelligencedev/manifold. The project has 496 stars and 30 forks, indicating an active community.
manifold is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to manifold on Agent Skills Hub include sre, claudepro-directory, agentor. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.