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llms-txt-hub serves as a central directory and knowledge base for the emerging llms.txt convention, a simple, text-based way for project owners to communicate preferences to AI tools. It catalogs implementations across projects and platforms, helping maintain a shared understanding of how LLM-powered services should interact with code and documentation. The repository aims to standardize patterns for allowlists, denylists, attribution, rate expectations, and contact information, mirroring the spirit of robots.txt for the AI era. It provides examples and templates to make adoption straightforward for maintainers of websites, docs portals, and repos. The hub encourages community debate and iteration so conventions remain practical as tooling evolves. By consolidating examples and tools, it accelerates consistent, respectful AI consumption of public content.
Features
- Directory of real-world llms.txt implementations and examples
- Templates and guidance to help maintainers publish clear policies
- Shared vocabulary for permissions, attribution, and contact details
- Community discussion to evolve the convention pragmatically
- References to tooling that reads or validates llms.txt files
- On-ramp for organizations to communicate AI access preferences
Project Samples
