documentation-templates

An llms.txt file provides RAG-optimized documentation specifically structured for AI crawlers and agents. It ensures your project documentation is easily indexed and parsed by AI systems, improving AI integration and automated content retrieval.

To structure a README for a new project, use standardized templates that provide pre-defined sections and example-driven content. This ensures your README is scannable, progressively detailed, and clear for both human readers and AI agents.

The best way to write Architecture Decision Records (ADRs) is using standardized templates that enforce consistent structure and clarity. This provides a scannable, example-driven format for capturing architectural choices and project context.

Yes, you can use these templates for JSDoc and TSDoc code comments. They provide specific structure guidelines to help developers document code effectively, ensuring consistent comment formatting across the entire project.

To write API documentation that is easy to scan, apply standardized templates that focus on progressively detailed, example-driven content. This approach ensures API endpoints are clearly defined and accessible for both human readers and automated tools.

A project changelog should include standardized, scannable entries of changes using a pre-defined template structure. This ensures consistency and clarity across project updates, making modifications easy to track for developers and AI agents.