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⚡Unlocking the Power of LLMs in CAP: Understanding llms.txt and llms-full.txt

Yogananda
Product and Topic Expert
Product and Topic Expert
‎2025 May 18 9:23 AM
850

As AI continues to reshape how we build and interact with software, the SAP Cloud Application Programming Model (CAP) is embracing this shift by introducing two new files: llms.txt and llms-full.txt. These files are designed to enhance the way large language models (LLMs) like SAP Build Code or ChatGPT or any AI IDE understand and interact with CAP documentation and projects.

In this blogpost, we’ll explore what these files are, how they benefit users, how to integrate them into your workflows, and what limitations you should be aware of.2025-05-18_13-42-33.png

LLMs.txt is a new web standard designed to help reasoning engines understand website content better. It addresses the limitations of AI systems by providing a format optimized for AI processing, removing non-essential information, and presenting content more efficiently. The concept was popularized by Mintlify, which added support for LLMs.txt to their docs platform. The file format includes two types: /llms.txt for navigation and structure, and /llms-full.txt for comprehensive documentation. Several tools are available to help generate these files, and their adoption is expected to grow as AI-readability becomes crucial for web content.

 

What exactly is an LLMs.txt file?

LLMs.txt is a markdown file with a specific structure. The specification defines two distinct files:

  1. /llms.txt: A streamlined view of your documentation navigation to help AI systems quickly understand your site’s structure
  2. /llms-full.txt: A comprehensive file containing all your documentation in one place

Benefits for Users

Improved AI Assistance

  • By referencing llms.txt or llms-full.txt in prompts, users can guide LLMs to more relevant and accurate answers. This is especially useful when working with AI tools that support prompt augmentation or retrieval-augmented generation (RAG).

Faster Onboarding

  • New developers can use AI tools enhanced with these files to get up to speed quickly, asking natural language questions and receiving answers grounded in official CAP documentation.

Context-Aware Development

  • When integrated into development environments or chat-based assistants, these files help LLMs provide suggestions, code snippets, and explanations that are aligned with CAP’s best practices.

How to Integrate and Use

  1. Prompt Augmentation: When using an LLM, include a reference to https://cap.cloud.sap/llms.txt in your prompt. For example:

    “Using the documentation at https://cap.cloud.sap/llms.txt, explain how to define a service in CAP.”

  2. RAG Pipelines: If you're building your own AI assistant or chatbot, you can ingest the URLs from llms-full.txt into your vector database or document retriever to enable semantic search over CAP docs.

  3. IDE Integration: Advanced setups can use these files to power AI-based code completion or documentation lookup tools within IDEs like VS Code.

Limitations and Considerations

While llms.txt and llms-full.txt are powerful tools, they come with a few caveats:

Static Nature

  • These files are snapshots of documentation URLs. They don’t automatically reflect real-time changes unless regularly updated.

No Content, Just Links

  • They don’t contain the actual documentation content—only links. LLMs still need access to the linked pages to provide meaningful answers.

Access Control

  • If your AI tool doesn’t have access to the CAP documentation (e.g., due to network restrictions), referencing these files won’t help.

LLM Limitations

  • Even with these files, LLMs may still hallucinate or misinterpret complex CAP concepts if not properly grounded with the actual content.

Final Thoughts

The introduction of llms.txt and llms-full.txt is a forward-thinking move by the CAP team, making it easier for developers to harness the power of AI in their workflows. Whether you're building intelligent assistants, enhancing developer productivity, or simply exploring CAP, these files offer a structured way to bring AI and documentation closer together.

 

Samples of /llms