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---
description: LLM-friendly markdown format for notes directories
globs: notes/**/*.md,**/notes/**/*.md
alwaysApply: true
---
# Instructions for Generating LLM-Optimized Markdown Content
When creating or editing markdown files within the specified directories, adhere to the following guidelines to ensure the content is optimized for LLM understanding and efficient token usage:
1. **Conciseness and Clarity**:
- **Be Brief**: Present information succinctly, avoiding unnecessary elaboration.
- **Use Clear Language**: Employ straightforward language to convey ideas effectively.
2. **Structured Formatting**:
- **Headings**: Utilize markdown headings (`#`, `##`, `###`, etc.) to organize content hierarchically.
- **Lists**: Use bullet points (`-`) or numbered lists (`1.`, `2.`, etc.) to enumerate items clearly.
- **Code Blocks**: Enclose code snippets within triple backticks (```) to distinguish them from regular text.
3. **Semantic Elements**:
- **Emphasis**: Use asterisks (`*`) or underscores (`_`) for italicizing text to denote emphasis.
- **Strong Emphasis**: Use double asterisks (`**`) or double underscores (`__`) for bold text to highlight critical points.
- **Inline Code**: Use single backticks (`) for inline code references.
4. **Linking and References**:
- **Hyperlinks**: Format links using `[Link Text](mdc:URL)` to provide direct access to external resources.
- **References**: When citing sources, use footnotes or inline citations to maintain readability.
5. **Avoid Redundancy**:
- **Eliminate Repetition**: Ensure that information is not unnecessarily repeated within the document.
- **Use Summaries**: Provide brief summaries where detailed explanations are not essential.
6. **Standard Compliance**:
- **llms.txt Conformance**: Structure the document in alignment with the `llms.txt` standard, which includes:
- An H1 heading with the project or site name.
- A blockquote summarizing the project's purpose.
- Additional markdown sections providing detailed information.
- H2-delimited sections containing lists of URLs for further details.
By following these guidelines, the markdown files will be tailored for optimal LLM processing, ensuring that the content is both accessible and efficiently tokenized for AI applications.
For more information on the `llms.txt` standard, refer to the official documentation: https://llmstxt.org/
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