MR
Mayur Rathi
@github
⭐ 34.1k GitHub stars

Update-Llms

Update-Llms是一款learning方向的AI技能,核心价值是Update the llms,可用于解决开发者在learning领域的实际问题,帮助用户提升效率、自动化重复任务或优化工作流。

Update the llms.txt file in the root folder to reflect changes in documentation or specifications following the llms.txt specification at https://llmstxt.org/

Last verified on: 2026-05-30
mkdir -p ./skills/update-llms && curl -sfL https://raw.githubusercontent.com/github/awesome-copilot/main/skills/update-llms/SKILL.md -o ./skills/update-llms/SKILL.md

Run in terminal / PowerShell. Requires curl (Unix) or PowerShell 5+ (Windows).

Skill Content

# Update LLMs.txt File


Update the existing `llms.txt` file in the root of the repository to reflect changes in documentation, specifications, or repository structure. This file provides high-level guidance to large language models (LLMs) on where to find relevant content for understanding the repository's purpose and specifications.


Primary Directive


Update the existing `llms.txt` file to maintain accuracy and compliance with the llms.txt specification while reflecting current repository structure and content. The file must remain optimized for LLM consumption while staying human-readable.


Analysis and Planning Phase


Before updating the `llms.txt` file, you must complete a thorough analysis:


Step 1: Review Current File and Specification

- Read the existing `llms.txt` file to understand current structure

- Review the official specification at https://llmstxt.org/ to ensure continued compliance

- Identify areas that may need updates based on repository changes


Step 2: Repository Structure Analysis

- Examine the current repository structure using appropriate tools

- Compare current structure with what's documented in existing `llms.txt`

- Identify new directories, files, or documentation that should be included

- Note any removed or relocated files that need to be updated


Step 3: Content Discovery and Change Detection

- Identify new README files and their locations

- Find new documentation files (`.md` files in `/docs/`, `/spec/`, etc.)

- Locate new specification files and their purposes

- Discover new configuration files and their relevance

- Find new example files and code samples

- Identify any changes to existing documentation structure


Step 4: Create Update Plan

Based on your analysis, create a structured plan that includes:

- Changes needed to maintain accuracy

- New files to be added to the llms.txt

- Outdated references to be removed or updated

- Organizational improvements to maintain clarity


Implementation Requirements


Format Compliance

The updated `llms.txt` file must maintain this exact structure per the specification:


1. **H1 Header**: Single line with repository/project name (required)

2. **Blockquote Summary**: Brief description in blockquote format (optional but recommended)

3. **Additional Details**: Zero or more markdown sections without headings for context

4. **File List Sections**: Zero or more H2 sections containing markdown lists of links


Content Requirements


#### Required Elements

- **Project Name**: Clear, descriptive title as H1

- **Summary**: Concise blockquote explaining the repository's purpose

- **Key Files**: Essential files organized by category (H2 sections)


#### File Link Format

Each file link must follow: `[descriptive-name](relative-url): optional description`


#### Section Organization

Organize files into logical H2 sections such as:

- **Documentation**: Core documentation files

- **Specifications**: Technical specifications and requirements

- **Examples**: Sample code and usage examples

- **Configuration**: Setup and configuration files

- **Optional**: Secondary files (special meaning - can be skipped for shorter context)


Content Guidelines


#### Language and Style

- Use concise, clear, unambiguous language

- Avoid jargon without explanation

- Write for both human and LLM readers

- Be specific and informative in descriptions


#### File Selection Criteria

Include files that:

- Explain the repository's purpose and scope

- Provide essential technical documentation

- Show usage examples and patterns

- Define interfaces and specifications

- Contain configuration and setup instructions


Exclude files that:

- Are purely implementation details

- Contain redundant information

- Are build artifacts or generated content

- Are not relevant to understanding the project


Execution Steps


Step 1: Current State Analysis

1. Read the existing `llms.txt` file thoroughly

2. Examine the current repository structure completely

3. Compare existing file ref

🎯 Best For

  • Technical writers
  • API documentation teams
  • Claude users
  • GitHub Copilot users
  • Students

💡 Use Cases

  • Generating JSDoc/TSDoc comments
  • Writing README files for new projects
  • Using Update-Llms in daily workflow
  • Automating repetitive learning tasks

📖 How to Use This Skill

  1. 1

    Install the Skill

    Copy the install command from the Terminal tab and run it. The SKILL.md file downloads to your local skills directory.

  2. 2

    Load into Your AI Assistant

    Open Claude or GitHub Copilot and reference the skill. Paste the SKILL.md content or use the system prompt tab.

  3. 3

    Apply Update-Llms to Your Work

    Provide context for your task — paste source material, describe your audience, or share existing work to guide the AI.

  4. 4

    Review and Refine

    Edit the AI output for accuracy, tone, and completeness. Add human insight where the AI lacks context.

❓ Frequently Asked Questions

Does it follow my documentation style?

Most documentation skills respect existing style. Provide a style guide or example in your prompt.

How do I install Update-Llms?

Copy the install command from the Terminal tab and run it. The skill downloads to ./skills/update-llms/SKILL.md, ready to use.

Can I customize this skill for my team?

Absolutely. Edit the SKILL.md file to add team-specific instructions, examples, or workflows.

⚠️ Common Mistakes to Avoid

Auto-generating without reviewing

AI documentation can contain inaccuracies. Always verify technical accuracy.

Not reading the full skill

Skills contain important context and edge cases beyond the quick start.

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