Maintain accurate llms.txt files that guide LLMs through repository documentation and structure.
Works with
Analyzes current repository state against the official llms.txt specification to identify outdated, missing, or incorrect file references
Organizes essential documentation into logical H2 sections (Documentation, Specifications, Examples, Configuration, Optional) with properly formatted markdown links
Validates compliance with https://llmstxt.org/ format requirements including H1 header,
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionupdate-llmsExecute the skills CLI command in your project's root directory to begin installation:
Fetches update-llms from github/awesome-copilot and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate update-llms. Access via /update-llms in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
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Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
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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.
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.
Before updating the llms.txt file, you must complete a thorough analysis:
llms.txt file to understand current structurellms.txt.md files in /docs/, /spec/, etc.)Based on your analysis, create a structured plan that includes:
The updated llms.txt file must maintain this exact structure per the specification:
Each file link must follow: [descriptive-name](relative-url): optional description
Organize files into logical H2 sections such as:
Include files that:
Exclude files that:
llms.txt file thoroughlyllms.txt file in the repository root/llms.txt)When adding new content:
When removing outdated content:
When restructuring content:
Example structure for llms.txt:
# [Repository Name]
> [Concise description of the repository's purpose and scope]
[Optional additional context paragraphs without headings]
## Documentation
- [Main README](README.md): Primary project documentation and getting started guide
- [Contributing Guide](CONTRIBUTING.md): Guidelines for contributing to the project
- [Code of Conduct](CODE_OF_CONDUCT.md): Community guidelines and expectations
## Specifications
- [Technical Specification](spec/technical-spec.md): Detailed technical requirements and constraints
- [API Specification](spec/api-spec.md): Interface definitions and data contracts
## Examples
- [Basic Example](examples/basic-usage.md): Simple usage demonstration
- [Advanced Example](examples/advanced-usage.md): Complex implementation patterns
## Configuration
- [Setup Guide](docs/setup.md): Installation and configuration instructions
- [Deployment Guide](docs/deployment.md): Production deployment guidelines
## Optional
- [Architecture Documentation](docs/architecture.md): Detailed system architecture
- [Design Decisions](docs/decisions.md): Historical design decision records
The updated llms.txt file should:
Prerequisites
Time Estimate
15-45 minutes depending on use case complexity
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
github/awesome-copilot
github/awesome-copilot
github/awesome-copilot
github/awesome-copilot
github/awesome-copilot
davila7/claude-code-templates
Solid pick for teams standardizing on skills: update-llms is focused, and the summary matches what you get after install.
update-llms fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Useful defaults in update-llms — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
I recommend update-llms for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
We added update-llms from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Keeps context tight: update-llms is the kind of skill you can hand to a new teammate without a long onboarding doc.
update-llms reduced setup friction for our internal harness; good balance of opinion and flexibility.
Keeps context tight: update-llms is the kind of skill you can hand to a new teammate without a long onboarding doc.
We added update-llms from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Solid pick for teams standardizing on skills: update-llms is focused, and the summary matches what you get after install.
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