Generates a specification-compliant llms.txt file that guides LLMs through repository structure and documentation.
Works with
Analyzes repository layout, identifies key files (READMEs, specs, examples, configuration), and catalogs documentation structure before generation
Creates llms.txt following the official specification at https://llmstxt.org/ with H1 project name, blockquote summary, and organized H2 file sections
Organizes files into logical categories (Documentation, Specifications, Exa
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versioncreate-llmsExecute the skills CLI command in your project's root directory to begin installation:
Fetches create-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 create-llms. Access via /create-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
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Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Learn new skills, understand complex topics, get expert guidance
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Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Enhance output quality through reviews, suggestions, and refinements
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Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
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Create a new llms.txt file from scratch in the root of the repository following the official llms.txt specification at https://llmstxt.org/. 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.
Create a comprehensive llms.txt file that serves as an entry point for LLMs to understand and navigate the repository effectively. The file must comply with the llms.txt specification and be optimized for LLM consumption while remaining human-readable.
Before creating the llms.txt file, you must complete a thorough analysis:
.md files in /docs/, /spec/, etc.)Based on your analysis, create a structured plan that includes:
The llms.txt file must follow 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 in the repository root/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 created 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
Registry listing for create-llms matched our evaluation — installs cleanly and behaves as described in the markdown.
create-llms is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
We added create-llms from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
create-llms has been reliable in day-to-day use. Documentation quality is above average for community skills.
Keeps context tight: create-llms is the kind of skill you can hand to a new teammate without a long onboarding doc.
Solid pick for teams standardizing on skills: create-llms is focused, and the summary matches what you get after install.
We added create-llms from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
create-llms is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
create-llms reduced setup friction for our internal harness; good balance of opinion and flexibility.
Keeps context tight: create-llms is the kind of skill you can hand to a new teammate without a long onboarding doc.
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