Amo.ng
Amo.ng is a public AI prompt library that provides a curated collection of advanced, copy-ready prompts for popular AI tools like ChatGPT, Claude, Gemini, and Codex. The platform is designed for practical workflows across coding, SEO, business, automation, research, education, and productivity. Users can browse prompts by category, tool, and difficulty without any signup or paywall. Each prompt includes context, constraints, output formats, verification steps, and next actions to ensure high-quality AI interactions. The library is regularly updated and focuses on expert-level templates that save time and improve results for serious AI users.
- Category
- Prompt Engineering
- Pricing
- Free
Problem solved
Finding effective, well-structured prompts for AI tools is time-consuming and often requires trial and error. Amo.ng solves this by offering a free, searchable library of ready-to-use prompts that are designed with practical constraints and output specifications, enabling users to immediately apply them to real-world tasks without needing deep prompt engineering skills.
Use cases
- Debugging and refactoring code with AI assistants
- Creating SEO content strategies and blog outlines
- Mapping business processes for automation
- Designing marketing campaigns and landing page copy
- Building no-code automation workflows
- Planning lessons and assessments for education
- Conducting literature reviews and research synthesis
Audience
- Developers
- Business Users
- Content Creators
- Researchers
- Startups
Pros
- Completely free with no signup required
- Wide range of categories covering coding, business, SEO, and more
- Prompts include context, constraints, and output formats for better results
- Easy to browse and copy prompts instantly
- Regularly updated with new prompts
Cons
- No ability to save or favorite prompts without an account
- Lacks community features like ratings or comments
- No API for programmatic access
- Prompt quality may vary as it's a public library
- Limited to the categories currently available
Official website: https://amo.ng/
Canonical LambdaBase page: https://www.lambdabase.com/tools/amo-ng