--- title: "awesome-prompts vs awesome" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/ai-boost-awesome-prompts-vs-sindresorhus-awesome" tools: ["ai-boost-awesome-prompts", "sindresorhus-awesome"] --- # awesome-prompts vs awesome *GraphCanon updated Jul 12, 2026* ## Verdict Pick awesome-prompts when license: awesome-prompts is GPL-3.0, awesome is CC0-1.0; pick awesome when license: awesome is CC0-1.0, awesome-prompts is GPL-3.0. [awesome-prompts](https://awesomegpt.vip) reports 8.4k GitHub stars, 798 forks, and 35 open issues, last pushed Jul 11, 2026. [awesome](https://github.com/sindresorhus/awesome) has 484k stars, 36k forks, and 92 open issues, last pushed Jun 30, 2026. Figures are from public GitHub metadata via [awesome-prompts's repository](https://github.com/ai-boost/awesome-prompts) and [awesome's repository](https://github.com/sindresorhus/awesome). | | [awesome-prompts](/tools/ai-boost-awesome-prompts.md) | [awesome](/tools/sindresorhus-awesome.md) | | --- | --- | --- | | Tagline | Curated list of chatgpt prompts from the top-rated GPTs in the GPTs Store. Prompt Engineering, prompt attack & prompt protect. Advanced Prompt Engineering papers. | 😎 Curated list of awesome topics including hardware resources | | Stars | 8,440 | 484,026 | | Forks | 798 | 35,799 | | Open issues | 35 | 92 | | Language | - | - | | Adopt for | - | - | | Persona | - | - | | Runtime | - | - | | License | GPL-3.0 | CC0-1.0 | | Categories | LLM Frameworks | LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [awesome-prompts](/tools/ai-boost-awesome-prompts.md) | [awesome](/tools/sindresorhus-awesome.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Active (82%) | | Days since push | 0d | 11d | | Open issues (now) | 35 | 92 | | Full report | [trust report](/tools/ai-boost-awesome-prompts/trust.md) | [trust report](/tools/sindresorhus-awesome/trust.md) | ## Choose when ### Choose awesome-prompts if… - License: awesome-prompts is GPL-3.0, awesome is CC0-1.0. - Tags unique to awesome-prompts: awesome, chatgpt, gpt4, gpts. - More recently updated (last pushed Jul 11, 2026). ### Choose awesome if… - License: awesome is CC0-1.0, awesome-prompts is GPL-3.0. - Tags unique to awesome: resources. - More GitHub stars (484k vs 8.4k) - visibility, not fit. ## When NOT to use awesome-prompts - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ## When NOT to use awesome - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ## Common questions ### What is the difference between awesome-prompts and awesome? awesome-prompts: Curated list of chatgpt prompts from the top-rated GPTs in the GPTs Store. Prompt Engineering, prompt attack & prompt protect. Advanced Prompt Engineering papers.. awesome: 😎 Curated list of awesome topics including hardware resources. See the comparison table for live GitHub stats and shared categories. ### When should I choose awesome-prompts over awesome? Choose awesome-prompts over awesome when License: awesome-prompts is GPL-3.0, awesome is CC0-1.0; Tags unique to awesome-prompts: awesome, chatgpt, gpt4, gpts; More recently updated (last pushed Jul 11, 2026). ### When should I choose awesome over awesome-prompts? Choose awesome over awesome-prompts when License: awesome is CC0-1.0, awesome-prompts is GPL-3.0; Tags unique to awesome: resources; More GitHub stars (484k vs 8.4k) - visibility, not fit. ### When should I avoid awesome-prompts? LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ### When should I avoid awesome? LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ### Is awesome-prompts or awesome more popular on GitHub? awesome has more GitHub stars (484,026 vs 8,440). Stars measure visibility, not whether either tool fits your constraints. ### Are awesome-prompts and awesome open source? Yes - both are open-source projects on GitHub (awesome-prompts: GPL-3.0, awesome: CC0-1.0). ### Where can I find alternatives to awesome-prompts or awesome? GraphCanon lists graph-backed alternatives at [awesome-prompts alternatives](/tools/ai-boost-awesome-prompts/alternatives) and [awesome alternatives](/tools/sindresorhus-awesome/alternatives) ([awesome-prompts markdown twin](/tools/ai-boost-awesome-prompts/alternatives.md), [awesome markdown twin](/tools/sindresorhus-awesome/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/ai-boost-awesome-prompts-vs-sindresorhus-awesome.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, awesome-prompts or awesome? awesome-prompts: Very active. awesome: Active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for awesome-prompts and awesome? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [awesome-prompts trust report](/tools/ai-boost-awesome-prompts/trust); [awesome trust report](/tools/sindresorhus-awesome/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=ai-boost-awesome-prompts`](/api/graphcanon/graph?tool=ai-boost-awesome-prompts) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_