--- title: "awesome-prompts vs Awesome-Prompt-Engineering" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/ai-boost-awesome-prompts-vs-promptslab-awesome-prompt-engineering" tools: ["ai-boost-awesome-prompts", "promptslab-awesome-prompt-engineering"] --- # awesome-prompts vs Awesome-Prompt-Engineering *GraphCanon updated Jul 28, 2026* ## Verdict Pick awesome-prompts if awesome-prompts is a collection of rated GPT prompts from the GPTs Store with a focus on engineering, attacks, protections, and academic papers; pick Awesome-Prompt-Engineering if awesome-Prompt-Engineering curates resources tailored for GPT, ChatGPT, PaLM prompt engineering in TypeScript under Apache-2.0 license. [awesome-prompts](https://awesomegpt.vip) reports 8.4k GitHub stars, 798 forks, and 35 open issues, last pushed Jul 11, 2026. [Awesome-Prompt-Engineering](https://discord.gg/m88xfYMbK6) has 6.2k stars, 734 forks, and 94 open issues, last pushed Jul 27, 2026. Figures are from public GitHub metadata via [awesome-prompts's repository](https://github.com/ai-boost/awesome-prompts) and [Awesome-Prompt-Engineering's repository](https://github.com/promptslab/Awesome-Prompt-Engineering). | | [awesome-prompts](/tools/ai-boost-awesome-prompts.md) | [Awesome-Prompt-Engineering](/tools/promptslab-awesome-prompt-engineering.md) | | --- | --- | --- | | Tagline | Curated chatgpt prompts and advanced prompt engineering papers | Hand-curated resources for Prompt Engineering focusing on Generative Pre-trained Transformers | | Stars | 8,440 | 6,197 | | Forks | 798 | 734 | | Open issues | 35 | 94 | | Language | - | TypeScript | | Adopt for | awesome-prompts is a collection of rated GPT prompts from the GPTs Store with a focus on engineering, attacks, protections, and academic papers. | Awesome-Prompt-Engineering curates resources tailored for GPT, ChatGPT, PaLM prompt engineering in TypeScript under Apache-2.0 license. | | Persona | - | - | | Runtime | - | - | | License | GPL-3.0 | Apache-2.0 | | Categories | Developer Tools | Developer Tools, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [awesome-prompts](/tools/ai-boost-awesome-prompts.md) | [Awesome-Prompt-Engineering](/tools/promptslab-awesome-prompt-engineering.md) | | --- | --- | --- | | Open issues (now) | 35 | 94 | | Owner type | User | Organization | | Full report | [trust report](/tools/ai-boost-awesome-prompts/trust.md) | [trust report](/tools/promptslab-awesome-prompt-engineering/trust.md) | ## Decision facts: awesome-prompts - **Adopt for:** awesome-prompts is a collection of rated GPT prompts from the GPTs Store with a focus on engineering, attacks, protections, and academic papers. ## Decision facts: Awesome-Prompt-Engineering - **Adopt for:** Awesome-Prompt-Engineering curates resources tailored for GPT, ChatGPT, PaLM prompt engineering in TypeScript under Apache-2.0 license. ## Choose when ### Choose awesome-prompts if… - License: awesome-prompts is GPL-3.0, Awesome-Prompt-Engineering is Apache-2.0. - Tags unique to awesome-prompts: awesome-list, prompt-attack, prompt-protect. - Need detailed prompt engineering resources ### Choose Awesome-Prompt-Engineering if… - License: Awesome-Prompt-Engineering is Apache-2.0, awesome-prompts is GPL-3.0. - Tags unique to Awesome-Prompt-Engineering: deep-learning, few-shot-learning, gpt, machine-learning. - Also covers Model Training. - You need focused materials on GPT and related models for prompt engineering ## When NOT to use awesome-prompts - Seeking a platform for generating new prompts rather than reviewing existing ones - In search of direct support tools or services, not just informational content - Requiring real-time collaboration on prompt creation and experimentation ## When NOT to use Awesome-Prompt-Engineering - The project requires languages other than TypeScript - Resource is about areas outside of GPT, ChatGPT, PaLM prompt engineering ## Common questions ### What is the difference between awesome-prompts and Awesome-Prompt-Engineering? awesome-prompts: Curated chatgpt prompts and advanced prompt engineering papers. Awesome-Prompt-Engineering: Hand-curated resources for Prompt Engineering focusing on Generative Pre-trained Transformers. See the comparison table for live GitHub stats and shared categories. ### When should I choose awesome-prompts over Awesome-Prompt-Engineering? Choose awesome-prompts over Awesome-Prompt-Engineering when License: awesome-prompts is GPL-3.0, Awesome-Prompt-Engineering is Apache-2.0; Tags unique to awesome-prompts: awesome-list, prompt-attack, prompt-protect; Need detailed prompt engineering resources. ### When should I choose Awesome-Prompt-Engineering over awesome-prompts? Choose Awesome-Prompt-Engineering over awesome-prompts when License: Awesome-Prompt-Engineering is Apache-2.0, awesome-prompts is GPL-3.0; Tags unique to Awesome-Prompt-Engineering: deep-learning, few-shot-learning, gpt, machine-learning; Also covers Model Training; You need focused materials on GPT and related models for prompt engineering. ### When should I avoid awesome-prompts? Seeking a platform for generating new prompts rather than reviewing existing ones In search of direct support tools or services, not just informational content Requiring real-time collaboration on prompt creation and experimentation ### When should I avoid Awesome-Prompt-Engineering? The project requires languages other than TypeScript Resource is about areas outside of GPT, ChatGPT, PaLM prompt engineering ### Is awesome-prompts or Awesome-Prompt-Engineering more popular on GitHub? awesome-prompts has more GitHub stars (8,440 vs 6,197). Stars measure visibility, not whether either tool fits your constraints. ### Are awesome-prompts and Awesome-Prompt-Engineering open source? Yes - both are open-source projects on GitHub (awesome-prompts: GPL-3.0, Awesome-Prompt-Engineering: Apache-2.0). ### Where can I find alternatives to awesome-prompts or Awesome-Prompt-Engineering? GraphCanon lists graph-backed alternatives at [awesome-prompts alternatives](/tools/ai-boost-awesome-prompts/alternatives) and [Awesome-Prompt-Engineering alternatives](/tools/promptslab-awesome-prompt-engineering/alternatives) ([awesome-prompts markdown twin](/tools/ai-boost-awesome-prompts/alternatives.md), [Awesome-Prompt-Engineering markdown twin](/tools/promptslab-awesome-prompt-engineering/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-promptslab-awesome-prompt-engineering.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-Prompt-Engineering? awesome-prompts: Very active. Awesome-Prompt-Engineering: Very 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-Prompt-Engineering? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [awesome-prompts trust report](/tools/ai-boost-awesome-prompts/trust); [Awesome-Prompt-Engineering trust report](/tools/promptslab-awesome-prompt-engineering/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/_