--- title: "wonderful-prompts vs Awesome-Prompt-Engineering" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/langgptai-wonderful-prompts-vs-promptslab-awesome-prompt-engineering" tools: ["langgptai-wonderful-prompts", "promptslab-awesome-prompt-engineering"] --- # wonderful-prompts vs Awesome-Prompt-Engineering *GraphCanon updated Jul 28, 2026* ## Verdict Pick wonderful-prompts if enhances ChatGPT with optimized prompts and guides for improved playability and utility; pick Awesome-Prompt-Engineering if awesome-Prompt-Engineering curates resources tailored for GPT, ChatGPT, PaLM prompt engineering in TypeScript under Apache-2.0 license. [wonderful-prompts](https://langgptai.feishu.cn/wiki/RXdbwRyASiShtDky381ciwFEnpe) reports 6.2k GitHub stars, 532 forks, and 1 open issues, last pushed Oct 22, 2025. [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 [wonderful-prompts's repository](https://github.com/langgptai/wonderful-prompts) and [Awesome-Prompt-Engineering's repository](https://github.com/promptslab/Awesome-Prompt-Engineering). | | [wonderful-prompts](/tools/langgptai-wonderful-prompts.md) | [Awesome-Prompt-Engineering](/tools/promptslab-awesome-prompt-engineering.md) | | --- | --- | --- | | Tagline | 精选中文 prompt，提升 ChatGPT 可玩性和可用性 | Hand-curated resources for Prompt Engineering focusing on Generative Pre-trained Transformers | | Stars | 6,206 | 6,197 | | Forks | 532 | 734 | | Open issues | 1 | 94 | | Language | - | TypeScript | | Adopt for | Enhances ChatGPT with optimized prompts and guides for improved playability and utility. | Awesome-Prompt-Engineering curates resources tailored for GPT, ChatGPT, PaLM prompt engineering in TypeScript under Apache-2.0 license. | | Persona | - | - | | Runtime | - | - | | License | MIT | Apache-2.0 | | Categories | Developer Tools | Developer Tools, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [wonderful-prompts](/tools/langgptai-wonderful-prompts.md) | [Awesome-Prompt-Engineering](/tools/promptslab-awesome-prompt-engineering.md) | | --- | --- | --- | | Maintenance | Slowing (36%) | Very active (96%) | | Days since push | 278d | 0d | | Open issues (now) | 1 | 94 | | Full report | [trust report](/tools/langgptai-wonderful-prompts/trust.md) | [trust report](/tools/promptslab-awesome-prompt-engineering/trust.md) | ## Shared compatibility - **Python**: [wonderful-prompts](/tools/langgptai-wonderful-prompts.md) - Python runtime; [Awesome-Prompt-Engineering](/tools/promptslab-awesome-prompt-engineering.md) - Python runtime ## Decision facts: wonderful-prompts - **Adopt for:** Enhances ChatGPT with optimized prompts and guides for improved playability and utility. ## 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 wonderful-prompts if… - License: wonderful-prompts is MIT, Awesome-Prompt-Engineering is Apache-2.0. - Tags unique to wonderful-prompts: prompts. - You need to improve interaction experience or application efficiency of ChatGPT in Chinese-language contexts. ### Choose Awesome-Prompt-Engineering if… - License: Awesome-Prompt-Engineering is Apache-2.0, wonderful-prompts is MIT. - 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 wonderful-prompts - Your primary working language is not Chinese, as the prompts are optimized specifically for this language. ## 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 wonderful-prompts and Awesome-Prompt-Engineering? wonderful-prompts: 精选中文 prompt，提升 ChatGPT 可玩性和可用性. 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 wonderful-prompts over Awesome-Prompt-Engineering? Choose wonderful-prompts over Awesome-Prompt-Engineering when License: wonderful-prompts is MIT, Awesome-Prompt-Engineering is Apache-2.0; Tags unique to wonderful-prompts: prompts; You need to improve interaction experience or application efficiency of ChatGPT in Chinese-language contexts. ### When should I choose Awesome-Prompt-Engineering over wonderful-prompts? Choose Awesome-Prompt-Engineering over wonderful-prompts when License: Awesome-Prompt-Engineering is Apache-2.0, wonderful-prompts is MIT; 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 wonderful-prompts? Your primary working language is not Chinese, as the prompts are optimized specifically for this language. ### 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 wonderful-prompts or Awesome-Prompt-Engineering more popular on GitHub? wonderful-prompts has more GitHub stars (6,206 vs 6,197). Stars measure visibility, not whether either tool fits your constraints. ### Are wonderful-prompts and Awesome-Prompt-Engineering open source? Yes - both are open-source projects on GitHub (wonderful-prompts: MIT, Awesome-Prompt-Engineering: Apache-2.0). ### Where can I find alternatives to wonderful-prompts or Awesome-Prompt-Engineering? GraphCanon lists graph-backed alternatives at [wonderful-prompts alternatives](/tools/langgptai-wonderful-prompts/alternatives) and [Awesome-Prompt-Engineering alternatives](/tools/promptslab-awesome-prompt-engineering/alternatives) ([wonderful-prompts markdown twin](/tools/langgptai-wonderful-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/langgptai-wonderful-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, wonderful-prompts or Awesome-Prompt-Engineering? wonderful-prompts: Slowing. 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 wonderful-prompts and Awesome-Prompt-Engineering? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [wonderful-prompts trust report](/tools/langgptai-wonderful-prompts/trust); [Awesome-Prompt-Engineering trust report](/tools/promptslab-awesome-prompt-engineering/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=langgptai-wonderful-prompts`](/api/graphcanon/graph?tool=langgptai-wonderful-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/_