freestylefly/awesome-gpt-image-2

Prompt as Code | GPT-Image2 工业级提示词引擎与模板库,530+ 个案例逆向工程,20+ 套工业级模板,并提炼出Skills,持续更新中

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Summary Information

Updated 18 minutes ago
Added to GitGenius on August 23rd, 2026
Created on April 25th, 2026
Open Issues & Pull Requests: 12 (+0)
GitHub issues: Enabled
Number of forks: 1,637
Total Stargazers: 15,429 (+22)
Total Subscribers: 44 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 4.7 days
Mean response time: 17.4 days
90th percentile: 47.4 days
Tracked items: 3

How this project is maintained

Around half of the issues opened in the past year never receive a reply. Only 2% of issues opened in the past year have been closed.

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Issue Activity (beta)

Open issues: 6
New in 7 days: 2
Closed in 7 days: 0
Avg open age: 58 days
Stale 30+ days: 3
Stale 90+ days: 0

Recent activity

Opened in 7 days: 2
Closed in 7 days: 0
Comments in 7 days: 1
Events in 7 days: 1

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Detailed Description

awesome-gpt-image2 is a prompt engineering resource library that provides reverse-engineered examples and templates for AI image generation with GPT-Image2.

The project addresses the challenge of crafting effective prompts for image generation by collecting and organizing real-world examples. It operates as a curated repository of over five hundred reverse-engineered cases alongside industrial-grade templates, extracting reusable skills and patterns that developers can apply to their own image generation workflows. The approach treats prompts as code, enabling systematic reuse and composition of proven prompt structures.

Developers working with AI image generation should consider this resource if they want to accelerate prompt development by learning from existing successful examples rather than starting from scratch. The project suits teams building image generation features who need both inspiration and practical templates to reduce iteration time. The accompanying website provides a visual gallery interface where users can browse examples, copy full prompts, filter by style or scenario, and test generation directly after authentication, making it accessible beyond those comfortable reading raw repository files.

The project receives irregular updates with new workflows added over time. Development activity shows ongoing curation and expansion of the example collection, with the maintainer actively managing community engagement through a paid discussion group and maintaining multiple language versions of documentation.