yang0/handraw-style

手绘风格编号画廊与双语提示词 Skill

View on GitHub ↗Jump to charts ↓Open shareable report →

Data as of . Signed-in members get hourly updates — create a free account.

Summary Information

Updated 15 minutes ago
Added to GitGenius on September 23rd, 2026
Created on September 5th, 2026
Open Issues & Pull Requests: 2 (+0)
GitHub issues: Enabled
Number of forks: 406
Total Stargazers: 3,126 (+1)
Total Subscribers: 10 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 30.1 hours
Mean response time: 2.8 days
90th percentile: 6.5 days
Tracked items: 4

Charts & Analytics

Fetching additional details & charts...

Issue Activity (beta)

Open issues: 0
New in 7 days: 1
Closed in 7 days: 4
Avg open age: N/A days
Stale 30+ days: 0
Stale 90+ days: 0

Recent activity

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

Top labels

No label distribution available yet.

Most active issues this week

Sign in to see which issues are moving.
Sign in

Detailed Description

Handraw-style is a prompt library and gallery tool that generates AI image generation prompts in hand-drawn styles for creators.

The tool addresses the difficulty of describing visual styles and composition to AI image generators. It provides a curated system of 277 hand-drawn illustration styles, 119 layout templates covering social media cards, infographics, and comic panels, and 30 monochromatic color themes. Users select a style number, layout number, and color theme, then describe their desired subject to receive tested bilingual Chinese-English prompts ready to paste into AI image generation tools. The tool includes an intelligent recommendation mode that automatically matches styles and colors to themes without requiring users to manually browse the catalog.

The project suits social media creators, educational content creators, comic and narrative illustrators, and designers who need to rapidly produce hand-drawn visual assets. It eliminates the need to memorize art terminology or spend time conceptualizing layouts. The tool supports both pure illustration mode and image-text mode where text integrates with the composition. It is designed as a Skill that can be installed directly into Codex, which handles resource configuration automatically.

Development activity shows consistent maintenance with regular updates to the style and layout galleries. The project maintains bilingual documentation in both Chinese and English, reflecting attention to accessibility across language communities. The codebase is structured as an HTML-based resource library with organized indexing systems for the style, layout, and color collections.