Image Generation

by tsingyuai

Image Generation is an AI Engineering skill for Claude Code, published by tsingyuai in growth-lab.

1.7K stars150 forkson tsingyuai/growth-labAdded 2026/08/19+41% in starsRepository updated 2026/08/11

View source on GitHub Download repo ZIP

agentic-marketingai-agentclaude-codecodexgrowthgrowth-hackingmarketing-automationopen-sourceseoskillsxiaohongshu

Install in seconds

Install Image Generation

Copy Image Generation into your Claude Code skills folder. Run the command in your terminal, or review the source on GitHub before installing.

terminal

npx degit https://github.com/tsingyuai/growth-lab/tree/main/executors/generate-image ~/.claude/skills/generate-image

Requires Node.js. Downloads this skill only — not the rest of the repository — into your Claude Code skills folder.

Without Node.js

git clone https://github.com/tsingyuai/growth-lab.git

Clones the whole repository, then copy the skill’s own directory into your skills folder yourself.

In this catalog

Source file: executors/generate-image/SKILL.md in tsingyuai/growth-lab
Installs to: ~/.claude/skills/generate-image
Collection: One of 19 skills cataloged from this repository
Category: AI Engineering — 2451 skills

What Image Generation does

Image Generation generates, edits, or batch-creates SEO, marketing, social, and document images using Gemini or OpenAI. Use it when a page or content loop needs illustrations, diagrams, covers, reference-image edits, multiple candidates, or verified image text and composition.

Image Generation is cataloged under AI Engineering on DirSkills. Image Generation comes from a repository tagged agentic-marketing, ai-agent, claude-code, codex and growth.

Documentation

README

Excerpt

Generate images

Use executors/generate-image/generate-image.mjs for text-to-image and reference-image editing. It is a repository-owned, zero-dependency Node.js client. Do not call Codex system Skills, private scripts, or files under ~/.codex.

Define the asset

Specify:

placement and purpose;
subject and visible action;
composition and aspect ratio;
visual style and brand palette;
exact text when text is essential;
details that must appear;
artifacts, logos, watermarks, and unrelated text to exclude.

Prefer real product screenshots when the image explains product behavior. Use generated visuals for concepts, scenes, covers, illustrations, diagrams, and supporting examples.

This is the opening of the README. Read the full README on GitHub.

Frequently asked about Image Generation

What else does tsingyuai publish alongside Image Generation?
Image Generation is one of 19 skills that DirSkills catalogs from tsingyuai/growth-lab, the repository it ships in. Its siblings there include Bilibili Media Crawler, Create SEO Page and Douyin Media Crawler. Each one is a separate skill with its own page in this directory, installs the same way Image Generation does, and is maintained by tsingyuai in that same repository. The rest of the collection is listed on the tsingyuai/growth-lab page.
How does Image Generation compare to other AI Engineering skills?
Image Generation ranks #926 by stars among the 2451 AI Engineering skills in this catalog. The most-starred ones next to it are Architecture Decision Records, AI-First Engineering and Agentic OS. DirSkills ranks by the star count of the repository each skill ships in, so that order reflects how popular those repositories are rather than any review of Image Generation against them. Open each page to compare what they document and how they install.