BlockRun Image Generation
BlockRunAI/ClawRouter
Generates or edits images through ClawRouter's local image API, with a choice of models and sizes and payment handled automatically through x402.
Generates or edits images from text prompts through a Python script that picks an image backend based on which API keys are configured.
Install AI Image Generation and Editing
$ npx skills add zhayujie/CowAgent --skill image-generation -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install zhayujie/CowAgent image-generation --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/zhayujie/CowAgent.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/image-generation .claude/skills/image-generation && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "image-generation" agent skill from https://github.com/zhayujie/CowAgent/tree/master/skills/image-generation into .claude/skills/image-generation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "image-generation", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/zhayujie/CowAgent/tree/master/skills/image-generationType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add zhayujie/CowAgent --skill image-generation -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install zhayujie/CowAgent image-generation --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/zhayujie/CowAgent.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/image-generation .agents/skills/image-generation && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "image-generation" agent skill from https://github.com/zhayujie/CowAgent/tree/master/skills/image-generation into .agents/skills/image-generation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "image-generation", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add zhayujie/CowAgent --skill image-generation -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install zhayujie/CowAgent image-generation --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/zhayujie/CowAgent.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/image-generation .cursor/skills/image-generation && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "image-generation" agent skill from https://github.com/zhayujie/CowAgent/tree/master/skills/image-generation into .cursor/skills/image-generation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "image-generation", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/zhayujie/CowAgent.git --path skills/image-generation--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add zhayujie/CowAgent --skill image-generation -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install zhayujie/CowAgent image-generation --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/zhayujie/CowAgent.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/image-generation .gemini/skills/image-generation && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "image-generation" agent skill from https://github.com/zhayujie/CowAgent/tree/master/skills/image-generation into .gemini/skills/image-generation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "image-generation", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install zhayujie/CowAgent image-generationInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add zhayujie/CowAgent --skill image-generation -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/zhayujie/CowAgent.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/image-generation .github/skills/image-generation && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "image-generation" agent skill from https://github.com/zhayujie/CowAgent/tree/master/skills/image-generation into .github/skills/image-generation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "image-generation", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add zhayujie/CowAgent --skill image-generation -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install zhayujie/CowAgent image-generation --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/zhayujie/CowAgent.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/image-generation .opencode/skills/image-generation && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "image-generation" agent skill from https://github.com/zhayujie/CowAgent/tree/master/skills/image-generation into .opencode/skills/image-generation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "image-generation", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
image-generation- GitHub stars
- 47k
- Token cost
- ~1.3k tokens
- SKILL.md length
- 525 words
- Files
- 2 (incl. scripts)
- Skills in repo
- 3
- Repo updated
- First seen
- Licence
- MIT
At a glance
Generates or edits images from text prompts through a Python script that picks an image backend based on which API keys are configured.
- Creating an illustration, icon, poster or photo from a text description
- Runs Python scripts from its folder; calls python; needs OPENAI_API_KEY and GEMINI_API_KEY
- Editing an existing image given as a file path or URL
- Combining several input images into one result
What it does
The agent runs scripts/generate.py with a JSON argument holding the prompt and optional settings. The script chooses a backend on its own according to which API keys are configured, so the agent should not name a model unless you ask for one and must never invent a model name. Supported model families include OpenAI image models, Gemini Nano Banana, Seedream, Qwen and MiniMax.
Parameters are the prompt, one or more input images for editing (a list enables multi-image fusion), quality of low, medium or high, a size, and an aspect ratio. Higher quality and larger sizes cost more and run slower, so low or medium is the normal choice and high is reserved for when you ask. Results are saved to an images folder in the workspace or open project so they persist. Generation can take 30 to 200 seconds per provider, so the shell timeout should be at least 600 seconds and the script should run synchronously. The skill also says to call it by absolute path instead of changing into its folder, since a built-in skill's directory is reset on restart.
When your agent uses it
- Creating an illustration, icon, poster or photo from a text description
- Editing an existing image given as a file path or URL
- Combining several input images into one result
- Producing a specific aspect ratio such as 16:9 or 9:16
Example prompts
- “Draw a flat-style icon of a paper plane on a pale blue background.”
- “Edit photo.jpg so the sky looks like a sunset.”
- “Generate a 16:9 poster for a jazz night with bold typography, at medium quality.”
Requirements
- Python
- An API key for at least one supported image provider
What it can do on your machine
Read from SKILL.md and the folder at commit 0152064. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships 1 file in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
python
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names these keys or tokens, usually read from environment variables:
OPENAI_API_KEYGEMINI_API_KEYARK_API_KEYDASHSCOPE_API_KEYMINIMAX_API_KEYLINKAI_API_KEY
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
AI Image Generation and Editing loads about 1.3k tokens when it runs. Until then it costs about 46 tokens; SKILL.md has 525 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.
SKILL.md
The full file from zhayujie/CowAgent at commit 0152064, republished under its MIT licence (© zhayujie). 525 words, ~1,262 tokens.
Download SKILL.mdSave it as
.claude/skills/image-generation/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.- name
- image-generation
- description
- Generate or edit images from text prompts. Use when the user asks to create, draw, design, or edit an image, illustration, photo, icon, poster, or any visual content.
Image Generation
Generate and edit images using AI models. The script automatically picks a backend based on which API keys are configured — you don't need to specify a model unless the user explicitly names one. Never guess or invent a model: when the user doesn't name one, omit model entirely so the configured default/provider is used.
Supported models (passed via model only when the user asks for a specific one):
- OpenAI —
gpt-image-2.5-flare(recommended default: best quality/latency trade-off),gpt-image-2.5-sunburst(highest editing precision),gpt-image-2,gpt-image-1 - Gemini Nano Banana —
nano-banana-2,nano-banana-pro,nano-banana - Seedream (Volcengine Ark) —
seedream-5.0-lite,seedream-4.5 - Qwen (DashScope) —
qwen-image-2.0,qwen-image-2.0-pro - MiniMax —
image-01
Usage
Run scripts/generate.py with a JSON argument. Use the absolute <base_dir> path — do NOT cd into the skill directory, since it is a builtin skill and gets reset on restart (anything written there is lost).
python <base_dir>/scripts/generate.py '<json_args>'Images are saved to the workspace (or the open project dir) under images/, so they persist and stay reachable to the client.
Set bash timeout to at least 600 seconds, as image generation can take 30–200s per provider, and the script may try multiple providers sequentially. Call it synchronously (do not run it in the background) and wait for its output in the same turn.
Parameters
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
prompt | string | yes | — | Image description |
image_url | string / list | no | null | Input image(s) for editing: local file path or URL. Multi-image fusion is supported (pass a list) |
quality | string | no | auto | low / medium / high (only some backends honour this) |
size | string | no | auto | 512 / 1K / 2K / 3K / 4K, or pixel value (1024x1024) |
aspect_ratio | string | no | null | 1:1 / 3:2 / 2:3 / 16:9 / 9:16 / 21:9 (some backends also support extreme ratios like 1:4 / 8:1) |
Higher quality and larger size cost more and run slower. In normal cases, when the user does not explicitly specify, low or medium is sufficient. Only use high when the user asks for it.
Example — generate
python <base_dir>/scripts/generate.py '{"prompt": "A corgi astronaut floating in space"}'With aspect ratio:
python <base_dir>/scripts/generate.py '{"prompt": "Isometric miniature city of Shanghai at sunset", "size": "2K", "aspect_ratio": "16:9"}'Show full SKILL.md (210 more words)Show less
Important: Editing vs Generating
When the user asks to edit, modify, or improve an existing image, pass the original image via image_url. Prefer local file paths directly — the script handles file reading internally. Without image_url, the script generates a brand-new image instead of editing.
Example — edit (image-to-image)
python <base_dir>/scripts/generate.py '{"prompt": "Add a Santa hat to the dog", "image_url": "/path/to/dog.png"}'Multi-image fusion — pass a list:
python <base_dir>/scripts/generate.py '{"prompt": "Combine these characters into a group photo", "image_url": ["/path/a.png", "/path/b.png"]}'Output
Prints JSON to stdout:
{
"model": "doubao-seedream-5-0-260128",
"images": [
{"url": "/path/to/output.png"}
]
}After success, display the image to the user. You can either embed it in markdown () or use the send tool.
On error:
{
"error": "error message"
}Setup
The script needs at least one of these API keys (set via env_config or config.json):
OPENAI_API_KEY / GEMINI_API_KEY / ARK_API_KEY / DASHSCOPE_API_KEY / MINIMAX_API_KEY / LINKAI_API_KEY
Each also has an optional *_API_BASE for custom endpoints. The script automatically picks the first configured backend and falls back to the next if it fails — no need to specify a model.
Error Handling
If the script returns an error after trying all configured backends, do NOT retry with the same parameters — the failure is almost always a configuration issue (wrong API key, unsupported API base). Tell the user to fix it via env_config, then retry.
Notes
- HTTP timeout is 300s — high-resolution generation can take over 200s.
- Omit
quality/sizeto let the model pick automatically (auto). - Input images for editing are auto-compressed to ≤ 4MB / longest edge ≤ 4096px.
© zhayujie, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 1 other file (scripts) in skills/image-generation of zhayujie/CowAgent.
- SKILL.md
- scripts/generate.py
Open the folder on GitHubat commit 0152064
Compare with similar skills
AI Image Generation and Editing next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| AI Image Generation and Editing this skillzhayujie/CowAgent | 47k | — | ~1.3k | Automated safety check: Pass | MIT | |
| BlockRun Image GenerationBlockRunAI/ClawRouter | 6.6k | — | ~2.1k | Automated safety check: Pass | MIT | |
| AI Image Creatorevolution-foundation/evo-nexus | 545 | — | ~5.1k | Automated safety check: Notes | Custom licence | |
| 9Router Image Generationdecolua/9router | 30k | — | ~830 | Automated safety check: Pass | MIT | |
| AI Image Creatorcentminmod/my-claude-code-setup | 2.7k | — | ~8.1k | Automated safety check: Notes | MIT | |
| Image Genopen-octo/octo-agent | 125 | — | ~3.1k | Automated safety check: Notes | MIT |
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Categories
Questions about AI Image Generation and Editing
What does AI Image Generation and Editing do?
Generates or edits images from text prompts through a Python script that picks an image backend based on which API keys are configured. py with a JSON argument holding the prompt and optional settings. The script chooses a backend on its own according to which API keys are configured, so the agent should not name a model unless you ask for one and must never invent a model name.
When should I use AI Image Generation and Editing?
AI Image Generation and Editing fits situations like: creating an illustration, icon, poster or photo from a text description; editing an existing image given as a file path or URL; combining several input images into one result; producing a specific aspect ratio such as 16:9 or 9:16.
How do I install AI Image Generation and Editing in Claude Code?
Run `npx skills add zhayujie/CowAgent --skill image-generation -a claude-code`. Or copy the skill folder (skills/image-generation in zhayujie/CowAgent) into .claude/skills/image-generation in your project. Claude Code loads it when a task matches its description.
How do I install AI Image Generation and Editing in Codex?
Run `npx skills add zhayujie/CowAgent --skill image-generation -a codex`. Or copy the skill folder (skills/image-generation in zhayujie/CowAgent) into .agents/skills/image-generation in your project. Codex loads it when a task matches its description.
Can I use AI Image Generation and Editing in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add zhayujie/CowAgent --skill image-generation -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/image-generation, .gemini/skills/image-generation, .github/skills/image-generation and .opencode/skills/image-generation in your project.
What does AI Image Generation and Editing need to run?
Going by SKILL.md and its folder, AI Image Generation and Editing needs Python for the scripts in its folder, the command-line tools its instructions call (python) and credentials named OPENAI_API_KEY, GEMINI_API_KEY, ARK_API_KEY and DASHSCOPE_API_KEY. Our summary lists: Python; An API key for at least one supported image provider.
Does AI Image Generation and Editing access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is AI Image Generation and Editing safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
What licence does AI Image Generation and Editing use?
AI Image Generation and Editing is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does AI Image Generation and Editing use?
About 1.3k tokens (SKILL.md is roughly 5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to AI Image Generation and Editing?
Skills that share tags, products or a category with AI Image Generation and Editing: BlockRun Image Generation (BlockRunAI/ClawRouter, 6.6k stars), AI Image Creator (evolution-foundation/evo-nexus, 545 stars), 9Router Image Generation (decolua/9router, 30k stars) and AI Image Creator (centminmod/my-claude-code-setup, 2.7k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains AI Image Generation and Editing?
zhayujie (a GitHub user) maintains it in zhayujie/CowAgent, which has 47,294 GitHub stars. The repository holds 3 skills in this directory. The repository was last updated on October 9, 2026.
Source: zhayujie/CowAgent on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.