AI Image Generation and Editing
zhayujie/CowAgent
Generates or edits images from text prompts through a Python script that picks an image backend based on which API keys are configured.
AI image generation: Gemini and Nano Banana backends; single/series/batch workflows with prompt-to-disk.
Install Image Gen
$ npx skills add notque/vexjoy-agent --skill image-gen -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install notque/vexjoy-agent image-gen --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/notque/vexjoy-agent.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/content/image-gen .claude/skills/image-gen && 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-gen" agent skill from https://github.com/notque/vexjoy-agent/tree/main/skills/content/image-gen into .claude/skills/image-gen/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "image-gen", 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/notque/vexjoy-agent/tree/main/skills/content/image-genType 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 notque/vexjoy-agent --skill image-gen -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install notque/vexjoy-agent image-gen --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/notque/vexjoy-agent.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/content/image-gen .agents/skills/image-gen && 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-gen" agent skill from https://github.com/notque/vexjoy-agent/tree/main/skills/content/image-gen into .agents/skills/image-gen/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "image-gen", 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 notque/vexjoy-agent --skill image-gen -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install notque/vexjoy-agent image-gen --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/notque/vexjoy-agent.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/content/image-gen .cursor/skills/image-gen && 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-gen" agent skill from https://github.com/notque/vexjoy-agent/tree/main/skills/content/image-gen into .cursor/skills/image-gen/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "image-gen", 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/notque/vexjoy-agent.git --path skills/content/image-gen--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 notque/vexjoy-agent --skill image-gen -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install notque/vexjoy-agent image-gen --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/notque/vexjoy-agent.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/content/image-gen .gemini/skills/image-gen && 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-gen" agent skill from https://github.com/notque/vexjoy-agent/tree/main/skills/content/image-gen into .gemini/skills/image-gen/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "image-gen", 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 notque/vexjoy-agent image-genInstalls 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 notque/vexjoy-agent --skill image-gen -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/notque/vexjoy-agent.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/content/image-gen .github/skills/image-gen && 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-gen" agent skill from https://github.com/notque/vexjoy-agent/tree/main/skills/content/image-gen into .github/skills/image-gen/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "image-gen", 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 notque/vexjoy-agent --skill image-gen -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install notque/vexjoy-agent image-gen --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/notque/vexjoy-agent.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/content/image-gen .opencode/skills/image-gen && 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-gen" agent skill from https://github.com/notque/vexjoy-agent/tree/main/skills/content/image-gen into .opencode/skills/image-gen/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "image-gen", 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-gen- GitHub stars
- 435
- Token cost
- ~1.3k tokens
- SKILL.md length
- 458 words
- Files
- 7 (incl. scripts, references)
- Skills in repo
- 61
- Repo updated
- First seen
- Licence
- MIT
At a glance
AI image generation: Gemini and Nano Banana backends; single/series/batch workflows with prompt-to-disk.
- Works in 5 steps: Detect Backend → Write Prompt Files → Select Script → …
- Tasks that involve Image generation
- SKILL.md covers Deep References, Phase 1: Detect Backend, Phase 2: Write Prompt Files and Phase 3: Select Script, plus 3 more sections
- Runs Python scripts from its folder; calls python3 and pip; needs GEMINI_API_KEY
What it does
Image Gen is an agent skill from notque/vexjoy-agent. AI image generation: Gemini and Nano Banana backends; single/series/batch workflows with prompt-to-disk.
Its SKILL.md is about 1.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 9 other files, including scripts and reference files (for example `references/backends/gemini.md`, `references/backends/nano-banana.md` and `scripts/detect-backend.py`).
It sits in Media & Creative, covering Image generation. It works with Google Gemini. The repository describes itself as: VexJoy AI Agent with Jev Intelligent Routing - /do routes plain-English requests to the right specialist agent and gates the work with reviews, tests, and a learning loop. The licence is MIT.
When your agent uses it
- Tasks that involve Image generation
Example prompts
- “/image-gen”
Requirements
- Python 3
- A credential in GEMINI_API_KEY
Workflow steps
5 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit 5218674. 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 4 files in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
python3pip
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md. Its commands use pip, which can reach the network depending on how they are called.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names these keys or tokens, usually read from environment variables:
GEMINI_API_KEY
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Image Gen loads about 1.3k tokens when it runs, and up to ~4k if it reads all its reference files. Until then it costs about 29 tokens; SKILL.md has 458 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 notque/vexjoy-agent at commit 5218674, republished under its MIT licence (© notque). 458 words, ~1,308 tokens.
Download SKILL.mdSave it as
.claude/skills/image-gen/SKILL.md (or your agent's skills folder). This skill also uses 6 other files; get the full folder from GitHub.- name
- image-gen
- description
- AI image generation: Gemini and Nano Banana backends; single/series/batch workflows with prompt-to-disk.
- agent
- python-general-engineer
- user-invocable
- false
- routing.category
- image-generation
- routing.triggers
- generate image, create image, image generation, AI image, gemini image, make image, draw, illustrate, sprite generation, card art, batch generation, series of…
- routing.not_for
- HTML visualization or charts (use html-artifact), or deterministic non-AI palette/matrix pixel art (use game-asset-generator)
- routing.pairs_with
- python-general-engineer, game-dev
image-gen
Backend-agnostic image generation: single images, series with anchor-chain consistency, batch pipelines. Two backends: Gemini (API) and Nano Banana (local scripts with post-processing).
Deep References
| Signal | Load | Content |
|---|---|---|
| Gemini backend selected | references/backends/gemini.md | Models, env vars, flag table, examples, error codes |
| Nano Banana needed (post-processing, series, JSON batch, style-match) | references/backends/nano-banana.md | Subcommands, flags, aspect ratios, prompt patterns by asset type |
Phase 1: Detect Backend
python3 skills/content/image-gen/scripts/detect-backend.pygemini-- loadreferences/backends/gemini.mdask-- no key found; ask the user to setGEMINI_API_KEY
Gate: backend confirmed.
Phase 2: Write Prompt Files
Write all prompts to disk before any API call. Prompt files are the generation record and anchor-chain input for series.
File naming: single prompts/YYYY-MM-DD-{slug}.md, series prompts/{series-name}-01.md through -NN.md.
---
model: gemini-3-pro-image-preview
aspect-ratio: 1:1
flags: []
---
Full prompt text. Be explicit about subject, style, background, constraints.mkdir -p promptsFor series: write ALL prompt files before calling any generation script.
Gate: all prompt files written and reviewed.
Phase 3: Select Script
| Use case | Script | Subcommand |
|---|---|---|
| Single image, Gemini | scripts/generate_image.py | --prompt |
| Batch from text file, Gemini | scripts/generate_image.py | --batch |
| Single with post-processing | scripts/nano-banana-generate.py | generate |
| Style match from reference | scripts/nano-banana-generate.py | with-reference |
| Batch from JSON manifest | scripts/nano-banana-generate.py | batch |
| Series (anchor chain) | scripts/nano-banana-generate.py | generate then with-reference |
| Post-processing only | scripts/nano-banana-process.py | crop / remove-bg / pipeline |
Model selection:
| Scenario | Model |
|---|---|
| Draft, testing, batch, cost-sensitive | gemini-2.5-flash-image (2-5s) |
| Final asset, character art, typography | gemini-3-pro-image-preview (~30s) |
Aspect ratio by use case:
| Asset type | Ratio |
|---|---|
| Sprites, characters, icons | 1:1 |
| Card art, landscape | 16:9 |
| Vertical maps, portrait bg | 9:16 |
| Portrait cards | 3:4 |
| Wide banners | 21:9 |
Generate at the target ratio. Generating 1:1 and cropping to 16:9 loses 56% of pixels.
Gate: script and subcommand identified.
Phase 4: Generate
Use absolute paths for output files. Show full script output.
Show full SKILL.md (202 more words)Show less
Anchor-Chain Algorithm (Series)
Character drift occurs when images are generated independently. Prevent it by passing the previous output as --reference:
image-01.png (no ref) -> image-02.png (ref=01) -> image-03.png (ref=02) -> ...- Generate image 1 with no reference.
- Use output of image 1 as
--referencefor image 2. - Continue: each image N references image N-1.
Save originals with --save-original for any batch or expensive generation. Re-processing a saved original is free; re-generating costs quota and may break the chain.
Gate: script exits 0.
Phase 5: Verify and Report
Read the generated image to verify:
- Subject matches prompt
- No unwanted watermarks or artifacts
- Aspect ratio and framing correct
- No excessive padding or dark borders
If inspection fails: regenerate with adjusted prompt. Report the issue before retrying.
Report: output file path (absolute), dimensions, model, post-processing applied, verification result. Report only what was requested.
Error Handling
| Error | Cause | Resolution |
|---|---|---|
GEMINI_API_KEY not set | Missing env var | export GEMINI_API_KEY=your_key |
No image in response | Safety filter or text-only response | Adjust prompt; remove policy-adjacent content |
Missing dependency: google-genai | Package absent | pip install google-genai pillow |
Rate limit exceeded (429) | Too many requests | Increase --delay; script retries automatically |
Content policy violation (400) | Restricted content | Rephrase using neutral language |
| Model not found | Wrong model string | Use exact strings: gemini-2.5-flash-image or gemini-3-pro-image-preview |
© notque, 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 6 other files (scripts, references) in skills/content/image-gen of notque/vexjoy-agent.
- SKILL.md
- references/backends/gemini.md
- references/backends/nano-banana.md
- scripts/detect-backend.py
- scripts/generate_image.py
- scripts/nano-banana-generate.py
- scripts/nano-banana-process.py
Open the folder on GitHubat commit 5218674
Compare with similar skills
Image Gen 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 |
|---|---|---|---|---|---|---|
| Image Gen this skillnotque/vexjoy-agent | 435 | — | ~1.3k | Automated safety check: Pass | MIT | |
| AI Image Generation and Editingzhayujie/CowAgent | 47k | — | ~1.3k | Automated safety check: Pass | MIT | |
| Gemini Web Reverse-Engineered ClientJimLiu/baoyu-skills | 26k | 6 repos | ~1.6k | Automated safety check: Pass | MIT | |
| Logo Generatorop7418/logo-generator-skill | 2.2k | — | ~1.8k | Automated safety check: Notes | None | |
| NanobananaReScienceLab/opc-skills | 1.8k | 1 repos | ~1.3k | Automated safety check: Pass | Apache-2.0 | |
| SEO Image GeneratorAgriciDaniel/claude-seo | 18k | 2 repos | ~2.1k | Automated safety check: Pass | MIT |
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Gemini Web Reverse-Engineered Client
JimLiu/baoyu-skills
Generates text and images through an unofficial, reverse-engineered Gemini Web API, supporting reference images and multi-turn conversations.
Logo Generator
op7418/logo-generator-skill
Generate professional SVG logos and high-end showcase images.
Nanobanana
ReScienceLab/opc-skills
Generate and edit images using Google Gemini 3 Pro Image (Nano Banana Pro).
SEO Image Generator
AgriciDaniel/claude-seo
Generates Open Graph previews, blog hero images, product photos and infographics for SEO use through Gemini image tools and the banana extension.
BlockRun Image Generation
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Generates or edits images through ClawRouter's local image API, with a choice of models and sizes and payment handled automatically through x402.
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Related
Works with
Categories
Questions about Image Gen
What does Image Gen do?
AI image generation: Gemini and Nano Banana backends; single/series/batch workflows with prompt-to-disk. Image Gen is an agent skill from notque/vexjoy-agent. AI image generation: Gemini and Nano Banana backends; single/series/batch workflows with prompt-to-disk.
When should I use Image Gen?
Image Gen fits situations like: tasks that involve Image generation.
How do I install Image Gen in Claude Code?
Run `npx skills add notque/vexjoy-agent --skill image-gen -a claude-code`. Or copy the skill folder (skills/content/image-gen in notque/vexjoy-agent) into .claude/skills/image-gen in your project. Claude Code loads it when a task matches its description.
How do I install Image Gen in Codex?
Run `npx skills add notque/vexjoy-agent --skill image-gen -a codex`. Or copy the skill folder (skills/content/image-gen in notque/vexjoy-agent) into .agents/skills/image-gen in your project. Codex loads it when a task matches its description.
Can I use Image Gen 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 notque/vexjoy-agent --skill image-gen -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-gen, .gemini/skills/image-gen, .github/skills/image-gen and .opencode/skills/image-gen in your project.
What does Image Gen need to run?
Going by SKILL.md and its folder, Image Gen needs Python for the scripts in its folder, the command-line tools its instructions call (python3 and pip) and credentials named GEMINI_API_KEY. Our summary lists: Python 3; A credential in GEMINI_API_KEY.
Does Image Gen access the network?
SKILL.md contains no URLs. Its commands use pip, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
Is Image Gen 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 Image Gen use?
Image Gen 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 Image Gen use?
About 1.3k tokens (SKILL.md is roughly 5.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 2.7k tokens, read only when the agent opens those files.
What are the alternatives to Image Gen?
Skills that share tags, products or a category with Image Gen: AI Image Generation and Editing (zhayujie/CowAgent, 47k stars), Gemini Web Reverse-Engineered Client (JimLiu/baoyu-skills, 26k stars), Logo Generator (op7418/logo-generator-skill, 2.2k stars) and Nanobanana (ReScienceLab/opc-skills, 1.8k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Image Gen?
notque (a GitHub user) maintains it in notque/vexjoy-agent, which has 435 GitHub stars. The repository holds 61 skills in this directory. The repository was last updated on October 3, 2026.
Source: notque/vexjoy-agent on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.