9Router Image Generation
decolua/9router
Generates images through a 9Router gateway's image endpoint, with model discovery, the request fields and per-provider quirks for OpenAI, Gemini, MiniMax and others.
Generates still images through the submit_image tool, choosing among Fal.ai, gpt-image-2, nano-banana, MiniMax image-01 and Grok Imagine by configured keys.
Install AI Image Generation
$ npx skills add 0xsline/OpenChatCut --skill image-gen -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install 0xsline/OpenChatCut 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/0xsline/OpenChatCut.git skills-src && mkdir -p .claude/skills && cp -r skills-src/src/agent/skills/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/0xsline/OpenChatCut/tree/main/src/agent/skills/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/0xsline/OpenChatCut/tree/main/src/agent/skills/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 0xsline/OpenChatCut --skill image-gen -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install 0xsline/OpenChatCut image-gen --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/0xsline/OpenChatCut.git skills-src && mkdir -p .agents/skills && cp -r skills-src/src/agent/skills/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/0xsline/OpenChatCut/tree/main/src/agent/skills/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 0xsline/OpenChatCut --skill image-gen -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install 0xsline/OpenChatCut image-gen --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/0xsline/OpenChatCut.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/src/agent/skills/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/0xsline/OpenChatCut/tree/main/src/agent/skills/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/0xsline/OpenChatCut.git --path src/agent/skills/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 0xsline/OpenChatCut --skill image-gen -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install 0xsline/OpenChatCut image-gen --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/0xsline/OpenChatCut.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/src/agent/skills/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/0xsline/OpenChatCut/tree/main/src/agent/skills/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 0xsline/OpenChatCut 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 0xsline/OpenChatCut --skill image-gen -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/0xsline/OpenChatCut.git skills-src && mkdir -p .github/skills && cp -r skills-src/src/agent/skills/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/0xsline/OpenChatCut/tree/main/src/agent/skills/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 0xsline/OpenChatCut --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 0xsline/OpenChatCut image-gen --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/0xsline/OpenChatCut.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/src/agent/skills/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/0xsline/OpenChatCut/tree/main/src/agent/skills/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
- 2.2k
- Token cost
- ~1.3k tokens
- SKILL.md length
- 437 words
- Files
- 6 (incl. references)
- Skills in repo
- 31
- Repo updated
- First seen
- Licence
- AGPL-3.0
At a glance
Generates still images through the submit_image tool, choosing among Fal.ai, gpt-image-2, nano-banana, MiniMax image-01 and Grok Imagine by configured keys.
- Generating a single image or still from a text prompt
- SKILL.md covers Model Selection, Tool Params, Defaults and Ask Before Submit, plus 3 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- Making an image that follows reference pictures closely
What it does
The skill generates images through a submit_image tool, and only with providers whose keys are configured. It offers Fal.ai with a chosen Fal model, gpt-image-2, nano-banana, MiniMax image-01 and xAI Grok Imagine, each with its own reference file that the agent must read before generating. gpt-image-2 is the default when its key is on, reference-heavy requests go to nano-banana, and a request that names MiniMax, or a setup with only the MiniMax key, uses image-01.
Tool parameters include aspect ratio (16:9 by default), image size from 512px up to 4K depending on the model, width and height, a quality setting for gpt-image-2, reference asset ids, a library name for the result and a count of images. The agent should make one clear still per request unless you ask for variants. A table lists how many reference images each model accepts, and the Fal limits depend on the model chosen.
When your agent uses it
- Generating a single image or still from a text prompt
- Making an image that follows reference pictures closely
- Choosing between image models according to the configured providers
- Producing images in a specific aspect ratio and size
Example prompts
- “Generate a 16:9 still of a lighthouse at dusk for the video intro.”
- “Create an image of our mascot using the reference images in the project library.”
- “Make a poster with the headline Open Studio in bold type.”
- “Use MiniMax to generate a live-style still of a night market.”
Requirements
- An API key for at least one of the supported image providers
What it can do on your machine
Read from SKILL.md and the folder at commit 2e6f4a2. 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
No scripts in the folder and no shell commands in SKILL.md (its code samples are typescript).
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 no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
AI Image Generation loads about 1.3k tokens when it runs, and up to ~3.5k if it reads all its reference files. Until then it costs about 45 tokens; SKILL.md has 437 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); files beside SKILL.md are not scanned.
SKILL.md
The full file from 0xsline/OpenChatCut at commit 2e6f4a2, republished under its AGPL-3.0 licence (© 0xsline). 437 words, ~1,349 tokens.
Download SKILL.mdSave it as
.claude/skills/image-gen/SKILL.md (or your agent's skills folder). This skill also uses 5 other files; get the full folder from GitHub.- name
- image-gen
- description
- AI image generation via Fal.ai, gpt-image-2, nano-banana, MiniMax image-01, and xAI Grok Imagine. Use when the user wants to generate or create an image / picture / still.
- user-invocable
- true
Image Gen
Generate AI images via submit_image (configured provider keys only). Prefer one clear still per request unless the user asked for variants.
Model Selection
| Model | Reference | Strengths | Max refs |
|---|---|---|---|
fal + falModel | references/fal.md | Explicit Fal catalog; see tool schema for per-model limits | Model-specific |
gpt-image-2 | references/gpt-image-2.md | Best text rendering, strongest prompt adherence | 16 |
nano-banana | references/nano-banana.md | Strongest reference-image fidelity | 14 |
image-01 | references/image-01.md | MiniMax stills / live style; one subject reference via R2 | 1 |
grok-imagine | references/grok-imagine.md | xAI Grok Imagine; text-to-image, ≤4 outputs, 1K/2K | 0 |
- If Fal.ai is selected or requested, use
model: "fal"and the requestedfalModelor saved Fal default from capabilities. Ask if none is selected. Native-provider defaults and controls below do not apply to Fal. - Default:
gpt-image-2when that key is on. - Reference-heavy →
nano-banana. - User named MiniMax / only MiniMax image key on →
image-01. - Respect capabilities: do not call a model whose vendor is not configured.
IMPORTANT: Before generating, READ the chosen model's reference.
Tool Params
| Param | Values | Default |
|---|---|---|
aspectRatio | 1:1, 16:9, 9:16, 4:3, 3:4, 3:2, 2:3, 4:5, 5:4, 21:9 | 16:9 |
imageSize | 512px, 1K, 2K, 4K (model-specific) | 1K |
width / height | GPT Image: 512–3840, /16; MiniMax: 512–2048, /8 | — |
quality | low, medium, high, auto (gpt-image-2 only) | high |
referenceAssetIds | Array of project asset ids — backend resolves bytes server-side | — |
name | Short descriptive asset name shown in the library | — |
count | Number of images to generate (1–10; image-01 max 9) | 1 |
promptOptimizer | MiniMax image-01 only — prompt_optimizer | false |
seed | MiniMax image-01 only | — |
maskAssetId, background, moderation, inputFidelity | GPT Image edit/output controls | — |
outputFormat, outputCompression | GPT Image PNG/JPEG/WebP controls | PNG |
Defaults
- Aspect ratio: 16:9. If the project composition is not 16:9, ASK the user which aspect ratio they want before generating.
- Size: 1K.
Show full SKILL.md (166 more words)Show less
Ask Before Submit
- Never auto-upgrade size.
- Only pass
imageSize: "2K"or"4K"when the user explicitly asks. Warn that 2K/4K are EXPERIMENTAL and may be slower.
Reference Images
Use when the user provides source material to edit, blend, or use as visual guidance (e.g. "change the background", "combine these into a poster").
- Pass project asset ids via
referenceAssetIds. The backend fetches and encodes them server-side — never pull the asset bytes yourself. - When the user @-references an image asset, pass its id directly in
referenceAssetIds. - Formats accepted by backend: png, jpeg, webp, svg (auto-rasterized to png), heic, heif. Each ≤ 50MB.
Run
// Basic generation
submit_image({
model: "gpt-image-2",
prompt: "a cute orange cat",
name: "Cat",
});
// With quality (gpt-image-2 only)
submit_image({
model: "gpt-image-2",
prompt: "hero poster with bold title",
quality: "high",
name: "Hero Poster",
});
// With reference images — pass project asset ids; backend resolves bytes
submit_image({
model: "gpt-image-2",
prompt: "change background to beach",
referenceAssetIds: ["<assetId>"],
name: "Beach Edit",
});
// Reference-heavy with nano-banana
submit_image({
model: "nano-banana",
prompt: "composite poster",
referenceAssetIds: ["<id1>", "<id2>"],
name: "Composite",
});
// Multiple images
submit_image({
model: "gpt-image-2",
prompt: "product shots",
count: 3,
name: "Product",
});
// MiniMax (optional single subject reference; R2 must be configured for refs)
submit_image({
model: "image-01",
prompt: "matte product bottle on marble, soft studio light",
name: "Bottle still",
promptOptimizer: false,
});OpenChatCut’s submit_image may return completed pool assets synchronously depending on the provider path. If a jobId is returned, use track_progress; otherwise treat the asset ids in the result as done.
Rules
- Always provide
namewith a short descriptive asset name. - Before submitting, briefly tell the user what you're about to generate — especially when generating multiple images.
- Only call models whose vendor key is configured (capabilities prompt).
© 0xsline, AGPL-3.0. 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 5 other files (references) in src/agent/skills/image-gen of 0xsline/OpenChatCut.
- SKILL.md
- references/fal.md
- references/gpt-image-2.md
- references/grok-imagine.md
- references/image-01.md
- references/nano-banana.md
Open the folder on GitHubat commit 2e6f4a2
Compare with similar skills
AI Image Generation 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 this skill0xsline/OpenChatCut | 2.2k | — | ~1.3k | Automated safety check: Pass | AGPL-3.0 | |
| 9Router Image Generationdecolua/9router | 30k | — | ~830 | Automated safety check: Pass | MIT | |
| Keirouter Imagemydisha/keirouter | 147 | — | ~691 | Automated safety check: Pass | MIT | |
| AI Image Generation and Editingzhayujie/CowAgent | 47k | — | ~1.3k | Automated safety check: Pass | MIT | |
| Forge Media Route Layer0x0funky/agent-sprite-forge | 4.4k | — | ~2.2k | Automated safety check: Pass | MIT | |
| Video-to-Sprite Animation Generator0x0funky/agent-sprite-forge | 4.4k | — | ~3.8k | Automated safety check: Pass | MIT |
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Generates WebGL shaders for video effects, transitions, masks and color grades in the OpenChatCut editor, trying built-in catalog effects such as zoom before making anything new.
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Generates instrumentals, songs, soundtracks and covers through Mureka, MiniMax, Atlas Cloud or Sonilo using the `submit_music` tool.
AI Video Generation
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Video Voiceover And SFX Generator
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Related
Categories
Questions about AI Image Generation
What does AI Image Generation do?
Generates still images through the submit_image tool, choosing among Fal.ai, gpt-image-2, nano-banana, MiniMax image-01 and Grok Imagine by configured keys. The skill generates images through a submit_image tool, and only with providers whose keys are configured.ai with a chosen Fal model, gpt-image-2, nano-banana, MiniMax image-01 and xAI Grok Imagine, each with its own reference file that the agent must read before generating.
When should I use AI Image Generation?
AI Image Generation fits situations like: generating a single image or still from a text prompt; making an image that follows reference pictures closely; choosing between image models according to the configured providers; producing images in a specific aspect ratio and size.
How do I install AI Image Generation in Claude Code?
Run `npx skills add 0xsline/OpenChatCut --skill image-gen -a claude-code`. Or copy the skill folder (src/agent/skills/image-gen in 0xsline/OpenChatCut) into .claude/skills/image-gen in your project. Claude Code loads it when a task matches its description.
How do I install AI Image Generation in Codex?
Run `npx skills add 0xsline/OpenChatCut --skill image-gen -a codex`. Or copy the skill folder (src/agent/skills/image-gen in 0xsline/OpenChatCut) into .agents/skills/image-gen in your project. Codex loads it when a task matches its description.
Can I use AI Image Generation 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 0xsline/OpenChatCut --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 AI Image Generation need to run?
SKILL.md names no scripts, command-line tools or credentials: AI Image Generation is instructions for the agent only. Our summary lists: An API key for at least one of the supported image providers.
Does AI Image Generation 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 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. Review the folder before installing.
What licence does AI Image Generation use?
AI Image Generation is published under the AGPL-3.0 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 use?
About 1.3k tokens (SKILL.md is roughly 5.4k 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 2.2k tokens, read only when the agent opens those files.
What are the alternatives to AI Image Generation?
Skills that share tags, products or a category with AI Image Generation: 9Router Image Generation (decolua/9router, 30k stars), Keirouter Image (mydisha/keirouter, 147 stars), AI Image Generation and Editing (zhayujie/CowAgent, 47k stars) and Forge Media Route Layer (0x0funky/agent-sprite-forge, 4.4k 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?
0xsline (a GitHub user) maintains it in 0xsline/OpenChatCut, which has 2,211 GitHub stars. The repository holds 31 skills in this directory. The repository was last updated on October 7, 2026.
Source: 0xsline/OpenChatCut on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.