Scenario Gemini Image logo

Scenario Gemini Image

Organization
scenario-labs
scenario-gemini-image

Use when generating or editing images with Google's Gemini image models (Nano Banana) on Scenario via MCP: text-to-image, natural-language instruction editing, identity locking or style transfer from reference images, multi-image fusion, pulling stills from a video clip, Google Search grounding, thinking level tuning, 512 to 4K output, or choosing between Flash, Pro, and Lite. Keywords: Gemini 3.1 Flash, Gemini 3.0 Pro, Gemini 3.1 Lite, Nano Banana 2, Nano Banana Pro, txt2img, img2img.

Overview

Publisherscenario-labs
Repositoryskills
Skill namescenario-gemini-image
Stars
970
Forks
114
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by scenario-labs on GitHub. Read the source before you install it.

Installation

Install the Scenario Gemini Image AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/scenario-labs/skills/tree/main/skills/scenario-gemini-image
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/scenario-labs/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/skills/scenario-gemini-image .claude/skills/scenario-gemini-image
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Scenario Gemini Image in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Scenario Gemini Image on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Scenario Gemini Image is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Scenario Gemini Image

Overview

Gemini, Google's image family on Scenario (the Nano Banana line), generates and edits through one required prompt: edits are instructions against the references, never mask painting. Discover members with search and treat model_schema_get as the contract: the creative fields are shared and nearly everything else is per member.

Connection and the core loop: see the scenario skill in this repo; model-agnostic image work: the scenario-image skill. Gemini video belongs to the scenario-gemini-omni skill; Gemini speech models are the audio domain. If a sibling skill named here is missing from your available skills, ask the user to install it (npx skills add scenario-labs/skills --skill <name>); unattended, proceed from tool schemas and flag the gap.

Quick reference

Three members at authoring time (per-member facts move, so read the schema):

MemberResolutionSets it apart
3.1 Flash512 to 4K, default 1Kvideo input, four thinkingLevel steps, Search grounding
3.0 Pro1K to 4K, default 2Kbuilt for complex instruction edits and multi-image fusion
3.1 Litefixed 1K, no resolutionfastest and cheapest; thinkingLevel is MINIMAL or HIGH

Shared fields: referenceImages (up to 14, an array even for one), numOutputs (1 to 4 variations of one prompt), aspectRatio (21:9 through 9:16 plus the default auto; pin the ratio when a placement demands one), and a prompt cap near 250000 characters, so a full brief fits verbatim. Flash alone takes video (one clip, about 15 MB, sampled at videoFps, default 1 fps) to pull stills from footage; video and referenceImages are mutually exclusive. useGoogleSearch (Flash and Pro) grounds the run in live web context and moves the price, like every field marked cost_impact. No mask, seed, or negative-prompt field exists: regional edits are sentences, and reruns give variations, not reproductions.

Write instructions, not tags

Describe subject, setting, and style in plain sentences. For edits, state the change and what must survive it: "keep the shoe's shape, colors, and branding unchanged; place it on a sunlit deck". With several references, assign roles by position ("image 1 is the character's face, image 2 the outfit, image 3 the background style"); unassigned references blur together. Lock identity explicitly: say the features must be preserved while pose, lighting, or scene changes. Quote in-image copy exactly and say where each block sits ("the title reads 'LUMEN', top third"); unquoted wording is treated as a theme to depict, not copy to render. When one word keeps mangling, do not rerun the design: pass the keeper in referenceImages and spell the word letter by letter ("the title reads 'LUMEN', spelled L, U, M, E, N"), changing nothing else. On Flash and Lite, thinkingLevel defaults to HIGH, the careful setting; drop to MINIMAL for speed on simple runs.

Price the member before the batch

The cost cliff sits between members more than between resolutions: at authoring time the same 1K edit cost about double on Flash what Lite charged, Pro's 2K default roughly doubled it again, and Lite returned in under half the time. dry_run=true the same parameters on two members before any batch, and re-estimate whenever resolution, numOutputs, references, or useGoogleSearch change.

Worked example: product restyle with locked identity

  1. search with target="models", query="gemini", public=true. Video and speech members surface too; pick an image member, e.g. model_google-gemini-3-1-flash (a live hit at authoring time: re-discover each session).
  2. model_schema_get with that id: fields, caps, and defaults.
  3. upload_asset the product photo and the style reference (see the scenario skill) to get asset ids.
  4. model_run with that model_id, dry_run=true, and parameters={"prompt": "Image 1 is the product: keep its shape, label, and colors exactly. Image 2 sets the mood: warm sunset palette, soft shadows. Place the product on a marble counter in natural window light.", "referenceImages": ["asset_a", "asset_b"], "aspectRatio": "4:5", "resolution": "2K", "numOutputs": 2} for the cost estimate.
  5. Repeat model_run with wait=false, then jobs_wait with the returned job id, re-called with pending_job_ids on timeout, never a second model_run.
  6. asset_display to review both variations, asset_download to save the pick.

Common mistakes

  • Passing video and referenceImages together on Flash: they are mutually exclusive.
  • Reaching for seed or mask: neither exists on any member; describe the edit and batch numOutputs to pick from.
  • Carrying fields across members: resolution fails on Lite, thinkingLevel on Pro, video everywhere but Flash.
  • Keyword-tag prompts: comma lists underperform; write the sentence you would give a designer.
  • Several references with no roles: outputs blend them; say which image is which by position.
  • Enabling useGoogleSearch for stylistic work: it raises cost and earns it only on factual, real-world subjects.

Frequently asked questions

What does the Scenario Gemini Image AI skill do?

Use when generating or editing images with Google's Gemini image models (Nano Banana) on Scenario via MCP: text-to-image, natural-language instruction editing, identity locking or style transfer from reference images, multi-image fusion, pulling stills from a video clip, Google Search grounding, thinking level tuning, 512 to 4K output, or choosing between Flash, Pro, and Lite. Keywords: Gemini 3.1 Flash, Gemini 3.0 Pro, Gemini 3.1 Lite, Nano Banana 2, Nano Banana Pro, txt2img, img2img.

Why use Scenario Gemini Image on TypingMind?

Because you install it once and use it with any model. Scenario Gemini Image is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Scenario Gemini Image in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/scenario-labs/skills/tree/main/skills/scenario-gemini-image. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Scenario Gemini Image?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Scenario Gemini Image?

As many as you like. As long as a model supports skills, you can use Scenario Gemini Image with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Scenario Gemini Image AI skill free?

Yes. It is published on GitHub by scenario-labs under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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