New: 98,000+ skills indexed from GitHub repos with 100+ stars · every skill safety-checkedBrowse top skillsTop skills
Esc to closeBrowse all skills
Submit a skillBrowse skills
Submit a skillBrowse skills

Agent skill

Scenario Mai Image

by scenario-labs in scenario-labs/skills

A skill your agent uses when generating or editing images with Microsoft MAI Image models on Scenario via MCP: photoreal or stylized text-to-image with legible in-image typography, posters…

MITAuto-check passedMedia & Creative

Install Scenario Mai Image

skills CLI
$ npx skills add scenario-labs/skills --skill scenario-mai-image -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install scenario-labs/skills scenario-mai-image --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/scenario-labs/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/scenario-mai-image .claude/skills/scenario-mai-image && rm -rf skills-src

Use ~/.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/

Facts

Skill name
scenario-mai-image
GitHub stars
946
Token cost
~1.5k tokens
SKILL.md length
777 words
Files
1
Skills in repo
146
Repo updated
First seen
Licence
MIT

At a glance

A skill your agent uses when generating or editing images with Microsoft MAI Image models on Scenario via MCP: photoreal or stylized text-to-image with legible in-image typography, posters…

  • Works in 6 steps: search with target="models", query="mai… → model_schema_get on the generation pick:… → model_run with dry_run=true and… → …
  • Editing images with Microsoft MAI Image models on Scenario via MCP: photoreal
  • SKILL.md covers Overview, Quick reference, Typography is the lever and Editing: preserve first, one…, plus 2 more sections
  • Calls npx

What it does

Scenario Mai Image is an agent skill from scenario-labs/skills. Use when generating or editing images with Microsoft MAI Image models on Scenario via MCP: photoreal or stylized text-to-image with legible in-image typography, posters, packaging, magazine covers, ads, key art, or instruction-based editing such as text swaps, recoloring, object removal or replacement, background swaps, lighting changes, and full restyles. Keywords: MAI Image 2.5, 2.5 Pro, 2.5 Edit, 2.5 Pro Edit, Microsoft, txt2img, img2img, typography, text rendering, image edit.

Its SKILL.md is about 1.5k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Media & Creative, covering Typography and Image generation. It works with Model Context Protocol. The repository describes itself as: Get production-ready images, video, audio, and 3D from any AI agent: skills that pick the right model, price before spending, and keep characters and brands consistent through… The licence is MIT.

When your agent uses it

  • Editing images with Microsoft MAI Image models on Scenario via MCP: photoreal
  • Stylized text-to-image with legible in-image typography
  • Magazine covers
  • Instruction-based editing such as text swaps

Example prompts

  • “/scenario-mai-image”

Requirements

  • Node.js

Workflow steps

6 steps, taken from the first numbered list in SKILL.md.

  1. search with target="models", query="mai image", public=true. Note the generation and edit hits, e.g. model_microsoft-mai-image-2-5-pro and…
  2. model_schema_get on the generation pick: ratio list, prompt cap, defaults.
  3. model_run with dry_run=true and parameters={"prompt": "A photorealistic poster of a climber on a granite wall at dawn, warm rim light, the…
  4. Repeat with wait=false, then jobs_wait with the returned job id, re-called with pending_job_ids on timeout, never a second model_run.
  5. asset_display the four outputs and keep one asset id.
  6. model_schema_get on the edit pick, then model_run with parameters={"referenceImages": ["asset_x"], "prompt": "Keep the climber, lighting…

What it can do on your machine

Read from SKILL.md and the folder at commit f6f8ab7. 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

    Shell commands in SKILL.md call:

    • npx

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use npx, 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 no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Scenario Mai Image loads about 1.5k tokens when it runs. Until then it costs about 126 tokens; SKILL.md has 777 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~126
When it runs · the whole SKILL.md, loaded when a task matches
~1.5k

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 scenario-labs/skills at commit f6f8ab7, republished under its MIT licence (© scenario-labs). 777 words, ~1,477 tokens.

Download SKILL.mdSave it as .claude/skills/scenario-mai-image/SKILL.md (or your agent's skills folder).
name
scenario-mai-image
description
Use when generating or editing images with Microsoft MAI Image models on Scenario via MCP: photoreal or stylized text-to-image with legible in-image typography, posters, packaging, magazine covers, ads, key art, or instruction-based editing such as text swaps, recoloring, object removal or replacement, background swaps, lighting changes, and full restyles. Keywords: MAI Image 2.5, 2.5 Pro, 2.5 Edit, 2.5 Pro Edit, Microsoft, txt2img, img2img, typography, text rendering, image edit.
license
MIT

Scenario MAI Image

Overview

MAI Image 2.5, Microsoft's image family on Scenario, splits into generation members (2.5, 2.5 Pro) and instruction editors (2.5 Edit, 2.5 Pro Edit). The family trait is typography: in-image headlines, labels, and taglines come back legible and placed where the prompt put them: the pick for posters, packaging, covers, and key art that carry real copy. Discover members with search and treat model_schema_get as the contract: the four agree on almost every field and disagree on the one that carries the source image.

Connection and the core loop: see the scenario skill in this repo; model-agnostic image work (sizing families, masks, upscales): the scenario-image skill. 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

At authoring time (names from the live schema):

MemberMakesSource inputRatios
2.5txt2imgnone11, incl. 21:9
2.5 Protxt2imgnone8
2.5 Editimg2imgreferenceImages, array of one8
2.5 Pro Editimg2imgimage, single file8

All four share prompt (4096 characters on 2.5 and Edit, 5000 on the Pro pair), aspectRatio (an enum defaulting to auto), and numOutputs (1 to 4, each added image adds cost). No width, height, seed, negative prompt, or mask field exists: aspectRatio is the only sizing control, and edits target elements by naming them in prose. On the generators auto picks a ratio from the prompt; on the editors it matches the source, so leave it there unless re-framing is the point.

Typography is the lever

Write prose sentences, not tag lists: the family reasons over subject, composition, materials, lighting, and mood in that rough order. Wrap exact in-image copy in quotes so it renders verbatim, and give each text block a role, a style, and a place ("the headline 'GAME DAY' in bold condensed type across the top third"). Unquoted or vague copy comes back paraphrased or mangled, and many small text blocks compete, so group them. At authoring time text rendering was tuned for English and outputs landed near 1K, so plan a downstream upscale for print or hero use. Steering is positive-only: explore with numOutputs 2 to 4 and refine the sentence rather than hunting for a seed.

Editing: preserve first, one change

Both editors take one source image and a plain instruction, under different fields: Edit wants referenceImages with exactly one asset id in an array, Pro Edit wants image as a single file. Porting a parameter block between them breaks the run, so re-read the schema when switching. Structure the prompt as what must stay unchanged, then one change, naming the exact element and its exact new state, with replacement copy in quotes ("change the sign to 'OPEN 24/7', same font and color"). Chain passes for several changes; edits hold identity well across iterations. The two shared one public image-edit arena entry (top 3 at authoring time) while a Pro Edit asset cost about four times an Edit asset, so dry_run both and start with Edit.

Show full SKILL.md (262 more words)Show less

Worked example: a campaign poster, then a copy swap

  1. search with target="models", query="mai image", public=true. Note the generation and edit hits, e.g. model_microsoft-mai-image-2-5-pro and model_microsoft-mai-image-2-5-edit (live hits at authoring time: re-discover each session).
  2. model_schema_get on the generation pick: ratio list, prompt cap, defaults.
  3. model_run with dry_run=true and parameters={"prompt": "A photorealistic poster of a climber on a granite wall at dawn, warm rim light, the headline 'ASCEND' in tall condensed sans-serif across the top, a small tagline 'Hold your line' lower left, editorial sports aesthetic.", "aspectRatio": "2:3", "numOutputs": 4}. numOutputs moves cost, so re-estimate after changing it.
  4. Repeat with wait=false, then jobs_wait with the returned job id, re-called with pending_job_ids on timeout, never a second model_run.
  5. asset_display the four outputs and keep one asset id.
  6. model_schema_get on the edit pick, then model_run with parameters={"referenceImages": ["asset_x"], "prompt": "Keep the climber, lighting, and layout unchanged. Change only the headline to 'ASCEND HIGHER', same font, color, and placement."}; jobs_wait, then asset_display.

Common mistakes

  • Carrying one editor's source field to the other: referenceImages (array of exactly one) and image (single file) are member-specific shapes.
  • Leaving in-image copy unquoted: only quoted text renders verbatim.
  • Stacking several edits in one instruction: one change per pass, then chain.
  • Sending pixel sizes or a ratio the member lacks: aspectRatio is an enum and the lists differ (21:9, 5:4, and 4:5 lived on one member at authoring time).
  • Re-running for a pixel-identical result: no seed exists; keep the winning asset and edit it forward.
  • Shipping the 1K output to print: upscale downstream (see the scenario-image skill).

© scenario-labs, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/scenario-mai-image of scenario-labs/skills.

Open the folder on GitHubat commit f6f8ab7

Compare with similar skills

Scenario Mai Image 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.

Scenario Mai Image compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Scenario Mai Image this skillscenario-labs/skills946—~1.5kAutomated safety check: PassMIT
Image Prompt ReverseLunarXuan/image-prompt-reverse467—~678Automated safety check: PassGPL-3.0
Nous Brandingmagnus919/agent-skills115—~4kAutomated safety check: PassMIT
Cover Design Psychologyrevfactory/harness-1001.3k—~1.3kAutomated safety check: PassApache-2.0
Minimal Zine Poster GeneratorLiamGvchi/gc-minimal-zine-poster7.3k—~2.9kAutomated safety check: PassMIT
SEO Image GeneratorAgriciDaniel/claude-seo19k2 repos~2.1kAutomated safety check: PassMIT

Similar skills

  • Image Prompt Reverse

    LunarXuan/image-prompt-reverse

    Analyze user-provided reference images and reverse-engineer high-fidelity AI image-generation prompts.

    467 GitHub stars~678 tokensUpdated 1 mo ago
    Media & CreativeAuto-check passed

  • Nous Branding

    magnus919/agent-skills

    Generate images and content consistent with the Nous Research brand identity.

    115 GitHub stars~4k tokensUpdated yesterday
    Media & CreativeAuto-check passed

  • Cover Design Psychology

    revfactory/harness-100

    A specialized skill for the cover-designer agent covering cover design psychology.

    1.3k GitHub stars~1.3k tokensUpdated 6 mo ago
    Media & CreativeAuto-check passed

  • Minimal Zine Poster Generator

    LiamGvchi/gc-minimal-zine-poster

    Creates or analyzes quiet, paper-texture zine posters with big negative space, one color accent and experimental type, returning an image prompt and the generated poster.

    7.3k GitHub stars~2.9k tokensUpdated 1 mo ago
    Media & CreativeAuto-check passed

  • 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.

    19k GitHub starsUsed in 2 repos~2.1k tokens
    Media & CreativeAuto-check passed

  • CapCut Video Director

    sun-guannan/VectCutAPI

    Guides an agent in building and polishing CapCut Desktop video projects through the CapCut MCP server and direct timeline file edits, including vertical canvas, subtitles and audio.

    2.3k GitHub stars~1.7k tokensUpdated 8 days ago
    Media & CreativeAuto-check passed

More from scenario-labs/skills

All 146 skills in this repo

  • Scenario Blender Grease Pencil

    scenario-labs/skills

    A skill your agent uses when drawing or animating with Grease Pencil in Blender 5.x from Python: 2D or 2.5D illustration, frame-by-frame animation, a cutout or part-based 2D character, strokes with…

    946 GitHub stars~4.5k tokensUpdated yesterday
    Auto-check passed

  • Scenario Blender Hair

    scenario-labs/skills

    A skill your agent uses when grooming hair or fur in Blender with hair curves, such as a character hairstyle, animal fur, procedural fur in geometry nodes, or hair cards and mesh hair for games.

    946 GitHub stars~4.7k tokensUpdated yesterday
    Auto-check passed

  • Scenario Blender Lighting Rendering

    scenario-labs/skills

    A skill your agent uses when lighting, rendering or compositing in Blender: light a character, product or hero shot, interior at dusk or night, three-point or motivated lighting, sun and sky, HDRI…

    946 GitHub stars~5k tokensUpdated yesterday
    Auto-check passed

  • Scenario Chatgpt Pet Create

    scenario-labs/skills

    A skill your agent uses when creating a ChatGPT pet or Codex pet with Scenario: hatching an animated companion from a text idea, a character, mascot or brand cue, or reference photos and art; making…

    946 GitHub stars~3.6k tokensUpdated yesterday
    Auto-check passed

  • Scenario Godot Animation

    scenario-labs/skills

    A skill your agent uses when animating characters or scenes in Godot 4.7: AnimationPlayer clips and RESET, AnimationTree state machines and blend spaces built in code, Mixamo or glTF import, loop…

    946 GitHub stars~4.7k tokensUpdated yesterday
    Auto-check passed

  • Scenario Godot Audio

    scenario-labs/skills

    A skill your agent uses when adding or fixing sound in Godot 4.7: audio buses and effects, volume sliders, 'too many sounds', combat audio with hundreds of enemies, sounds clipping or distorting, 3D…

    946 GitHub stars~4.7k tokensUpdated yesterday
    Auto-check passed

Works with

Categories

Questions about Scenario Mai Image

What does Scenario Mai Image do?

A skill your agent uses when generating or editing images with Microsoft MAI Image models on Scenario via MCP: photoreal or stylized text-to-image with legible in-image typography, posters…. Scenario Mai Image is an agent skill from scenario-labs/skills. Use when generating or editing images with Microsoft MAI Image models on Scenario via MCP: photoreal or stylized text-to-image with legible in-image typography, posters, packaging, magazine covers, ads, key art, or instruction-based editing such as text swaps, recoloring, object removal or replacement, background swaps, lighting changes, and full restyles.

When should I use Scenario Mai Image?

Scenario Mai Image fits situations like: editing images with Microsoft MAI Image models on Scenario via MCP: photoreal; stylized text-to-image with legible in-image typography; magazine covers; instruction-based editing such as text swaps.

How do I install Scenario Mai Image in Claude Code?

Run `npx skills add scenario-labs/skills --skill scenario-mai-image -a claude-code`. Or copy the skill folder (skills/scenario-mai-image in scenario-labs/skills) into .claude/skills/scenario-mai-image in your project. Claude Code loads it when a task matches its description.

How do I install Scenario Mai Image in Codex?

Run `npx skills add scenario-labs/skills --skill scenario-mai-image -a codex`. Or copy the skill folder (skills/scenario-mai-image in scenario-labs/skills) into .agents/skills/scenario-mai-image in your project. Codex loads it when a task matches its description.

Can I use Scenario Mai Image 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 scenario-labs/skills --skill scenario-mai-image -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/scenario-mai-image, .gemini/skills/scenario-mai-image, .github/skills/scenario-mai-image and .opencode/skills/scenario-mai-image in your project.

What does Scenario Mai Image need to run?

Going by SKILL.md and its folder, Scenario Mai Image needs the command-line tools its instructions call (npx). Our summary lists: Node.js.

Does Scenario Mai Image access the network?

SKILL.md contains no URLs. Its commands use npx, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Scenario Mai Image 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 Scenario Mai Image use?

Scenario Mai Image is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Scenario Mai Image use?

About 1.5k tokens (SKILL.md is roughly 5.9k 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 Scenario Mai Image?

Skills that share tags, products or a category with Scenario Mai Image: Image Prompt Reverse (LunarXuan/image-prompt-reverse, 467 stars), Nous Branding (magnus919/agent-skills, 115 stars), Cover Design Psychology (revfactory/harness-100, 1.3k stars) and Minimal Zine Poster Generator (LiamGvchi/gc-minimal-zine-poster, 7.3k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Scenario Mai Image?

scenario-labs (a GitHub organization) maintains it in scenario-labs/skills, which has 946 GitHub stars. The repository holds 146 skills in this directory. The repository was last updated on October 10, 2026.

Source: scenario-labs/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.