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.
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Run score Not tested
See how to installReview the instructions the agent will receive before you install.
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.
At authoring time (names from the live schema):
| Member | Makes | Source input | Ratios |
|---|---|---|---|
| 2.5 | txt2img | none | 11, incl. 21:9 |
| 2.5 Pro | txt2img | none | 8 |
| 2.5 Edit | img2img | referenceImages, array of one | 8 |
| 2.5 Pro Edit | img2img | image, single file | 8 |
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.
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.
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.
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).model_schema_get on the generation pick: ratio list, prompt cap, defaults.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.wait=false, then jobs_wait with the returned job id, re-called with
pending_job_ids on timeout, never a second model_run.asset_display the four outputs and keep one asset id.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.referenceImages (array of exactly one) and
image (single file) are member-specific shapes.aspectRatio is an enum and the lists differ
(21:9, 5:4, and 4:5 lived on one member at authoring time).scenario-image skill).No reviews yet. Tell others what you thought.
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Handle review comments received on GitHub for the current branch's PR or a given PR number or URL, by triaging each unresolved thread, fixing what is warranted, pushing, and replying in each thread, when asked to address, fix or answer PR comments. Works in any Scenario repository.
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Generate one short Conventional Commits squash message describing only the net diff between the PR's base and head, set its header as the PR title, validate it with the repository's commitlint and both copy its description to the clipboard and display it, when asked for a squash message. Works in any Scenario repository, whatever its default branch.
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Refresh the current pull request description from its net changes, following the repository's PR template, when asked to update or write the PR summary. Works in any Scenario repository, whatever its default branch.
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Use when connecting an AI agent to Scenario (scenario.com) through MCP, or when a task involves generating images, video, 3D, audio, sprites, textures, or game assets. Also when picking a Scenario model, running a LoRA, refining a generation prompt, uploading reference images, waiting on generation jobs, checking credits or quota, hitting Scenario auth, scope, or Forbidden errors, or setting up mcp.scenario.com in Claude Code, Cursor, VSCode, or another agent.
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Use when generating or handling 3D assets through the Scenario MCP server, including text-to-3D or image-to-3D meshes, GPT-6 Astra 3D or Claude Opus 5.5 3D, GLB, FBX, OBJ, STL, or VOX files, PBR-textured or game-ready models, voxel models, multi-view reconstruction, editing a mesh by prompt, retexture, remesh, UV unwrap, auto-rigging a biped or quadruped, or retargeting an animation, previewing a mesh in the 3D viewer, or downloading a model for import into Unity, Unreal, Godot, or Blender.
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Use when generating navigable 3D worlds or Gaussian splat scenes on Scenario via MCP: text-to-world, image-to-world, a 360 panorama or skybox turned into a walkable splat, multi-view photos or a video walkthrough reconstructed as a splat, or one object photo to splat. Keywords: World Labs Marble 1.1, 1.1 Plus, 1.0 Draft, Hunyuan World, HY World, image-to-skybox, skybox-to-splat, multiview-to-splat, TripoSplat, gaussian splatting, 3DGS, spz, world generation, explorable scene, VR.
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