Use when generating or editing images with Reve models on Scenario via MCP: text-to-image from a prompt alone, instruction edits (swap poster text, recolor a product, change materials, relight or restyle a scene), merging references with consistent subjects, blending up to 6 images into one composite, or choosing between Reve v2.1 and Reve Remix. Keywords: Reve v2.1, Reve Remix, Reve AI, txt2img, img2img, frame tags, compositing, style blending, text swap.
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查看安装方法安装前可以查看交给 AI 代理的指令内容。
Reve, Reve AI's image family on Scenario, splits into two members that share a brand and little
else: v2.1 is a reasoning-driven generator and instruction editor (a top-2 text-to-image arena entry
at authoring time), Remix a fast, cheap compositor that blends several images into one. Discover
them with search and treat model_schema_get as the contract: they disagree on field names,
prompt caps, and ratio lists.
Connection and the core loop: see the scenario skill in this repo; model-agnostic image work: 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 (the live schema wins):
| Member | Capabilities | References | Prompt cap | Aspect ratios |
|---|---|---|---|---|
| Reve v2.1 | txt2img, img2img | references, optional | 4000 | 18 values, 4:1 through 1:4, default auto |
| Reve Remix | img2img | referenceImages, required, 1 to 6 | 2560 | 7 values, 16:9 through 9:16, default 3:2 |
Three parameters each: the prompt, the reference array, aspectRatio. Neither member has a mask,
seed, width and height, negative prompt, or batch-count field, so an edit is scoped by wording and
size comes only as a ratio. auto (v2.1 only) picks a fitting shape; pass an explicit ratio when
the deliverable demands one.
Pick by job. v2.1 covers generation from a prompt alone and precise edits: swap the text on a
poster, recolor a product, change a material, relight or restyle, merge references while every
subject stays consistent. Remix blends photos, illustrations, or design assets into one cohesive
composite. Where either would do, dry_run both: at authoring time a v2.1 run cost several times a
Remix run and took over a minute at p50 against Remix's twenty-odd seconds.
In a v2.1 prompt, a reference is addressed with a <frame>N</frame> tag, numbered from 0 in the
order the assets appear in references: the first is <frame>0</frame>, the second
<frame>1</frame>. Use the tags whenever more than one reference is in play; without them the model
guesses which image you mean. Remix documents no tag syntax: name subjects in plain words ("the
bottle from the first image, the lighting from the second").
Neither member takes a mask, so the prompt carries the whole edit: state what changes and what must
stay untouched. v2.1's reasoning rewards specific plain-language instructions over keyword lists,
and its 4000-character budget leaves room for constraints. For masked inpainting on an exact region,
use a model that exposes a mask field (see scenario-image).
search with target="models", query="reve", public=true. At authoring time the hits were
model_reve-v2-1 (generation and instruction edits) and model_reve-remix (multi-image blends);
re-discover each session.model_schema_get on the pick: field names, caps, and the ratio list before anything else.upload_asset the poster (see the scenario skill) to get an asset id.model_run with that model_id, dry_run=true, and
parameters={"prompt": "Replace the headline on the poster in <frame>0</frame> with 'SUMMER SALE', matching the original font, perspective, and lighting. Change nothing else.", "references": ["asset_x"], "aspectRatio": "auto"}
for the cost estimate.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.asset_display to check the swap, then asset_download to save.<frame>1</frame> is the second reference; the first is
<frame>0</frame>.references, Remix takes referenceImages; each
schema lists only its own.referenceImages is required (1 to 6 at authoring time);
prompt-only generation belongs to v2.1.aspectRatio is the only
size control.jobs_wait timeout as an error: p50 latency topped a minute at authoring time;
re-call with pending_job_ids.还没有评价。欢迎分享你的使用感受。
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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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