Scenario game assets skill

Scenario Game Assets

Overview

Scenario's public catalog carries purpose-trained models per asset type (sprites, icons, props, tilesets, isometric scenes, pixel art, concept art) plus utilities for background removal, upscaling, and pixel cleanup. Discover by asset type, inspect the schema, generate, post-process, export. A sheet whose cells are one character's animation frames, and any walk cycle, loop, or GIF, belongs to scenario-sprite-animation. Connection and core loop: see the scenario 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

Task	Call
Find a model by asset type	recommend with the asset need in the user's own words (sprite, game icon, tileset, isometric, pixel art); search is for a member known by name
Inspect inputs	model_schema_get (always before model_run)
Generate	model_run (dry_run=true prices a batch; launch wait=false), then jobs_wait; on timeout re-call with pending_job_ids
Transparent background	recommend for a native-alpha generator first; else for background removal on the asset
Upscale or enhance	recommend for upscaling (2x to 16x tools exist)
Pixel-art cleanup	recommend for cleanup (grid snapping, palette reduction)
Parallax background planes	Split a painted background with the layer tool (recommend, capability: "img2img"), or generate one plane per run; see Parallax backgrounds
Export for an engine	asset_download with format="png"

Worked example: a transparent potion icon set

Request: "four style-matched potion icons for an RPG inventory."

1. recommend with the user's own words as prompt ("four style-matched potion icons for an RPG inventory"). Typical picks: cartoon icon LoRAs ("Stylized Game Icons & Props"). Confirm the pick with the user: catalogs differ per team; re-discover, never hardcode model IDs.
2. model_schema_get model_id="<picked id>". Note the prompt field, size fields, and any sample-count parameter.
3. model_run parameters={"prompt": "health potion, corked glass bottle, glowing red liquid, bold outline, centered, plain background"} (a plain field cuts cleanly in a removal pass; a native-alpha model wants the subject alone, never the word transparent). The schema's sample-count parameter repeats one prompt for variants of one item; different items are separate runs varying only the item ("mana potion", "stamina potion") with the wording template fixed. Price with dry_run=true first (one dry run prices one leg; multiply across the batch), then launch with wait=false.
4. jobs_wait job_ids=["<returned job_id>"] (up to 32 ids, one call covers the batch); on timeout re-call with the returned pending_job_ids, never a second model_run. Then asset_display to review, one asset_id per call.
5. Transparency: recommend for a native-alpha generator first, since it makes the icons transparent at the source and skips a billed removal pass per icon. Treat the pick as opaque unless its recommend entry or its schema says it outputs transparency. Fall back to a removal model only when the chosen generator lacks alpha: recommend for background removal (Photoroom, Pixelcut, 851 Labs at authoring time), model_schema_get the pick, then model_run with its image field set to the generated asset id.
6. Optional: upscale keepers (recommend for upscaling, model_schema_get as always; upscalers go 2x to 8x and beyond).
7. asset_download asset_id, format="png" (PNG keeps alpha). Follow redirects: curl -L -o potion.png "<url>".

Style consistency

• The cheap levers first: reuse one seed across the batch, and pin the model's prompt-expansion flag off where the schema has one; an expander rewrites each prompt independently and defeats a fixed template.
• Reference images: upload_asset the art direction images, then pass the asset ids (never local paths) to the model's image or reference parameters.
• asset_describe turns one on-style asset into a promptable style synthesis reusable across prompts (catalog tool, billed, dry_run: true prices it: run via scenario_tools_search + scenario_tool_execute_read; see the scenario skill).
• search target="assets" images={like: ["asset_..."]} finds assets already matching the target look.
• For a locked-in project style, train a custom LoRA on the project's own art (the scenario-model-training skill); trained models use the same generation loop.

Preparing a variation-batch reference

Restyling one approved component into a set (button, panel, popup well, icon family) fails on the reference more often than the prompt: the model treats everything composited onto the object as the object.

• Crop to the object's own bounds. Transparent padding reads as composition: scale and offset drift every run, so sprite-measuring code gets a different box. Trim the alpha, generate, re-pad to a fixed canvas. When the model's supported aspect ratios exclude the source's, aspect also drifts per run; reconcile UI components with a nine-slice-aware rescale (stretch middle bands, keep corners and lettering undistorted) before re-padding.
• Strip baked effects before generating. A drop shadow, outer glow, or bevel in the reference reads as silhouette and comes back thickened, doubled, or fused to the object. Feed flat art and re-apply the effect in engine, where it stays adjustable. For a final PNG matching a shadowed source, lift the source's effect layer by alpha (on a transparent source the shadow is semi-transparent and the object opaque, but so is the object's antialiased rim: take the shadow as the semi-transparent pixels outside a 1 to 2 px dilation of the opaque mask, and keep the rim with the object) and composite it under each output.
• Say which parts are functional. A nine-slice panel needs stretchable middles and fixed corners; diffusion has no concept of either. Name the constraint in the prompt, then check that it held.
• One object, plain field, no scene. Several objects in one reference get recombined into a hybrid.
• Check the alpha edge on any transparent output. Removed shadows leave a semi-transparent fringe; native-alpha models can ship a large semi-transparent glow around the object. Both read as a halo on a colored UI background. Check interior alpha too: a native-alpha model can punch one item's see-through surface (empty glass) to alpha 0 while painting the next item's opaque, so the set disagrees in an engine slot.

Verify the set by measurement, not by eye: compare each output's alpha bounding box against the source before accepting the batch.

Isometric tiles and masked fills

Choose the grid before the style. A 2:1 diamond is a common game projection; a projected hex is a different footprint. Share one projection, placement anchor, light direction, and shadow side across a set. A tile's ground footprint is not its full sprite silhouette: trees and buildings rise above it and may overlap the tile behind. Never clip a tall object through the ground mask. Check a small assembled map for joins, path connections, occlusion, and visual quality before scaling the batch; a clean alpha boundary alone is not acceptance.

Use the isometric template guide to choose a neutral ground or slab reference and separate ground, side, and object regions. The JSON manifest records their geometry, filenames, and source hashes. The template builder, run by a maintainer or an agent needing local geometry, creates the PNGs and manifest. It generates geometry only, not finished game art. Keep the geometry reference separate from the approved style reference; neutral geometry must not force a palette or faceted look. Resolve uploaded assets and publish new versions through the scenario skill's shared asset lifecycle; upload local inputs only when no matching asset is accessible.

Dedicated isometric members exist in the public catalog. recommend with the user's tile need, then model_schema_get. Read the reference, mask, seed, and strength fields instead of assuming they exist or that low strength preserves geometry: conventions vary. Keep the camera and lighting wording fixed while varying the subject. Reuse a seed only when supported. If the model drifts in projection or light despite a consistent reference, use scenario-consistency, then consider scenario-model-training on approved tiles.

For a ground fill or content explicitly bounded to a shape, use masked img2img. If the specialty pick has no mask field, recommend again with capability: "img2img" and the mask need. Read mask polarity and any required base-image field from model_schema_get (scenario-image covers model-specific conventions). Template region images are white inside; adapt them to the model's convention, including alpha if required. The base canvas must match the mask dimensions and placement; an approved style reference does not replace it. When that canvas is opaque, preserve its background during the edit: asking for transparent output simultaneously contradicts the protected-canvas constraint. Extract transparency afterward. Use the ground region for terrain, and the taller object region for trees or buildings; the latter is editing space, never a final silhouette mask.

Run one tile first. Measure changes outside the edit region against the source canvas and inspect the result. A few-pixel overrun on a deliberately bounded ground fill can be clipped to its mask; extensive drift needs diagnosis of polarity, base canvas, and consumed references before retrying. For taller sprites, preserve the object silhouette with native alpha or background removal and verify the ground anchor separately. A deterministic ground mask cannot repair a wrong camera or a poor composition.

A "low-poly" look and a low-poly mesh are different deliverables. The look is a 2D style word on an image model. The mesh is scenario-3d: whether the image-to-3D pick (recommend, capability: "img23d") exposes a polycount target or a topology choice is read off model_schema_get, never assumed, and when it exposes neither a separate remesh utility (its own billed run, found with recommend, capability: "3d23d") brings the count down afterwards. Either way the concept image feeding it wants flat shading, a clean silhouette, and a plain background so the geometry reads.

Terrain tilesets and transitions

A top-down terrain set is a layout contract with the engine: every edge and corner case must exist and join its neighbors. recommend with the user's words, tile size included ("32x32 top-down tileset, grass to dirt transitions"), then model_schema_get. The pixel tileset member at authoring time had a style enum: a full tileset from one terrain prompt, a two-terrain transition mode (extraPrompt or extraImage for the second), plus single tile, variation, and object modes. Its width and height size one tile, not the sheet, and they and the mode move the price, so dry_run first. It promises a simple Wang set, not a 47-tile blob layout: map the tiles onto the engine's autotile rules, and paint a small test map with the downloaded sheet in the engine's tile editor and check the joins before more terrains.

Parallax backgrounds

A parallax background is a stack of depth planes the engine scrolls at different speeds: an opaque sky or far plane, then two or three cutout planes with transparent gaps the planes behind show through. Two routes produce the stack; writing "layers" or "parallax" into one generation prompt produces neither, it returns a single picture of stacked layers, and on a style-trained model it returns several layers painted into one image.

• Split a painted background you already have. The layer extractor is a contested lane (Scenario's own tool competes with third-party splitters), so recommend with capability: "img2img" and the need in the user's words ("separate this background into depth planes for parallax"), then model_schema_get the pick. The purpose-built tool at authoring time took a separationInstruction, a splitting rule and not a scene description ("four planes, front to back: foreground bushes, near trees, far hills, sky"), a maxLayers cap that moves the price, and an inpaint choice for filling the hole each cut leaves, also priced. It returns the cutouts plus a rebuilt background (the rearmost plane), one asset each, so review them one at a time with asset_display. A plane cut from a viewport-sized painting is only as wide as the viewport, and a scrolling plane needs bleed past the camera on both sides. Canvas-expansion tools repaint an opaque image and would fill a cutout's transparent gaps, so widen the painting before splitting it (recommend with capability: "img2img" and the expand need; size the painting for the largest required scroll range; all split planes inherit that width), or take the second route for the near planes.
• Generate one plane per run. Fix the camera, horizon line, light direction and palette words, then vary only the plane's content: the sky and far plane as an ordinary opaque image, each nearer plane as a cutout (a native-alpha generator, or a plain field plus the removal pass above; never the word transparent at a diffusion model). Say what the plane must not contain ("no ground, no sky") so the planes do not repeat each other, and size each plane for the viewport plus its full horizontal scroll-offset range; larger offsets need more bleed, while looping requires seamless edges.

Check the stack before exporting: model_scenario-compose-image (a fixed first-party id, Scenario's single deterministic image compositor, so discovery would only re-derive it) takes the planes as layers, each with source (the asset id) and zIndex in depth order, over canvasMode: "custom" with numeric canvasWidth and canvasHeight and backgroundColor: "transparent". Use the camera viewport dimensions, preserve each plane's source size, and position the shared canvas so bleed lies outside both viewport edges. Equal-width split planes work when that bleed covers each plane's offset range. A second composite with the near planes shifted a few percent in x (a percent string) within its available bleed previews the parallax offset the engine will produce; a seam, a doubled horizon or a plane whose cutout edge shows a halo is visible here, before any engine work. Verify actual alpha, not just the thumbnail. Reject a stack with cutout seams, missing scenery, or foreground objects left in the rebuilt background: shifting the planes exposes those duplicates. Revise the separation or inpaint settings, or use the one-plane-per-run route, within the user's budget; otherwise report a failed preview instead of an engine-ready set. asset_download each accepted plane with format="png" (the far plane too, so the set shares one format), tag them with their depth order, and leave scroll speeds and looping to the engine.

Common mistakes

• Prompting "transparent background" at a diffusion model: outputs are opaque. Cut the background afterward with a removal tool, or pick a native-alpha model.
• Exporting JPG sprites: JPG has no alpha channel; keep format="png".
• Shipping AI pixel art with off-grid pixels or noisy palettes: post-process with a pixel cleanup tool (found with recommend) for grid snapping and a strict palette.
• Skipping model_schema_get: specialty models (the pixel-art family) are txt2img-only with their own fields; generic parameters get rejected.
• Asking one generation for "the layers" of a parallax background: one image comes back; depth planes are a split of a finished painting or one run per plane (see Parallax backgrounds).
• Hand-stitching tilesets: tileset members generate the edge and corner cases; texture-specific upscalers preserve tiling.
• Single-sampling lettered assets: the same recipe can render one word and fail another (dark embossed text, not the reference typography). Generate several samples per run (schema's sample-count parameter) and pin exact hex colors in the prompt when the palette drifts.