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Ludo AI Game Assets

by ai.ludo

generateWithStyle

Generate new images that match the visual style of a reference image: supply a style_image (URL or base64) plus a text prompt describing what to create and an image_type (defaults to sprite). The job result is an array of image results, each with a url; request n (1-4) to control the number of variations. The style_image is uploaded and validated, and an image larger than 15MB is rejected with HTTP 400. Credits are charged only on success, scaled to the number of images produced. Use this instead of createImage when style consistency with an existing asset matters; use editImage to alter the content of a specific image rather than borrow its style, and removeBackground to isolate a subject. Pass an optional request_id to tag the results so you can retrieve them later via GET /assets/images/results. Requires an API key (user scope). Returns 202 with a job id immediately; poll getApiJob (pass wait: 30) until status is succeeded, then read its result field, which is exactly the response documented for this operation. Each account may have up to 50 generations queued or running at once; beyond that submissions return 429 (PENDING_JOBS_LIMIT) - wait for jobs to finish.

Credits: This endpoint consumes 0.5 credits per result.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
requestBodyYesPayload for generating new content while maintaining the visual style of a reference image

TDQS

A4.6/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It discloses that the endpoint returns 202 with a job id, requires polling getApiJob, charges credits only on success, rejects images over 15MB with HTTP 400, allows request_id deduplication, and enforces a 50-job concurrency limit with 429 responses. This is rich, actionable behavioral context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is long but front-loaded with the core purpose and contains almost no filler. It duplicates a few schema facts, such as n range and image_type default, but the extra length is justified by the operational details needed because there are no annotations.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

This is a complex asynchronous tool with no output schema and no annotations. The description covers inputs, alternatives, required auth scope, polling workflow, result retrieval, error conditions, quota limits, and credit costs. An agent has enough information to invoke it correctly and interpret the result.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents n, prompt, image_type, style_image, request_id, and augment_prompt. The description mostly restates schema details such as the n range, image_type default, and request_id usage, adding only limited extra meaning beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource: 'Generate new images that match the visual style of a reference image.' It also names the sibling tools it is not, including createImage, editImage, and removeBackground, making the tool's distinct scope immediately clear.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly says when to use this tool: 'Use this instead of createImage when style consistency with an existing asset matters' and contrasts it with editImage and removeBackground. It also explains the asynchronous job flow, polling with getApiJob, and the rate-limit behavior, giving an agent a full decision and execution path.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A4/5.0
Disambiguation4/5

Most tools pair a clear action and asset type (create3DModel, editVideo, removeBackground), and overlapping pairs such as animateSprite vs transferMotion vs animateSpriteKeyframes are carefully differentiated by input mode. The main friction is listApiJobs vs listGenerations, which both return generation history from slightly different scopes.

Naming Consistency4/5

The set is overwhelmingly consistent camelCase verb+noun (create*, edit*, list*, animate*, cancel*), with only minor deviations like generatePose/generateWithStyle alongside createImage and the slightly awkward validateApiKeyEndpoint. There is no chaotic mixing of conventions.

Tool Count2/5

At 31 tools this exceeds the 25+ threshold for 'too many', even though the multimodal game-asset scope explains much of the breadth. Agents face a large selection surface with many generation variants across 3D, sprites, images, audio, and video.

Completeness4/5

Core workflows are covered: image-to-3D plus rigging and animation, sprite pose/rotation/animation/editing, image create/edit/style/background-removal, video create/edit/upscale, and audio SFX/ambiance/music/voice. Minor gaps remain, such as no image upscaler and no individual asset retrieval or deletion.

Resources