Recraft v3 — professional design-quality image generation
| Name | Required | Description | Default |
|---|---|---|---|
| size | No | Width and height of the generated image. Size is ignored if an aspect ratio is set. | 1024x1024 |
| style | No | Style of the generated image. | any |
| prompt | Yes | Text prompt for image generation | |
| aspect_ratio | No | Aspect ratio of the generated image | Not set |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It only asserts a quality level and offers no details about output format, potential limitations, or operational behavior. This is insufficient for a generation tool that could return varied output types.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that states the tool's purpose without redundancy. It is front-loaded and easy to parse, earning full marks for conciseness and structure despite being short.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description is too sparse to be complete. It lacks information about the output format (URL, binary, etc.), does not explain how it differs from sibling image tools, and omits usage context. The schema covers parameters but not the broader behavioral or selection context, leaving significant gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with all four parameters having descriptions. The tool description adds no extra parameter semantics, but the baseline of 3 applies because the schema already documents each parameter clearly, including the interaction between size and aspect_ratio.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'professional design-quality image generation' clearly identifies the tool as an image generator, with 'generation' as the verb and 'image' as the resource. It adds a quality differentiator ('professional design-quality') that loosely distinguishes it from other image tools, though it does not explicitly compare to siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternatives. The description does not mention any specific use cases, prerequisites, or exclusions, so an agent has no basis to decide between Recraft v3 and other image generators like FLUX or Ideogram.
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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Six of eight tools are for image generation, with overlapping capabilities and only subtle differentiators (speed, quality, text rendering). An agent cannot easily determine which model to use for a generic image generation request, leading to high ambiguity.
All tool names follow the same snake_case pattern using provider_model format (e.g., black_forest_labs_flux_pro, stability_ai_sdxl). The convention is uniform across the entire set, making it predictable and easy to parse.
The count of 8 tools is within the ideal range for a media studio, but the heavy redundancy of image generation models makes the set slightly bloated. Still, the overall scope is clear and manageable.
The tool surface covers the primary media generation modalities—image, video, and text-to-speech—which aligns with the 'Media Studio' purpose. Minor gaps exist (e.g., no image editing or audio-to-text), but core generation workflows are well covered.