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recraft_generate_image

Generate images from text descriptions with configurable model, style, color palette, text placement, and size, including SVG output for vector models.

Instructions

Generate images from text prompt. Supports all Recraft models (V4, V4 Vector/SVG, V4 Pro, V3, V2), 70+ styles, color palette control, text layout, and multiple sizes. V4 Vector models produce SVG output.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nNoNumber of images to generate (1-6)
sizeNoImage size (e.g., 1024x1024, 1344x768) or ratio (e.g., 16:9, 1:1 for vector models)1024x1024
modelNoModel: recraftv4_1, recraftv4_1_vector, recraftv4_1_pro, recraftv4_1_pro_vector, recraftv4_1_utility, recraftv4_1_utility_vector, recraftv4_1_utility_pro, recraftv4_1_utility_pro_vector, recraftv4, recraftv4_vector, recraftv4_pro, recraftv4_pro_vector, recraftv4_styles, recraftv4_styles_vector, recraftv4_styles_pro, recraftv4_styles_pro_vector, recraftv3, recraftv3_vector, recraftv2, recraftv2_vectorrecraftv4
styleNoStyle name (V3/V2 only). E.g., photorealism, illustration, vector_art, pixel_art, icon
promptYesImage description (max 10,000 chars for V4, 1,000 for V3/V2)
controlsNoGeneration controls
style_idNoCustom style UUID (from recraft_create_style). Cannot combine with style.
text_layoutNoText placement on image
negative_promptNoWhat to exclude from the image
response_formatNoResponse formaturl

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.2.0

TDQS

A3.5/5.0
Behavior3/5

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

With no annotations provided, the description carries the full burden and does add useful behavior context: it declares support for all Recraft model families and reveals that V4 Vector models produce SVG output, which is a genuine behavioral trait not obvious from the schema. However, it omits operational behaviors that matter when calling a paid generation API, such as credit consumption, rate limits, or how output is delivered beyond the schema's response_format enum.

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

Conciseness5/5

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

Three sentences totaling roughly 45 words, with the core purpose front-loaded in the first sentence. Each subsequent sentence adds non-redundant capability context (model coverage, style/control options, SVG behavior), so no sentence is wasted.

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

Completeness3/5

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

The schema fully documents all ten parameters, so the parameter surface is well covered and the description does not need to repeat it. For a tool with this complexity, the description gives a solid high-level orientation but leaves gaps: no differentiation from overlapping generation siblings, no credit or cost disclosure, and no mention of prompt-length or other constraints that only appear buried in the schema.

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 baseline is 3 even without parameter detail in the description. The description's references to models, styles, color palette, text layout, and sizes largely mirror existing schema properties, but the note that V4 Vector models produce SVG adds a selection-relevant meaning not present in the model enum descriptions, keeping it at baseline rather than below.

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 opening sentence 'Generate images from text prompt' states a specific verb, resource, and input source, leaving no ambiguity about the core function. The supporting sentences enumerate capabilities (all model families, 70+ styles, palette, text layout, sizes, SVG output) that clearly distinguish it from specialized siblings like recraft_erase_region, recraft_variate_image, or recraft_image_to_image.

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

Usage Guidelines2/5

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

The description gives no guidance about when to use this tool versus any of its 23 siblings. Overlapping tools such as recraft_batch_generate, recraft_generate_sized, recraft_generate_asset, and recraft_variate_image are never mentioned, and there is no when-to-use or when-not-to-use statement. The only routing signal is the tool's name itself.

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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