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generate_grok_image

Creates images from text prompts using Grok through snapgen, with options for speed/quality, orientation, and multiple results.

Instructions

Generate an image with Grok. POST /uapi/v1/imagen/grok.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeNoSPEED
promptYes
file_urlsNo
num_resultNo
orientationNolandscape
ref_historyNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.3/5.0
Behavior1/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It only restates the action and supplies a POST endpoint; it does not say whether generation is synchronous or asynchronous, what authentication is required, whether there is a cost, or what the response looks like—especially important given the sibling wait_for_generation tool implies async workflows.

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 two short, front-loaded sentences with no filler. The endpoint sentence is a minor technical detail that may not aid tool selection, but the overall structure is compact and readable.

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

Completeness1/5

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

For a six-parameter image-generation tool with no annotations and no output schema, the description omits critical context: mode differences, num_result, orientation, file_urls, ref_history, and async behavior. It is not complete enough to let an agent invoke the tool confidently.

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

Parameters1/5

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

Schema description coverage is 0% and six parameters (prompt, mode, file_urls, num_result, orientation, ref_history) are completely undocumented in both the schema and the description. The description adds no parameter-level meaning, such as the distinction between SPEED and QUALITY or how ref_history or file_urls are used.

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

Purpose4/5

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 an image with Grok'), and naming Grok differentiates it from the sibling generate_gpt_image. However, it does not distinguish this tool from generate_image or explain when to prefer one over the other.

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?

There is no explicit when-to-use guidance, no prerequisites, and no routing advice among the multiple image-generation siblings (generate_image, generate_gpt_image). The reader is left to infer usage entirely from the tool name and provider.

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