Generate images from visual prompts through the NormaHub API using GPT Image or Grok Imagine models.
Generate images using GPT Image or Grok Imagine Image via NormaHub API.
| Name | Required | Description | Default |
|---|---|---|---|
| model | No | Image model ID (gpt-image-2.5-flare, grok-imagine-image-2.0) | gpt-image-2.5-flare |
| prompt | Yes | Visual prompt describing the image to generate |
Changes observed during successful MCP inspections.
v0.2.5Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden and only says the operation uses an API. It does not disclose auth needs, rate limits, cost, async behavior, or what is returned (URL, base64, file), which are important for an image-generation tool.
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?
A single front-loaded sentence with no wasted words. It communicates the core action and supported models efficiently.
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?
No output schema exists, and the description does not explain the return format or any post-call behavior. For a generation tool with no annotations, this leaves important invocation context missing.
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%, so the schema already documents both prompt and model. The description adds no additional meaning about model selection tradeoffs or prompt formatting beyond what the schema provides.
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?
States a specific verb and resource: "Generate images" and names the supported models. It is distinguishable from sibling video/audio tools, but it does not explicitly contrast with normahub_generate_video or other alternatives.
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?
No guidance on when to use this tool versus siblings, prerequisites, model selection criteria, or limitations. The usage context is only implied by the tool name and description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.