Generate image

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

The description discloses several behaviors not visible in annotations: real API credit costs, sequential generation slowdown on Gemini for n>1, automatic switch from gpt-image-2 to gpt-image-1.5 for transparent backgrounds, model-specific image size handling, and MCP output token limits for return_image. This goes well beyond the sparse annotations.

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 four sentences, each carrying essential info: core function, return value, output_path preference, and cost warning. It is front-loaded with the primary purpose and avoids filler while remaining comprehensive.

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?

With no output schema, the description explains the return format (absolute paths + provider/model metadata). It covers cost, output path fallback chain, allowed directories via list_capabilities, transparency caveats, and return_image token limits — a thorough treatment for a 10-param tool with no output schema.

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?

All 10 parameters already have detailed descriptions in the JSON schema (100% coverage), so the description adds little per-parameter semantics. The only extra guidance is preferring an absolute output_path and noting cost implications, which doesn't elevate beyond the schema-driven baseline of 3.

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 opens with a specific verb+resource: 'Generate one or more images from a text prompt using Gemini or OpenAI image models and save them to disk.' This clearly distinguishes it from sibling edit_image (which edits existing images) and names the underlying providers and model families.

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?

The description gives explicit usage cues: strongly prefer an absolute output_path, call list_capabilities to see configured providers/allowedDirs, and use low quality for cheap drafts. It doesn't explicitly state when to choose generate_image over edit_image, so it lacks a full when-not-to-use contrast.

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