multi_image_edit

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

No annotations are provided, so the description must disclose behavioral traits. It only states the high-level action without addressing permissions, image uploads, output handling, or potential side effects. This leaves significant behavioral uncertainty.

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?

Single sentence, front-loaded with the core purpose and illustrative examples. No wasted words.

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?

Despite the schema richness, the description omits important operational details such as how results are returned (e.g., file output), any constraints on image combinations, or the role of the optional parameters in practice. With no output schema or annotations, the description alone is insufficient for advanced use.

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?

The input schema covers all 6 parameters (100%) with detailed descriptions for each, so the tool description need not add parameter-level details. The description itself adds no extra meaning beyond the schema, meriting the baseline.

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 clearly states the tool edits or combines multiple images using Gemini image models, with concrete examples (transfer pose, style, combine elements). This distinguishes it from siblings like generate_image (creation) and edit_image (likely single image).

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 examples imply when to use this tool (multi-image transformations like pose transfer or element combination), but it does not explicitly contrast with alternatives or state exclusions. The context is clear enough for basic selection.

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