Extract Image Query

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

No annotations are provided, so the description carries the full burden. It discloses the core processing ('noun extraction') and output (a search query), but lacks detail on edge cases, failure modes, or the exact output format. It is not misleading but leaves room for ambiguity.

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 that conveys the tool's purpose and mechanism without wasted words. It is appropriately concise and structured for quick understanding.

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?

Given the tool's simplicity (one parameter), the description is fairly complete. However, with no output schema, it does not specify the exact return type (e.g., whether the query is a string or object), and it does not clarify how this tool relates to sibling search tools. Still, it covers the essential transformation.

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 already provides a description for 'context' ('Free-form text to extract search terms from'), and the tool description does not add significant new semantics beyond that. Schema coverage is 100%, so a baseline of 3 is appropriate.

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?

Description clearly states a specific action ('Transform free-form text into an optimized image search query') and mechanism ('noun extraction'), distinguishing it from sibling search/attribution tools. It names the resource and the transformation clearly.

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?

Provides clear context for when to use (given free-form text like UI copy or context) but does not explicitly mention alternatives or when not to use. It implies the use case without exclusions, so slightly below an explicit 5.

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