Get one frame of a capture as an image

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

Annotations already declare readOnlyHint true, so the description adds extra context: the image is downscaled and costs substantially more tokens than the structured form. This goes beyond the annotation's safety signal, though it doesn't mention potential errors or output format specifics.

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?

Three focused sentences: one for function, one for usage context, one for cost warning. Each sentence adds distinct value with no redundancy or filler.

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?

For a simple two-parameter tool with no output schema, the description fully covers purpose, when to use it, and an important cost caveat. Annotations cover the read-only nature, making this complete in context.

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 schema already provides 100% coverage for both parameters (id and frame) with detailed descriptions. The tool description adds no additional parameter-level semantics, so the baseline score 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?

The description clearly states the tool returns actual pixels of one frame as an image, distinguishing it from sibling tools like get_capture which returns structured data. It also specifies that the image is downscaled for model readability, making the purpose unambiguous.

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 explicit use cases: visual questions that text and coordinates cannot settle, such as spacing, style, colour balance, or imagery without text. It also contrasts with the structured form of the same capture, implicitly indicating when not to use this tool.

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