get_camera_image

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

With no annotations, the description carries full behavioral burden. It discloses read-only nature, subscription behavior, message types (CompressedImage/Image), return format, size limit (4 MB), and error response behavior. This is comprehensive.

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 moderately long but well-structured with Args and Returns sections. Every sentence adds operational detail (size limits, raw image metadata, readonly mode), making it appropriately sized.

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 complexity (subscription, timeout, size handling, output schema), the description covers all operational aspects including error conditions and return payload, making it complete. The output schema is described in prose, which is acceptable.

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 has no descriptions and 0% coverage, so the description fully compensates. It explains topic with an example and guidance, and timeout with default and max clamp. Additionally, it documents the return structure.

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 'Grab one frame from a camera topic, for vision-capable models,' clearly stating the tool's function with a specific verb and resource. It distinguishes itself from sibling tools like get_topic_snapshot by emphasizing camera images and VLM workflows.

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?

It provides clear context for when to use: 'This is the bridge for VLM / vision-language-action workflows' and advises 'Prefer a compressed topic.' However, it does not explicitly name alternative tools or exclusionary criteria, so it stops short of full when/when-not guidance.

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