vector_capture_image

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

With no annotations, the description carries the full disclosure burden. It clearly states the core action and underlying API call, but it does not mention side effects, blocking behavior, return format, or whether the robot state is modified. This is adequate for a zero-parameter read-like capture, but leaves some behavioral details unstated.

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 a single front-loaded sentence that states the action, resource, and API method with no wasted words. It is concise without sacrificing essential information.

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 parameterless, single-action tool, the description is largely complete: it tells the agent what to invoke and what to expect conceptually. It could be more explicit about the returned frame format, but its simplicity and lack of parameters keep the omission minor.

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 zero parameters, so there is no semantic ambiguity to clarify. The description adds nothing beyond the schema, but nothing is needed; the baseline of 4 for a parameterless tool applies.

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 uses a specific verb, 'Capture', and a clear resource, 'a single camera frame', with the exact API method named. This unambiguously distinguishes it from vision-analysis siblings like vector_find_faces and vector_face_detection.

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?

There is no guidance about when to use this tool versus alternatives. It does not mention cases where vector_scan, vector_look, or other vision tools would be more appropriate, so the agent must infer usage from the name alone.

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