get_perception_snapshot

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 states the output includes multiple images and object data in a dictionary with paths, but lacks details on potential latency, format specifics, or blocking behavior. Adequate but not rich.

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 very concise with two sentences plus a return line, front-loaded with key information. Every sentence adds value without redundancy.

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 complexity of multi-modal data and the existence of an output schema (covering return details), the description is reasonably complete. It mentions images and object data, though it could be slightly more specific about the number of images or type of detection data.

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?

No parameters exist, baseline is 4. The description adds meaning beyond the empty schema by explaining what the tool returns and its composition.

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 verb 'Get' and the resource 'comprehensive perception snapshot', listing specific components (camera, LiDAR, object detection overlays). It distinguishes well from siblings like capture_camera_view, get_detected_objects, and visualize_lidar_scene.

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 description implies usage for a multi-sensor snapshot, but does not explicitly state when to use this tool versus alternatives like capture_camera_view or get_detected_objects. No when-not-to-use guidance is given.

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