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Glama

Look through the camera

look
Read-only

Capture a photo with the robot's front camera to identify sports balls, barrels, AIM robots, or AprilTags with bearings; use the ruler for other objects.

Instructions

Take a photo with the robot's front camera and see it yourself. Objects the robot's onboard AI recognises (sports balls, blue/orange barrels, AIM robots, AprilTags) are listed with their bearing. For anything else, read its bearing off the ruler along the top of the photo.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
overlayNoDraw a bearing ruler and detection boxes on the photo
yolo_detectionNoAlso run YOLO on this computer to label 80 kinds of everyday object (person, cup, bottle, chair...). Takes a few seconds the first time.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.5/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, non-destructive), so the description's job is to add content semantics — and it does, listing the recognised classes and the bearing ruler. It stops short of stating exactly what is returned (image vs structured detections) and omits the on-demand YOLO path.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two tight sentences, front-loaded with the action and immediately followed by what the agent will see. No filler, though the second sentence carries two ideas (detections and the ruler) that could be split for speed of scanning.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description usefully explains what the photo contains and how to derive bearings for unrecognised objects, which is the key thing an agent needs. It is not fully complete since the yolo_detection option and the exact return shape are unaddressed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so both parameters are already documented in the schema. The description references the ruler that the 'overlay' parameter controls, but adds no new detail about the overlay toggle or the yolo_detection option, so baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a concrete verb and resource (take a photo with the front camera) and clarifies the outcome (you see it yourself). It is clear on its own, though it never names siblings like detect_objects or scan_surroundings to distinguish overlapping capability.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no explicit guidance on when to use this versus detect_objects or scan_surroundings, which are close functional siblings. The only routing hint is 'for anything else, read its bearing off the ruler,' which is about interpreting the output rather than choosing the tool.

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