Agent Cam MCP Tool

measure

Analyze camera frames or regions to return mean brightness, contrast, lit-pixel percentage, dominant colors, edge density, sharpness, and motion level without heavy image output.

Instructions

Compute quantitative measurements on the camera frame or region without returning heavy images. Returns mean brightness, contrast, lit-pixel percentage, dominant colors, edge density, sharpness (Laplacian variance), and motion level.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "measure"
  }
}

Input Schema

Name	Required	Description	Default
`camera`	No	Camera ID
`region`	No	Optional named region to measure

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Oct 4, 2026

TDQS

A3.8/5.0

Behavior3/5

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

With no annotations provided, the description carries the full behavioral burden. It helps by enumerating the computed metrics and stating the lightweight, non-image return, which implies a side-effect-free read. It stops short of explicitly declaring it is read-only/advisory, whether it analyzes a live frame or cached frame, or any permission requirements.

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

Conciseness5/5

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

Two tight sentences, front-loaded with the action and the key differentiating constraint, then the payload of returned metrics. Every clause earns its place with no filler.

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?

There is no output schema, and the description compensates well by enumerating the exact metrics returned (brightness, contrast, lit-pixel %, dominant colors, edge density, sharpness, motion). The gap is that with zero required parameters it never explains what happens if 'camera' or 'region' is omitted, though for a simple two-param read tool this is minor.

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 description coverage is 100%, so both parameters are already documented in the schema. The description only echoes the camera/region scoping ('camera frame or region') without adding format, default, or behavior detail beyond the schema, so baseline 3 applies.

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

Purpose5/5

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

The description states a precise verb (compute quantitative measurements) and resource (camera frame or region), and immediately distinguishes itself from image-returning siblings like capture_image by noting it works 'without returning heavy images'. An agent can select this over capture_image without opening any schema.

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

Usage Guidelines3/5

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

The phrase 'without returning heavy images' implies the appropriate context (use this when you need numbers, not an image), which is adequate implied guidance. However, it never names capture_image or compare_to_baseline as alternatives, nor does it state any exclusions or prerequisites for use.

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