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Glama

zoom

Magnifies a specified screen region to make small text or icons readable, with optional upscaling by a chosen factor.

Instructions

Magnify a region (x, y, width, height) of the screen to read small text or icons.

The image is upscaled by factor (default: to about 1568px on the long side, at most 4x). Image pixel (px, py) is screen pixel (x + px / factor, y + py / factor).

Input Schema

NameRequiredDescriptionDefault
xYes
yYes
widthYes
factorNo
heightYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It does disclose meaningful behavior — the upscale cap ('about 1568px on the long side, at most 4x') and the pixel coordinate mapping — which is genuinely useful. It omits whether this is non-destructive/read-only, how the result is delivered (image payload vs handle), and any cost or rate considerations for repeatedly zooming.

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?

Three short blocks: purpose first, then the upscale rule, then the coordinate transform. Every sentence carries information the schema does not, and nothing is repeated from the input schema.

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?

For a five-parameter, annotation-free tool with no output schema, the description covers the region semantics, the scaling behavior, and the coordinate math an agent needs to interpret the returned image. The remaining gap is the return payload itself and the zoom-vs-screenshot decision, which is where an agent is most likely to go wrong.

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

Parameters4/5

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

Schema coverage is 0%, so the description must compensate, and it largely does: x/y/width/height are framed as a screen-pixel region, and `factor` gets both a default behavior and a hard ceiling. The inverse mapping formula makes the relationship between image pixels and screen pixels unambiguous. Minor gap: units for x/y/width/height are only implied by the mapping formula.

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?

States a specific verb and resource ('Magnify a region of the screen') plus the intent ('to read small text or icons'), which naturally separates it from the plain screenshot sibling. It stops short of naming screenshot explicitly, so differentiation relies on inference.

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 'to read small text or icons' implies when to reach for zoom, but there is no explicit guidance such as 'use this instead of screenshot when detail is too small to read'. No prerequisites, no when-not-to-use, no named alternative among the many siblings.

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