Skip to main content
Glama

Circle crop

circle_crop

Creates a round profile picture by center-cropping to a square and applying a circular transparent mask. PNG, WebP, and AVIF keep transparent corners; JPEG flattens them onto a background color.

Instructions

Make a round profile picture: center-square crop plus a circular transparent mask. png (default), webp and avif keep the transparent corners; jpeg flattens them onto a background color.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sizeNoOutput side in pixels (default: the largest centered square).
inputYes
formatNo
outputNoOutput file path. Default: next to the input, with a suffix and the right extension.
previewNoAttach a small JPEG preview to the result (default true).
qualityNoLossy quality 1-100 (default 80). Ignored for png.
backgroundNoCSS color used to flatten transparency when the output is jpeg (default #ffffff).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.1

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations, the description carries the disclosure burden and does disclose non-obvious behavior: the center-square crop, transparent corners, and jpeg-specific background flattening. It could add detail about overwriting/output behavior, but the core behavioral traits are clearly stated.

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 sentences, no filler: the first states the purpose and mechanism, the second covers the format-dependent edge cases. Every clause adds useful information and the most important detail is front-loaded.

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 7-parameter image transform with no output schema or annotations, the description plus schema covers the essential usage: what it does, how transparency is handled per format, and the default png behavior. It omits explicit when-not-to-use guidance and output/response shape, but these are either in the schema or not required for this straightforward operation.

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 71%, and the description adds meaning beyond the schema for format and background: png is the default, transparency is preserved for png/webp/avif, and jpeg flattens against the background color. The input parameter is not explained, but its role is inferable and the key format semantics are supplied.

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 names a specific verb and resource ('Make a round profile picture') and explains the mechanism ('center-square crop plus a circular transparent mask'). This clearly distinguishes it from generic crop_image or resize_image siblings and leaves no ambiguity about what the tool produces.

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?

Usage context is implied by the phrase 'round profile picture', but the description never says when to prefer it over alternatives like crop_image, convert_image, or roundcut_web_tools, nor does it mention exclusions. An agent is left to infer selection criteria.

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