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iftahs
by iftahs

crop_preview

crop_preview
Read-only

Generate a 1:1 or zoomed JPEG preview of any image region to inspect star shapes, halos, ringing, and noise texture. Specify a center point or rectangle to evaluate details before full processing.

Instructions

1:1 (or zoomed) JPEG of a region — for star shapes, halos, ringing, noise texture. Defaults to a 512 px box at the image centre. Pass center [x,y] or rect. zoom >1 magnifies.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYes
rectNo[x, y, width, height] in image pixels
sizeNo
zoomNo
centerNo
stretchNo
stf_from_cropNoCompute the stretch from the crop instead of the full image

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare the operation read-only and non-destructive. The description usefully adds that the output is a JPEG, that the default view is a 512 px center box, and that zoom > 1 magnifies. It does not explain stretch behavior or how the JPEG is returned, but the annotation-covered safety profile lowers the burden.

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?

The description is short and front-loaded: it states the output type and purpose first, then packs defaults, coordinate options, and zoom behavior into three tight sentences. Every clause adds operational value, and there is no redundant filler.

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

Completeness3/5

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

Core invocation details are present — required id context, center/rect alternatives, default box size, and zoom semantics — and annotations cover the safety profile. However, the `stretch` parameter is unexplained and, with no output schema, the description does not state whether the JPEG is returned inline, as a path, or as a saved artifact, leaving some ambiguity for an agent.

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?

The description adds meaning for center, rect, zoom, and the default size semantics, all of which the schema largely leaves undocumented. However, with only 29% schema coverage, the unexplained `stretch` enum (stf/hard/none) is a notable gap, and `stf_from_crop` is only covered by the schema. The description partially compensates but does not fully explain all parameters.

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 identifies a specific resource and outcome — a '1:1 (or zoomed) JPEG of a region' — and gives a concrete inspection use case ('for star shapes, halos, ringing, noise texture'). It is clear about what the tool produces, though the verb is implicit and it does not explicitly contrast with sibling render/crop tools.

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

Usage Guidelines4/5

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

The description communicates the intended context: pixel-level visual inspection of stars and artifacts, which implies when to use it versus full-frame rendering or statistical measurement. It does not mention exclusions or name alternatives like render_preview or crop, but the context is clear and not misleading.

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