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photo_crop

Crop Image — Crop an image to a specified region (x, y, width, height) in pixels. [category: photo]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
xNoLeft offset px on the DISPLAYED (EXIF-upright) image — the handler auto-orients before cropping.
yNoTop offset px on the DISPLAYED (EXIF-upright) image — the handler auto-orients before cropping.
fileYesJPG, PNG, WebP, HEIC, TIFF, BMP, or GIF. Output keeps the input format.
widthYesCrop width px. Clipped at the image edge if the region overruns.
heightYesCrop height px. A region overrunning the image edge is clipped, not an error.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.2/5.0
Behavior3/5

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

Annotations already signal readOnlyHint=false and destructiveHint=false, so no contradiction exists and the basic mutation profile is covered. The description adds no side-effect context (e.g., whether output replaces the input or is returned, or auto-orientation behavior), though the schema parameter descriptions do document clipping and EXIF-upright handling.

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?

The description is short and front-loaded with the operation and coordinate format. The '[category: photo]' tag is redundant noise, but the main sentence is efficient and easy to scan.

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?

The tool is simple and the schema compensates for many gaps (accepted formats, auto-orientation, clipping, numeric bounds), so invocation is feasible. However, the description omits usage context versus siblings and there is no output schema describing the returned artifact, leaving minor completeness gaps.

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%, with each parameter already documented including coordinate ranges, defaults, and edge-clipping behavior. The description merely lists the same parameter names and adds no semantic meaning beyond the schema.

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 clearly states the operation ('Crop an image') and the exact coordinate model ('x, y, width, height) in pixels'), so an agent can tell this is a crop tool. It does not explicitly distinguish itself from sibling tools like photo_editor or photo_resize, but the verb+region formula is specific enough for purpose clarity.

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 guidance on when to use photo_crop versus alternatives such as photo_resize, photo_editor, or pdf_crop. The description only defines what the tool does, leaving the selection decision entirely to inference from the name.

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

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