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Before/after comparison GIF

animate
Read-onlyIdempotent

Make a looping before/after comparison GIF from two images.

A slider sweeps across the frame and reveals the before image over the after image, with Before and After labels. Use it to show the effect of an edit such as upscaling, retouching or colour correction. Both images should show the same scene: the before image is resized to the after image's size. The GIF is at most 800 px on its longer side and loops one 3 s back-and-forth sweep. A small crisp.photos mark sits in the bottom right corner.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "url_before": "<url_before>",
      "url_after": "<url_after>"
    },
    "name": "animate"
  }
}

Input Schema

NameRequiredDescriptionDefault
url_afterYesPublic https URL of the edited image, showing the same scene. JPEG, PNG or WebP, at most 20 MB.
url_beforeYesPublic https URL of the original image. JPEG, PNG or WebP, at most 20 MB.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Annotations only declare the safe/idempotent/open-world profile; the description goes well beyond them by disclosing output traits the agent cannot infer: 800 px maximum on the longer side, a single 3 s back-and-forth loop, Before/After labels, a crisp.photos watermark bottom right, and that the before image is resized to the after image's dimensions.

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 core action and output traits are front-loaded in the first two sentences, and the remaining sentences each add a distinct constraint or output detail. It is slightly dense with output minutiae (exact loop length, watermark placement), but nothing is redundant.

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

Completeness5/5

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

With only two required parameters, full schema coverage, and clear annotations, the description covers everything needed: inputs, preconditions, output format, dimensions, and duration. The absence of an output schema is fully compensated by the described return characteristics.

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 100% and both URL parameters are documented with format and size limits, so the baseline is 3. The description adds genuine meaning beyond the schema: the two images must depict the same scene, and the before image gets resized to match the after image, which clarifies how the pairing is handled.

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 opens with a specific verb and resource — 'Make a looping before/after comparison GIF from two images' — and immediately explains the mechanism (a slider sweeping across the frame). An agent knows exactly what artifact this produces without opening the schema.

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?

It gives a clear use case ('show the effect of an edit such as upscaling, retouching or colour correction') plus a precondition that both images show the same scene. No alternatives or exclusions are named, but no siblings exist in the supplied catalog, so the only real gap is the absence of explicit when-not-to-use guidance.

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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