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Upscale without blur

upscale_pixel_art

Scale pixel art up by a whole number using nearest-neighbour sampling so pixels stay sharp for previews, store pages or social posts.

Instructions

Scale pixel art up by a whole number with nearest neighbour, so pixels stay sharp (for previews, store pages or social posts).

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": {
      "input": "<input>"
    },
    "name": "upscale_pixel_art"
  }
}

Input Schema

NameRequiredDescriptionDefault
inputYesPath or URL of a PNG image
scaleNo
outputNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.2

TDQS

A3.9/5.0
Behavior3/5

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

With no annotations, the description carries the full load; it does disclose the resampling method (nearest neighbour) and that scaling is by a whole number, which are genuine behavioral traits. However, it never says whether a file is written, what happens when 'output' is omitted, whether existing files are overwritten, or what the tool returns.

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?

A single sentence that front-loads the operation and method, then appends the relevant use cases in parentheses. No filler, nothing repeated from structured fields.

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?

For a three-parameter tool with no annotations and no output schema, the definition is workable but thin: the destination behavior for 'output', accepted input formats beyond PNG, and any return value are unspecified. An agent can invoke it, but not predict exactly what side effects to expect.

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 coverage is only 33%, so the description should compensate more than it does. 'Whole number' usefully clarifies the integer nature of 'scale', but 'input' and 'output' get no explanation beyond the schema's one-line path note, and the default (8) and bounds (2–64) are left entirely to the schema.

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 (scale up), a specific resource (pixel art), the algorithm used (nearest neighbour), and the outcome (pixels stay sharp). It is instantly distinguishable from siblings like pixelate_image, extract_palette, and remap_palette, which perform unrelated operations.

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 concrete usage contexts (previews, store pages, social posts), which tells an agent when this tool is the right fit. It stops short of any exclusions or explicit comparison to pixelate_image, which is the inverse operation an agent might confuse it with.

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