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correct_pixelart

Clean up existing pixel art without changing its size: sharpens edges, removes stray pixels, and tightens palettes while preserving transparency. Pass multiple same-size frames to keep animation consistent.

Instructions

Clean up existing pixel art WITHOUT changing its size: sharpens edges, removes stray/anti-aliased pixels, and tightens the palette while keeping the sprite on its pixel grid. Good for art that went through a lossy pipeline, hand-drawn art, or nearly-on-grid output from other tools. Pass several same-size frames together (an animation, or a character's directions) so they stay consistent. Max area 1024x1024; transparency is preserved. If the image is upscaled, run unzoom first.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
imagesYesImage(s) to clean up. All must be the same size
strengthNoHow far the model may move from your art (0.0-1.0, default 0.1). Start low; raise only if the art needs real repair

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.8.0

TDQS

A4.9/5.0
Behavior5/5

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

With no annotations provided, the description carries the full behavioral disclosure burden and does so well: no size change, pixel-grid retention, transparency preservation, max area of 1024x1024, and consistent treatment of multi-frame inputs. These are genuine behavioral guarantees, not just a restatement of the tool name.

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?

Four sentences, each earning its place: core capability, ideal use cases, multi-frame guidance, and constraints/prerequisite. The key constraints are front-loaded in the first sentence, and there is no filler or repetition of the schema.

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?

For a two-parameter image transformation tool with no output schema, this description is complete. It covers when to use the tool, input constraints, behavioral guarantees, and the upscaled-image prerequisite. The only omission is an explicit return format, but that absence is acceptable given no output schema is provided.

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%, so the baseline is 3 because parameters are already documented. The description adds value above the schema: passing several same-size frames together keeps animation/directions consistent, and the max-area constraint applies to the image inputs. This goes beyond the schema's field-level descriptions.

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?

States a specific verb ('clean up') and resource ('existing pixel art') while also declaring the non-goal 'WITHOUT changing its size'. The concrete effects (sharpen edges, remove stray/anti-aliased pixels, tighten palette) clearly differentiate it from siblings like image_to_pixelart or unzoom.

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

Usage Guidelines5/5

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

Explicitly enumerates when to use the tool: lossy pipeline output, hand-drawn art, or nearly-on-grid output from other tools. It also names a relevant alternative/action for a specific case: 'If the image is upscaled, run unzoom first.' This gives an agent actionable selection criteria.

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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