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process_sprite

Transforms external PNGs into clean sprites: removes backgrounds, auto-crops, pads to square, and splits sprite sheets for game asset use.

Instructions

Post-process an existing PNG image into a clean sprite. Handles background removal, auto-crop, square padding, and sprite sheet splitting. Use this for images from external sources that need processing.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
namesNoNames for split sprites (default: 0, 1, 2, ...)
splitNoSplit sprite sheet into individual sprites by detecting content boundaries
squareNoPad output to square (default: false)
paddingNoPadding around content in pixels (default: 2)
skipCropNoSkip auto-crop step
inputPathYesPath to the input PNG file
thresholdNoColor detection threshold 0-255 (default: 20)
outputPathNoOutput path. For split mode: prefix for frame files (e.g. "assets/snake" → "assets/snake-head.png")
skipTransparentNoSkip background removal step
Behavior3/5

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

No annotations are provided, so the description must carry the burden of behavioral disclosure. It does list the processing steps (background removal, auto-crop, etc.), which is helpful. However, it does not disclose whether the input file is modified in place, what happens if outputPath is omitted, or any side effects like generating multiple files in split mode. This is a notable gap for a tool that processes existing files.

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 two sentences long with no fluff. The first sentence states the core purpose and key operations, and the second provides usage context. Every word earns its place.

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?

With 9 parameters and no annotations or output schema, the description is somewhat thin. It gives a high-level overview but does not explain the return value or what the output looks like, especially in split mode. The schema covers parameter details, but for a complex tool, more contextual information about side effects and output would be expected.

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 input schema has 100% coverage, with descriptions for all 9 parameters. The tool description adds no additional parameter semantics beyond the schema. The baseline for full schema coverage is 3, and the description does not go above that.

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?

Description uses specific verb 'post-process' with resource 'existing PNG image' and lists concrete operations: background removal, auto-crop, square padding, sprite sheet splitting. This clearly distinguishes it from sibling tools like forge_sprite or optimize_sprite, which are more about creation or optimization.

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 final sentence 'Use this for images from external sources that need processing' provides a clear context for when to use the tool. It doesn't explicitly state when not to use it or mention alternatives, but the context is sufficiently clear for an agent to make a decision.

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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