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export_slice_metadata

Export Aseprite slices as JSON metadata, automatically detecting type and ID from slice names or user data. Includes bounds, pivot, nine-slice, and raw data.

Instructions

Export every slice as engine-agnostic JSON (aseprite_mcp.slice_metadata.v1).

Each slice becomes ``{name, type, id, bounds, pivot, nine_slice, color, data,
raw_data}``. **Type detection:** a slice's user-data JSON ``type`` wins; otherwise the
name convention ``<type>:<id>`` (recognized types: hitbox, hurtbox, collision, interact,
pivot, origin, attach, spawn, nine_slice — anything else becomes ``"custom"``, never an
error). ``id`` comes from the data ``id`` or the name's ``:<id>`` suffix. ``nine_slice``
(Aseprite's 9-patch center) and ``pivot`` are emitted whenever the slice has them. Slice
user-data that is valid JSON is parsed into ``data``; the raw string is kept in ``raw_data``.

Args:
    output: Destination .json path. Defaults to ``<sprite>_slices.json`` beside the sprite.
    overwrite: Replace an existing file (default False = no-clobber).

Returns a ``workflow_manifest.v1`` manifest (kind ``engine_metadata``).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
outputNo
filenameYes
overwriteNo
Behavior4/5

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

With no annotations, the description carries the full burden. It discloses behavioral traits: file output defaults, overwrite flag behavior, type detection rules, and data parsing logic. However, it does not explicitly state that it creates a file (though implied by output parameter).

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 well-structured with a clear header, format details, type detection rules, and argument list. It is slightly long but every sentence contributes value. No redundancy.

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?

Given 3 parameters, no output schema, and no annotations, the description is highly complete: it explains the return type (workflow manifest), covers edge cases in type detection, and specifies format structure. An agent can reliably invoke this tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema has 0% description coverage, so the description fully compensates. It explains each parameter: output defaults to <sprite>_slices.json, filename is required, overwrite controls replacement. This adds essential meaning beyond 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 clearly states it exports every slice as engine-agnostic JSON, specifies the format version, and details the output structure. It distinguishes this tool from siblings like list_slices or export_layers by focusing on slice metadata export with specific transformation logic.

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

Usage Guidelines3/5

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

The description implies usage for exporting slice metadata in a standardized format but does not explicitly state when to use this tool versus alternatives like list_slices for basic listing or other export tools. No direct mention of when not to use.

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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