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jdsalasca

Aseprite Asset MCP

by jdsalasca

render_onion_skin

Render nearby animation frames as translucent ghost overlays in a PNG, letting you preview motion and timing between frames.

Instructions

Render neighboring animation frames as translucent onion-skin ghosts into a PNG.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
afterNo
scaleNo
beforeNo
filenameYes
frame_indexYes
ghost_opacityNo
output_filenameYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

C2.6/5.0
Behavior2/5

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

Annotations are absent, so the description carries the full burden of behavioral disclosure. It states the tool renders ghosts into a PNG, implying it produces a file, but does not disclose side effects such as whether it overwrites existing files, modifies the source animation, or requires specific permissions. The safety profile (read-only vs. destructive) is unknown, which is a significant gap for a tool that creates an output file.

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 a single, compact sentence with no filler words. It efficiently states the action and output in 10 words. This is an example of excellent conciseness.

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

Completeness1/5

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

With 7 parameters, no output schema, and zero schema coverage, the description is severely incomplete. It does not explain the output format details, how edge frames are handled, the relationship between before/after and frame_index, or what the scale and ghost_opacity parameters do. An agent cannot confidently call this tool correctly based solely on this description.

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

Parameters1/5

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

Schema description coverage is 0%, so the description must compensate for the undocumented parameters. It mentions 'neighboring frames' and 'onion-skin ghosts' but provides no explanation for the 7 parameters (filename, frame_index, output_filename, before, after, scale, ghost_opacity). The description adds no meaning beyond the parameter names, leaving the agent to guess how to set values correctly.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'Render' and the resource 'neighboring animation frames as translucent onion-skin ghosts into a PNG.' It conveys the core action and output. However, it does not differentiate this tool from closely related siblings like set_onion_skin or compare_frames, which also deal with frame visualization. The purpose is clear but not unique.

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus alternatives. The description does not mention when onion-skin rendering is appropriate, nor does it contrast with sibling tools such as set_onion_skin (which toggles the onion-skin overlay) or compare_frames (which compares frames). The agent is left to infer usage from the name and description.

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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