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Batch operations

aseprite_batch

Execute multiple Aseprite operations in a single call, reducing round trips and token usage. Run drawing, layer, frame, and save commands sequentially.

Instructions

Runs several operations in ONE call, in order (saves round trips and tokens). Each item is {"op": , ...the same arguments as the tool aseprite_}. Allowed ops: new_sprite, pixel_map, set_pixels, draw, clear, layer, frame, copy, animation, outline, history, save. Stops at the first error; earlier ops stay applied (each op is its own undo step). Returns one short result per op plus the final sprite status if layers/frames changed. Example: [{"op":"layer","action":"new","name":"bg"},{"op":"draw","tool":"filled_rectangle","points":[[0,0],[15,15]],"color":"#5fcde4"},{"op":"layer","action":"new","name":"fg"},{"op":"pixel_map","palette":{"k":"#000"},"rows":["kk"],"x":4,"y":4}]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
opsYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.6.0

TDQS

A4.6/5.0
Behavior5/5

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

With no annotations provided, the description carries full responsibility, and it excels: it states that operations run in order, stops at the first error, earlier ops stay applied, each op is its own undo step, and it returns one short result per op plus final status if layers/frames changed. This is rich, actionable behavioral disclosure.

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 long but every sentence earns its place: purpose, structure, allowed ops, error handling, return format, and a representative example. It is front-loaded with the core purpose and flows logically. Slightly dense but appropriate for a complex batch wrapper.

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

Completeness4/5

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

The description covers all essential aspects: operation ordering, error behavior, undo granularity, return value, and argument mapping to individual tools. The example anchors it. It doesn't enumerate every possible argument for each op, but that would be redundant since they mirror the individual tools, which is explicitly stated. Complete enough for correct usage.

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 coverage is 0%, so the description must explain the only parameter 'ops'. It does so precisely: each item is an object with an 'op' key and 'the same arguments as the tool aseprite_<name>'. The example concretely illustrates the structure. This adds enormous semantic value beyond the bare 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 states a clear, specific purpose: 'Runs several operations in ONE call, in order' – a verb+resource that immediately distinguishes it from the individual sibling tools. It also names the allowed ops, reinforcing what the tool does. This is unambiguous and differentiates from the per-operation tools.

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 explains the benefit ('saves round trips and tokens') which implies when to use it, and the example demonstrates a realistic multi-step workflow. However, it doesn't explicitly say 'use this instead of multiple single calls' or mention when the individual tools might be preferred, so it stops short of a full when/when-not contrast.

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