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Opentoonz Render Frame

opentoonz_render_frame

Render a single OpenToonz frame to PNG for visual inspection, returning an inline downscaled preview and a saved file; set max_width to control preview size.

Instructions

Render a single frame to a PNG — the agent's 'look' at the result.

The image is returned inline as well as on disk, so looking at a frame costs no extra round-trip. It is downscaled to 768px wide by default, so a large scene costs far fewer image tokens; pass max_width to change that, or max_width=0 for the full-resolution frame. Only the returned preview is affected — the scene's resolution is unchanged, and opentoonz_render / opentoonz_render_video output is never downscaled.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
frameNo
sceneYes
out_nameNolook
max_widthNo
workspaceYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.8.0

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations, the description carries the full behavioral burden and discharges it well: the image is returned inline AND written to disk, downscaling is preview-only, the default width is 768px, and max_width=0 restores full resolution. It does not state overwrite behavior, permissions, or what happens if the frame doesn't exist, but it is far richer than a bare 'render' description.

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?

Front-loaded with the core action, then the token-saving rationale, then the max_width escape hatch. Three tight sentences, no repetition, every clause carries information an agent would otherwise have to guess.

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?

For a 5-parameter tool with no annotations and no output schema, the description covers the return channel and the key sizing parameter thoroughly. The remaining gap is out_name, which determines the on-disk artifact name but is never mentioned, and no guidance on workspace/scene requirements.

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?

Schema coverage is 0% across 5 parameters, so the description must compensate, and it does so well for max_width (default downscale to 768px, 0 means full resolution) — a parameter whose schema default of null is otherwise opaque. It says nothing about frame, scene, workspace, or out_name (the on-disk filename, default 'look'), leaving the majority of parameters undocumented.

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 and resource (render a single frame to PNG) and frames it as the agent's 'look' at the result. It also distinguishes itself from opentoonz_render and opentoonz_render_video by stating their output is never downscaled, so an agent can tell which render tool to reach for.

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 description explains the intended use case (inspecting a frame cheaply, no extra round-trip) and when to vary behavior via max_width. It stops short of an explicit 'use this instead of opentoonz_render when you only need to see the result' rule, so the routing is implied rather than spelled out.

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