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luquimbo

DaVinci Resolve MCP Server

by luquimbo

render_set_settings

Apply render settings to DaVinci Resolve exports using a dictionary of parameters like resolution, frame rate, audio codec, and export alpha.

Instructions

Apply render settings from a dictionary.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
settingsYesA dict of render setting key-value pairs. Valid keys: TargetDir, CustomName, FormatWidth, FormatHeight, FrameRate, MarkIn, MarkOut, AudioCodec, AudioBitDepth, AudioSampleRate, ExportAlpha.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

With no annotations, the description must carry the burden of behavioral disclosure. It only states the action without explaining side effects, whether settings persist, what happens to existing render jobs, or what is returned. This is a significant gap for a setter-type tool.

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 a single, direct sentence that is immediately clear and waste-free. It is front-loaded with the verb and object, but the extreme brevity leaves out important context that would earn additional sentences.

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

Completeness2/5

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

Given the presence of a nested settings object with many possible keys and a complex render context, the description is far too minimal. It lacks any information about return values (though an output schema exists), behavioral effects, or how the settings dictionary content maps to render outcomes. The tool likely requires more explanation for reliable use.

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 100% because the 'settings' parameter description lists valid keys and indicates additionalProperties. The tool description adds little beyond restating that it's a dictionary, but the high schema coverage means the description doesn't need to compensate. It provides a baseline-3 contribution.

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 action (apply) and resource (render settings), and the phrase 'from a dictionary' indicates the input format. It distinguishes from siblings like render_set_format_and_codec by focusing on a general settings dict, though the boundary with render_load_preset is not explicit.

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

Usage Guidelines1/5

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

No guidance on when to use this tool versus alternatives such as render_load_preset or render_set_format_and_codec. There is no mention of prerequisites, context, or exclusions, leaving the agent without enough information to decide correct usage.

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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