Skip to main content
Glama
wassermanproductions

unofficial-davinci-mcp

resolve_apply_lut

Apply a .cube LUT to specific clips or all clips on a video track. Perform a dry run to preview changes, then confirm to apply.

Instructions

Apply a .cube LUT to clips on a timeline video track. dry_run first, then confirm. Live tier only. To produce the LUT file itself, use the color_match engine (both tiers).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
confirmNoMust be true when dry_run is false, to apply the plan.
dry_runNoWhen true (default), return the plan without changing anything.
lut_pathYesPath to a .cube LUT.
node_indexNoGrade node to set the LUT on.
track_indexNoVideo track.
clip_indexesNo1-based clip positions; omit for all clips on the track.
Behavior4/5

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

With no annotations provided, the description bears the full burden of behavioral disclosure. It effectively communicates the dry-run/confirm workflow and tier restriction, but could further elaborate on side effects or failure modes.

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 consists of three concise sentences, each adding distinct value: purpose, workflow, and alternative tool. No unnecessary words or redundancy.

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?

Given the tool's complexity (6 parameters, no output schema) and the presence of sibling tools, the description covers the core workflow and constraints adequately. Some parameter behaviors (e.g., clip_indexes, node_index) rely on schema descriptions, which is acceptable.

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 description coverage is 100%, so parameters are already well-documented. The description adds minimal additional meaning beyond the schema, such as the dry_run/confirm pattern, but doesn't significantly enhance parameter understanding.

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 the tool applies a .cube LUT to clips on a timeline video track. It distinguishes from sibling tool color_match by specifying that color_match produces the LUT file, whereas this tool applies it.

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

Usage Guidelines5/5

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

The description explicitly advises to dry_run first then confirm, which is a clear workflow directive. It also restricts usage to Live tier and directs users to color_match for LUT production, providing explicit alternatives.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/wassermanproductions/unofficial-davinci-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server