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media.compose

Submit FFmpeg composition and rendering jobs. Combine video clips and output to a specified path, with resumable long-running media processing.

Instructions

Submit an FFmpeg composition/render job.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.0.0

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations and no output schema, the description carries the full burden of explaining behavior, but it only says 'Submit an FFmpeg composition/render job.' It does not state whether this is asynchronous, whether it returns a job ID, what side effects occur, or whether it validates inputs before queuing. This is a significant gap for a job-submitting tool.

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 focused sentence with no filler, fluff, or repetition. It is front-loaded with the core action and resource, making it easy to parse quickly.

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?

For a job-submission tool with no annotations, no output schema, and an effectively empty parameter schema, this description is too thin. It does not mention what the return value is, whether results are fetched via media.job.status, or what constraints apply to clips and outputPath. An agent would need additional documentation to invoke it correctly.

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?

The input schema provides only the required names clips and outputPath with no property descriptions, so the description's mention of 'FFmpeg composition/render' adds useful context for inferring their meaning. However, additionalProperties is true, and the description does not explain accepted formats, required clip structure, or output path conventions, leaving substantial ambiguity.

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 identifies a specific action ('Submit') and a specific resource ('an FFmpeg composition/render job'), so an agent knows this tool is about launching rendering work. It does not explicitly distinguish itself from related tools like media.video.generate or media.job.run_once, but the phrase 'FFmpeg composition/render job' provides reasonable specificity.

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?

The description gives no guidance on when to use this tool instead of siblings such as media.video.generate, media.job.run_once, or media.director.review. There is no mention of prerequisites, queuing semantics, or which workflow step it belongs to, so an agent must infer usage from the name and context.

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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