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Start video generation

start_video_generation

Generates the video from the storyboard: hook, voice, every scene, then the final render. Takes 10–30 minutes and spends the estimate get_project returns (estimatedVideoCredits). Confirm that with the user and pass it as max_credits. Poll get_video_status.

Input Schema

NameRequiredDescriptionDefault
project_idYesThe project's id.
max_creditsYesThe most this run may cost; it refuses above it.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations only declare non-read-only, non-destructive, closed-world. The description adds real behavioral context beyond them: a 10–30 minute runtime, that it consumes credits, and that it is asynchronous and must be polled via get_video_status. The cost-refusal behavior is partly covered by the schema's max_credits 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?

Three short sentences, front-loaded with what is produced and immediately followed by the time/cost constraint and the required follow-up call. Nothing is padded.

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?

No output schema exists, and the description supplies what an agent needs to invoke it correctly: duration, credit spend, the max_credits sourcing rule, and the polling loop. It is slightly thin on failure behavior and on what to do if the run is interrupted, which matters given resume_video_generation exists as a sibling.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3, but the description adds operational meaning the schema lacks: max_credits should be the estimatedVideoCredits value from get_project and should be confirmed with the user first. It does not explain the consequence of setting it too low beyond the schema's 'refuses above it'.

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 ('Generates the video from the storyboard') and enumerates the pipeline stages (hook, voice, scenes, final render), which separates it from generate_storyboard and generate_script without opening a schema.

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?

Gives concrete workflow guidance: read the estimate from get_project, confirm with the user, pass it as max_credits, then poll get_video_status. It stops short of naming resume_video_generation as the alternative path for an interrupted run, which is the one sibling most likely to be confused with this one.

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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