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Create a reel

create_reel

Start rendering a vertical short-form reel. Uses one reel credit per variant, reserved at start and released if the render fails. Returns job_id; poll it with get_job.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
aspectNoOutput aspect ratio; defaults to 9:16
scriptNoOptional narration script; generated from the subject when omitted
subjectYesWhat the reel is about (the topic or hook)
languageNoScript language code, e.g. en or tr; defaults to auto
variantsNoRender 1 to 3 variants; each uses one credit
avatar_idNoAvatar presenter id from GET /avatars
voice_nameNoVoice id from GET /voices
caption_styleNoCaption style id
screen_recording_keyNoKey of an uploaded screen recording you own

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations only declare openWorldHint/destructiveHint, so the description carries real weight here and delivers: credit cost per variant, reservation at start, and release on render failure — non-obvious billing behavior an agent should know before calling. It omits auth/permission requirements, which keeps it from a 5.

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 tight sentences, front-loaded with the action, then cost semantics, then the async handoff. Every sentence earns its place with no filler.

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?

With no output schema, the description correctly supplies the return value (job_id) and the polling workflow. For a 9-parameter mutation with billing side effects it is largely complete, though it says nothing about failure/error surfaces beyond credit release.

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 every parameter (aspect, script, subject, language, variants, avatar_id, voice_name, caption_style, screen_recording_key) is already documented in the schema. The description only reinforces the credit-per-variant cost implied by the 'variants' param, adding little beyond the structured fields — baseline 3.

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?

Specific verb+resource: 'Start rendering a vertical short-form reel.' It also names the async follow-up tool (get_job), which distinguishes it from sibling list/schedule/quote tools. An agent knows immediately this kicks off a render job.

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?

Clear context for use (start a render) and explicit routing for the follow-up step ('poll it with get_job'). It does not mention the sibling generation_quote for estimating cost beforehand, nor state when not to call it, so it stops short of full alternative routing.

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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