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Clip

render.clip.create

Render a short captioned video clip (1-60 seconds) over a public image, video or solid colour. Always a durable job; ask for a task or poll render.job.get. Counts every output second, rounded up, when it succeeds: render.video_second_fhd for vertical and landscape (1080p), render.video_second_hd for square and 720p.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sizeNovertical
colourNoBackground colour when no background is given.
captionsNo
durationNoSeconds.
font_sizeNo
backgroundNoPublic http(s) image or video to play behind the captions. Omit for a solid colour.
external_idNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindYes
errorNo
usageYesWhat the job counts against the organisation's usage: its billing meter, the quantity the product admitted, and the quantity committed once it succeeds, in the meter's units.
cachedYes
job_idYes
resultYes
statusYes
call_idNo
productYes
created_atYes
request_idYes
connection_idNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior5/5

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

Annotations declare it is a non-read-only, open-world, non-idempotent mutation, but the description adds genuinely new behavior: it is always asynchronous, must be awaited via render.job.get, and carries a per-output-second billing model (rounded up) with specific pricing keys tied to output size. This is exactly the kind of cost and lifecycle disclosure annotations cannot convey.

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?

Three front-loaded sentences with no filler; the core action and constraints come first and the async/pricing details follow. The final pricing sentence is dense with two SKU keys and four enums but remains readable and earns its space.

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 annotations covering the safety profile and an output schema covering the return shape, the description is left to explain lifecycle and cost, which it does. Minor gaps remain around caption/font behavior, but nothing critical to invoking the tool correctly is missing.

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 43% across 7 parameters, so the description must compensate. It clarifies that background accepts image/video and that omitting it yields solid colour, and it maps the size enum to pricing tiers (vertical/landscape to FHD, square/720p to HD), but leaves colour, font_size, external_id, and the captions structure unexplained.

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 (render), resource (short captioned video clip), duration bound (1-60 seconds), and overlay medium (public image, video or solid colour). This clearly distinguishes it from sibling render.* tools like render.pdf.create, render.screenshot.create, and render.qr.create.

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 explicit async workflow guidance: it's always a durable job and the agent should request a task or poll render.job.get. It does not, however, contrast this with alternative creation paths such as render.batch.create or render.template.render, so sibling selection is left partly to inference.

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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