StreamClipping AI

Import a VOD

import_vod

Creates a project from a Twitch, YouTube, Kick or CHZZK VOD (stream replay) link. Importing does not start clipping: start_clipping is the next step once the project reaches AWAITING_CROP.

Input Schema

TableJSON Schema

Name	Required	Description
`url`	Yes	Link of the VOD to import. Twitch (twitch.tv), YouTube (youtube.com, youtu.be), Kick (kick.com) or CHZZK (chzzk.naver.com/video/…). The stream must be over and the replay public.
`title`	No	Project title. Defaults to a title derived from the date.
`creator`	No	Agency creator to scope to, by name or id (see the creator profiles of the account). 'default' targets the default profile, the one without a named creator. Omit to cover all creators of the organization.
`language`	No	Spoken language as a 2-letter ISO code (fr, en, es…). Omit to let automatic detection decide.

Output Schema

TableJSON Schema

Name	Required	Description
`hint`	Yes
`status`	Yes
`projectId`	Yes
`nextAction`	Yes
`waitSeconds`	Yes
`alreadyImporting`	Yes	True if this source was already being imported: no duplicate was created.

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedOct 16, 2026

addedInput schema / properties / creator

Added value: +{
+  "description": "Agency creator to scope to, by name or id (see the creator profiles of the account). 'default' targets the default profile, the one without a named creator. Omit to cover all creators of the organization.",
+  "maxLength": 100,
+  "minLength": 1,
+  "type": "string"
+}

First observedOct 9, 2026

TDQS

A4.2/5.0

Behavior4/5

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

Annotations already declare the safety profile (readOnlyHint=false, destructiveHint=false, idempotentHint=false), so the bar is lower. The description adds real behavioral context beyond the annotations: it clarifies that import is a non-clipping state transition and exposes the AWAITING_CROP milestone. It does not cover auth requirements or behavior on private/ongoing streams, but the schema's url description handles the latter.

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?

Two sentences, zero waste. The core action is front-loaded and the workflow constraint follows immediately; 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?

With an output schema present, return values need not be explained, and the annotations plus 100% schema coverage carry safety and parameter detail. The description supplies the one thing structured fields don't: where this sits in the import→start_clipping pipeline. Slight gap on failure modes keeps it from a 5.

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 all four parameters (url, title, creator, language) are already fully documented in the schema. The description adds no syntax or format detail beyond it, so the baseline of 3 is appropriate.

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: 'Creates a project from a ... VOD (stream replay) link,' and enumerates the supported platforms (Twitch, YouTube, Kick, CHZZK). It also distinguishes itself from the workflow sibling start_clipping, so an agent can place it without opening the 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 clear context and the expected next step: importing is not clipping, and start_clipping follows once the project reaches AWAITING_CROP. It stops short of naming when NOT to use it (e.g., re-importing an existing VOD via list_channel_vods), but the workflow routing is explicit.

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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