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Generate shot clip

generate_shot_clip

Generate a video clip for a single shot (episode_shots row). Spends credits. Returns a job id — poll it with get_job.

Input Schema

NameRequiredDescriptionDefault
modelNoVideo model override. Defaults to the project's video model.
shot_idYesShot id.
idempotency_keyYesStable key identifying this generation request. Reuse the SAME key when retrying the same request — the original job is returned and no second charge is made. Use a NEW key when you deliberately want another generation.
short_shot_numberNoTarget a specific short shot.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / model / description
      Previous value: -"Video model override."New value: +"Video model override. Defaults to the project's video model."
  2. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations only cover readOnlyHint=false and destructiveHint=false; the description adds the two behaviorally important facts the annotations omit: the call consumes credits and is asynchronous, requiring polling via get_job. It does not cover failure behavior (e.g. insufficient credits, what happens on a job that never completes), keeping it below 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 short sentences in a deliberate order: what it does, what it costs, what you get and what to do next. Zero filler, and the key operational facts are front-loaded.

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 fills that gap by naming the return value (job id) and the polling tool, and it flags the credit cost. It is slightly thin on prerequisites — whether continuity references or background images must exist before generating — but nothing required to invoke the tool 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 100%, so the schema already documents model override, shot_id, and the idempotency-key retry semantics in detail. The description only reinforces that shot_id refers to an episode_shots row and adds no syntax or format guidance beyond that, which is the expected baseline when the schema does the work.

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+resource ('Generate a video clip') and narrows scope to 'a single shot (episode_shots row)', which distinguishes it from siblings like generate_shot_background_image or generate_character_image that operate on other asset types. An agent can identify the target entity 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?

'Spends credits. Returns a job id — poll it with get_job' tells the agent the cost implication and the required follow-up call, which is real routing guidance to a sibling tool. It stops short of stating when NOT to use this versus the other generate_* tools or any prerequisites (e.g. continuity references attached).

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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