Sequencer

create_shot_with_media

Create a shot with an image prompt in one call. Resolves tagged assets (characters, locations) to get descriptions and reference images, applies the prompt formula from edit settings, then either triggers generation immediately (if all reference images are ready) or queues for dependency-driven generation.

Input Schema

TableJSON Schema

Name	Required	Description
`model`	No	Image model ID (uses the edit default or Nano Banana Pro if not specified)
`order`	No	Shot order within the scene (auto-appends to end if not provided)
`editId`	Yes	The edit ID
`prompt`	Yes	Image generation prompt (visual description ONLY). Use @tags for character/location references (e.g. "@John walks through @CityPark"). Never include dialogue, narration, or spoken text here because it may render visibly in the image.
`sceneId`	Yes	The scene this shot belongs to
`dialogue`	No	Visible on-screen character speech for this shot. Stored separately for intentional lip-sync/TTS use. Do not use for off-screen narration or captions.
`duration`	No	Editorial shot duration in seconds. Five seconds is only a compatibility fallback. For planned edits, choose and pass the duration that fits this shot's narration or story beat.
`aspectRatio`	No	Fallback aspect ratio only used if the edit has no aspectRatio. Shots normally inherit the edit aspect ratio.
`videoPrompt`	No	Video/motion prompt describing camera movement and action for video generation. Include speech only when visible on-screen character lip-sync is intentionally required. Never include off-screen narration.
`workspaceId`	Yes	The workspace ID
`taggedAssets`	No	Assets to tag in this shot (characters, locations, props, styles)

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 7, 2026

TDQS

A4/5.0

Behavior4/5

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

With no annotations, the description carries the full behavioral burden and discloses important traits: asset resolution, prompt-formula application, immediate generation when references are ready, and queuing when they are not. It omits permissions, cost implications, or failure behavior, but covers the core conditional execution.

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 compact sentences, front-loaded with the core action and followed by the execution logic. Every clause adds useful information without repetition.

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?

For an 11-parameter creation/generation tool with no output schema and no annotations, the description explains the key workflow and conditional generation path. It could go further by describing return values, permissions, or cost behavior, but it is sufficient for correct invocation based on the rich input schema.

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 parameter documentation is already thorough in the schema. The description adds only high-level context about tagged assets and the prompt formula, not syntax or edge cases beyond the schema.

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?

The description states a specific verb, resource, and scope: creating a shot with an image prompt in a single call. It also explains the internal workflow that distinguishes it from a plain create_shot sibling.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The first sentence and workflow imply when to use the tool, but there is no explicit guidance on when to prefer it over siblings like create_shot or generate_shot_video, nor any stated exclusions.

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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