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Generate storyboard

generate_storyboard
Destructive

Plans the scenes from the script, actor and product photos. Runs in the background for 1–3 minutes: poll get_project until storyboard.scenes > 0, then review the scenes with the user. Needs a paid plan. Regenerating replaces the scenes. video_quality picks the models the video is filmed with: "standard" (default — Grok Imagine and MiniMax H3, affordable) or "premium" (Seedance 2.5 for every scene, most realistic, about 28 credits per second of video; English only for now). Ask the user which they want before the first storyboard.

Input Schema

NameRequiredDescriptionDefault
project_idYesThe project's id.
video_qualityNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A5/5.0
Behavior5/5

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

Goes well beyond annotations: discloses the 1–3 minute background execution, the polling-based completion check, the paid-plan requirement, and that regenerating replaces existing scenes (consistent with destructiveHint=true). It also quantifies cost (~28 credits/sec) and the English-only limitation of premium.

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?

Dense but every sentence earns its place, and it is front-loaded with the core action before the operational details. No filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description still explains how to detect completion and what the result contains (storyboard.scenes), plus the prerequisite and destructive behavior. An agent has everything needed to invoke and follow up correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is only 50%, but the description fully compensates: project_id is implicit in 'the script, actor and product photos', and video_quality is explained in depth (standard vs premium, the models behind each, cost, and premium's English-only restriction) — meaningful semantics the bare enum does not convey.

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 ('Plans the scenes from the script, actor and product photos') and clearly distinguishes itself from siblings like generate_script and start_video_generation. An agent knows exactly what artifact this produces.

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

Usage Guidelines5/5

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

Explicitly states when to call it, the prerequisite (paid plan), the follow-up workflow (poll get_project until storyboard.scenes > 0, then review with the user), and the instruction to ask the user about video_quality before the first storyboard. Nothing is left 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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