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kling_generate_storyboard

Create multishot Kling V3 or V3 Omni videos from prompts and images, using automatic or custom shot sequences. Returns a task to poll for completion.

Instructions

Generate V3/V3 Omni automatic or custom multishot video. Poll kling_get_task.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
requestYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.1.24

TDQS

B3.1/5.0
Behavior3/5

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

With no annotations, the description carries the full behavioral burden; it does disclose that generation is asynchronous and must be polled via kling_get_task, which is real value beyond the schema. It omits cost/credit implications, failure/retry behavior, and whether prompt or multi_prompt is required for each shot_type.

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?

Two short sentences, front-loaded with the capability and followed by the required follow-up action; no filler. It is efficient, though the terseness substitutes brevity for needed specifics rather than reflecting a genuinely complete definition.

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

Completeness2/5

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

For a 14-parameter generation tool with a nested shot array, no annotations, and 0% parameter documentation, the description is far too thin; the output schema plus 'poll' covers results retrieval, but the agent is left guessing how to construct custom multishot requests. A one-line note on multi_prompt vs prompt would close the main gap.

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

Parameters2/5

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

Schema description coverage is 0% and there are 14 nested fields, yet the description explains only the model and shot-type dimension ('automatic or custom'). Key parameters such as multi_prompt/Shot.index, duration bounds (3-15), aspect_ratio, start_image_url/end_image_url, callback_url, and generate_audio get no explanation in either the schema or the description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a concrete verb and resource ('Generate ... multishot video') plus the supported models (V3/V3 Omni), which distinguishes it from the plain kling_generate_video siblings. It stops short of naming which sibling to use instead when the user doesn't need multishot.

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?

'Poll kling_get_task' gives a clear post-call workflow step, which is useful routing guidance. However, it never says when this tool is preferable to kling_generate_video, kling_generate_turbo_video, or kling_generate_video_from_image, leaving the alternative selection to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.