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kling_goods_studio

Generate a product studio video from a reference image and goods title. Polls task status automatically.

Instructions

Generate product studio video from ref_image and goods_title contents. 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
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden. It discloses the async polling pattern implicitly via 'Poll kling_get_task' (consistent with async defaulting to true in the schema), but says nothing about permissions/auth, cost, watermarking, callback_url behavior, or how long generation takes.

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 core action and the required inputs, with no filler. It is arguably too terse for the schema complexity, but nothing in it is wasted.

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 tool with a deeply nested request schema, 0% schema description coverage, and a 16-value content enum, this description is thin. The existence of an output schema removes the need to explain return values, but the required-content composition and settings are not covered well enough for reliable invocation.

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?

The schema has 0% description coverage across a large nested Content enum, so the description must compensate. It does add genuinely useful information by naming ref_image and goods_title as the content types this tool expects, which the schema never marks as required. Still, the other 14 content types, settings, and duration/aspect_ratio choices are left unexplained.

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 specific verb and resource ('Generate product studio video') and narrows it by naming the two required content types, ref_image and goods_title. That distinguishes it reasonably well from sibling product tools like kling_apparel_video and kling_virtual_try_on, though it doesn't explicitly say how it differs.

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 second sentence, 'Poll kling_get_task,' is a useful next-step/routing hint that tells the agent what to do after invocation. However, there is no guidance on when to pick this over kling_video_commerce, kling_apparel_video, or kling_generate_video, nor any stated prerequisites.

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