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regenerate_shot_video

Regenerate an existing shot video for a storyboard after user approval, optionally using a new prompt. Requires a confirmed quote ID.

Instructions

确认后重生某镜视频(可选新 prompt)。⚠️ 批量报价确认流程:先调对应的 quote_* 工具,把返回的 estimated_points 原样告诉用户,用户明确同意后,才用返回的 quote_id 调本工具。不要擅自确认。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptNo可选:覆盖该镜视频 prompt
quote_idYes来自 quote_regenerate_shot_video
storyboard_idYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.57

TDQS

A4.2/5.0
Behavior3/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It does disclose that this is a quote-gated, user-consent-required operation and implies a point cost. However, it does not explicitly state what happens to the existing shot video—whether it gets overwritten or becomes irreversibly replaced—which is important for a mutation tool.

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?

The description is compact and front-loaded: the core purpose appears first, followed by the critical confirmation workflow and a direct prohibition. Every sentence earns its place, and the warning is placed where it is most likely to be respected.

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 a 3-parameter mutation tool with no output schema, the description adequately covers the essential invocation context: required quote confirmation, where quote_id comes from, and the optional prompt. It does not describe the return value or the exact effect on existing video, but the agent has enough information to select and invoke the tool correctly.

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 already describes prompt and quote_id, covering 67% of parameters. The description reinforces the meaning of quote_id by tying it to the quote tool's return value and mentions the optional prompt override. It adds some context but does not compensate much beyond what the schema already provides; storyboard_id receives no additional semantic guidance in the description.

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 action—regenerating a shot's video with an optional new prompt—and clearly separates this execution tool from the related quote_regenerate_shot_video tool by describing the quote-then-confirm flow. The verb and resource are specific, and the scope is unambiguous even without a title.

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?

The description provides an explicit workflow: first call the corresponding quote_* tool, show the returned estimated_points to the user, wait for explicit consent, and only then call this tool with the quote_id. It also includes a strong exclusionary warning ('不要擅自确认'), making when-to-use and when-not-to-use very clear.

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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