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Glama

get_storyboard_table_spec

Produce import-ready storyboards by retrieving the accepted table spec with template, examples, and whitelists for shot types and movements.

Instructions

取本平台认可的分镜表格式契约:markdown 范本全文 + external_prompt(可整段转发给任意外部 AI 的任务提示词) + skeleton(〈…〉占位骨架) + filled_example(成品对照) + checklist + shot_types(景别白名单) + movements(运镜白名单与认得的中文写法)。免费·静态·不扣费。★什么时候用:客户手上是成品分镜表(逐镜秒数/景别/运镜)、或想让外部 AI/自己的工具把镜头设计整理成我们认的格式时——在 import_storyboard_table 之前先调它。★契约要点:一镜一行 [镜 001 | 4s | 特写 | 固定](加粗式/全角竖线/繁体也认);景别与运镜只认白名单里的词(写别的会留空);声明之后的正文=画面叙述(至少一行,否则出不了图)+ 角色名:台词 + [SFX:]/[BGM:]/[VFX:] 标注;整屏文字用 [字卡 9s] 行一 | 行二;STYLE/NEG 全片风格块不写进表(写进项目设定);## 非场景标题 会结束当前镜。转发给外部 AI 时务必把 filled_example 一起给:格式正确率靠可模仿的完整样例。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
drama_titleNo仅用于范本抬头,不影响契约本身
episode_numberNo仅用于范本抬头

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.57

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations, the description carries the full burden. It discloses that the call is free, static, and non-charging, lists the returned content, and documents important behavioral contract rules such as non-whitelist terms being left blank, requiring at least one description line to generate images, and non-scene headings ending a shot. It doesn't cover auth/error behavior, but that is low-risk for a static read-oriented spec endpoint.

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?

The description is long but well-structured with ★ markers, front-loading the returned artifact list, then the usage context, then the formatting contract. Each block earns its place, though there is slight redundancy in the repeated external-AI forwarding guidance, which keeps it from a 5.

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?

There is no output schema, so the description compensates by naming every returned component and giving the key syntax and whitelist rules an agent needs. It also covers when to call it, the static/free behavior, and the instruction to include filled_example when forwarding to external AI. For a zero-required-parameter spec tool, this is complete.

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 input schema covers 100% of the two optional parameters (drama_title and episode_number), so the baseline of 3 applies. The description adds no parameter-specific detail, but the schema already explains both only affect the template header, so no information is missing.

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 uses a specific verb ('取') and a specific resource: this platform's recognized storyboard-table format contract, and enumerates its components (markdown template, external_prompt, skeleton, filled_example, checklist, whitelists). It also distinguishes the tool from siblings by explicitly saying it should be called before import_storyboard_table.

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

Usage Guidelines4/5

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

The description has an explicit '★什么时候用' section: call it when a client has a finished storyboard table, when external AI/tools need to normalize shot design into the platform format, and before running import_storyboard_table. It gives clear context but does not state when not to use it or name alternative spec tools such as get_script_format_spec.

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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