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LupinLin1

jimeng-web-mcp

by LupinLin1

image_batch

Generate a series of coherent images in one request, using separate prompts per image and a shared base prompt for consistent style. Designed for storyboards, room sets, and product angles.

Instructions

系列图片生成 - 用于生成高相关性的连续图片(如:房间系列、故事分镜、绘本画面、产品多角度)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
asyncNo是否异步模式,默认true(异步)
modelNo模型名称,支持: jimeng-4.5, jimeng-4.1, jimeng-4.0 (默认)
promptsYes每张图片的完整描述数组(1-15个)。⚠️重要:每个描述应该是一小段话(不是单个词),重点描述该图与其他图的差异部分。示例:["现代客厅,灰色沙发靠窗,阳光洒入", "温馨卧室,米色床品,木质床头柜"]
filePathNo可选参考图路径(影响整体风格,最多4张)
basePromptNo整体通用描述,会添加在最终prompt最前面。用于描述:产品基础信息(材质、颜色)、房子整体风格(三室两厅现代简约)、故事背景设定(赛博朋克世界观)等通用信息。示例:"三室两厅现代简约风格,木地板,暖色调照明"
resolutionNo分辨率选择,2k或4k,默认2k2k
aspectRatioNo宽高比: auto/1:1/16:9/9:16/3:4/4:3/3:2/2:3/21:9auto
negative_promptNo负向提示词
sample_strengthNo参考图影响强度0-1,默认0.5
reference_strengthNo每张参考图的独立强度数组
Behavior3/5

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

With no annotations, the description must bear the burden of behavioral disclosure. It mentions 'highly relevant' but does not reveal asynchronous behavior, return format, or any side effects. The schema already documents parameters, so the description adds only a quality trait.

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 a single, concise sentence with illustrative examples, placing the core purpose upfront. It is efficient but perhaps too brief to fully convey operational expectations.

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?

The tool has 10 parameters and no output schema, yet the description never clarifies what the tool returns, how to handle async results, or any constraints on batch generation. This leaves an agent without critical operational context for a complex generation task.

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?

Schema coverage is 100% with descriptions for all parameters, so the baseline is 3. The description does not add any parameter-specific meaning beyond what the schema provides.

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 clearly states the tool generates a series of highly relevant continuous images, with concrete examples like room series, storyboards, and product angles. This distinguishes it from the sibling 'image' tool, which likely handles single images.

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 provides specific use cases (room series, storyboards, picture books, product multi-angle) that indicate when this tool is appropriate. However, it does not explicitly contrast with alternatives or state when not to use it.

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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