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chyinan

MCP Word Commander

by chyinan

read_images

Read images from Word documents and return them for direct AI viewing, supporting optional index selection and table inclusion.

Instructions

读取 Word 文档中的图片,直接返回给 AI 查看。

Args: file_path: 文档路径 image_index: 指定读取第几张图片 (0-based),不指定则读取所有图片 include_tables: 是否包含表格中的图片 (默认True)

Returns: Image 对象列表,AI 可以直接"看到"这些图片。 如果发生错误,返回错误信息字符串。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
file_pathYes
image_indexNo
include_tablesNo
Behavior3/5

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

With no annotations, the description should disclose behavioral traits. It states the return type (Image objects or error string) and mentions parameters like include_tables, but lacks details on side effects, performance, or what the Image object contains. Adequate but not comprehensive.

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 concise with a clear Args/Returns structure. Every sentence adds value, no redundancy, and the main purpose is front-loaded.

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?

The description covers main functionality, parameter details, return type, and error handling. It explains default behavior for image_index and include_tables. Some information about the Image object format is missing, but acceptable without output schema.

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

Parameters4/5

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

The description explains all three parameters with clear semantics: file_path as document path, image_index as 0-based optional index, include_tables with default True. Since schema had 0% description coverage, this fully compensates.

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 reads images from Word documents and returns them directly for AI viewing. The verb 'read' and resource 'images' are specific, and it distinguishes from siblings like get_images_info (metadata) and read_tables (tabular data).

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

Usage Guidelines2/5

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

No explicit guidance on when to use this tool versus alternatives like get_images_info or read_document_structure. The description does not provide context for when to choose this over siblings or any exclusion criteria.

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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