Skip to main content
Glama

vision_analyze_file

Analyze a publicly accessible document file (PDF or text) to answer your questions. Provide a URL and a question; optionally enable deep thinking. Returns structured JSON with answers and usage.

Instructions

分析一个文档文件(PDF / 文本等)并回答问题。source 仅支持公网可访问的文件 URL; 本地文件请先上传到可访问地址。question 为对文档的提问;thinking=True 开启深度思考。 返回 JSON:{ok, content, thinking, usage} 或 {ok:false, error:{code,message}}。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sourceYes
questionYes
thinkingNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations, the description carries the burden of behavioral disclosure. It honestly reveals the input constraint (public URL only), the effect of thinking parameter, and the exact return JSON structure (both success and error). It does not mention potential rate limits or file size limits, but the provided details are substantial and useful.

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 three concise sentences, front-loaded with the primary purpose. Every sentence adds value: the first states what it does, the second covers constraints, and the third explains parameters and return format. No filler.

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?

Given the tool's moderate complexity (3 parameters, no annotations, no output schema in structured form), the description covers all necessary aspects: input constraints, parameter meanings, return format, and error handling. It is sufficient for an agent 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.

Parameters5/5

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

Schema description coverage is 0%, but the description fully compensates by explaining each parameter: source (file URL, public only), question (question about the document), and thinking (enable deep thinking). This adds all necessary meaning beyond the bare schema definitions.

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 analyzes a document file (PDF/text) and answers questions, with a specific verb and resource. It distinguishes itself from sibling tools (vision_analyze_image, vision_analyze_video) by focusing on documents, making its purpose immediately clear.

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 clear usage context: source must be a publicly accessible URL, and local files need to be uploaded first. It also explains the thinking flag. However, it does not explicitly contrast with sibling tools, leaving the when-to-use decision implied by the file type rather than stated.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/JunHua-ECJTU/deepseek-vision-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server