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mlexpertio

MCP PDF Reader

by mlexpertio

get_document_text

Extract the text of a PDF document by providing its filename. Returns the content in Markdown format for further use.

Instructions

Use this tool to get the content of a document given its filename.

Args:
    filename (str): The filename of the document to get.

Returns:
    str: The content of the document in Markdown format.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filenameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

With no annotations, the description carries full burden for behavioral transparency. It reveals that the return format is Markdown, which is useful, but omits any details about side effects, authentication, rate limits, or error behavior (e.g., missing file). The tool is simple, but more context would be ideal.

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 extremely concise, comprising only two sentences plus a structured Args/Returns block. It is front-loaded with the purpose and wastes no words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity, the description covers the basic usage. However, it lacks details about error cases (e.g., file not found) and does not explain how the output relates to the sibling tool. An output schema exists but is not shared; the description mentions returning Markdown, which is helpful but not fully comprehensive.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate. However, it merely restates the parameter name and type ('filename (str)') without adding constraints like allowed paths, case sensitivity, or file extensions. This adds little value beyond the schema.

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 action ('get the content of a document') and the resource ('given its filename'). It directly distinguishes from the sibling tool 'get_document_list' by focusing on content retrieval rather than listing.

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

Usage Guidelines3/5

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

The description indicates when to use the tool (when you need document content) but does not explicitly exclude alternatives or provide when-not-to-use guidance. The existence of 'get_document_list' is implied, but no direct comparison or exclusion is stated.

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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