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mlexpertio

MCP PDF Reader

by mlexpertio

get_document_list

Retrieve a list of available PDF document filenames from the server to know which files can be processed.

Instructions

Use this tool to get the list of documents.

Returns:
    list[str]: The list of document filenames.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations were provided, so the description carries the full burden of behavioral disclosure. It states the tool returns a list of strings (filenames), but it does not reveal any side effects, potential errors, whether the list is sorted, or any limitations (e.g., pagination, timeout). The output schema is present but the description adds little beyond it.

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 very short (three lines), which is appropriate given the tool has no parameters. It front-loads the purpose in the first line. However, it could omit the redundant 'Returns:' block since the output schema already documents the return type.

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?

For a zero-parameter tool with a simple output, the description is minimally adequate. However, it could mention that the list includes all documents available to the user or provide context on document scope (e.g., workspace, shared drives). The sibling tool 'get_document_text' suggests documents are identifiable by filename, but the description does not clarify how filenames map to identifiers.

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?

There are no parameters, so parameter semantics are irrelevant. The description correctly indicates that the tool takes no input, which is consistent with the schema (0 parameters, 100% coverage). It provides a clear return type that is not redundant with the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states that the tool retrieves a list of documents, using the verb 'get' and the resource 'list of documents'. It distinguishes itself from the sibling tool 'get_document_text' by focusing on listing filenames rather than retrieving document content, though it does not explicitly differentiate.

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 guidance is provided on when to use this tool versus the sibling 'get_document_text'. There is no mention of prerequisites, such as needing a workspace or filter parameters. The description lacks context for appropriate use.

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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