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mlintangmz2765

Scholar MCP Server

get_full_text_visual_tool

Downloads a PDF and converts pages to images for AI analysis of graphs, tables, and layouts. Use when text extraction misses formatting.

Instructions

Multimodal Vision Tool. Downloads a PDF and renders the specified number of pages identically into images for the AI to 'look at'. Use this if the user asks you to analyze a graph, table, format, or layout in the paper. If the text extractor doesn't capture formatting, you can use this tool to 'see' the actual PDF! Returns a sequence of texts and images (multimodal format natively parsed). Warning: High token/vision capacity used per page. Default 3 pages.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYes
max_pagesNo
Behavior4/5

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

Without annotations, the description effectively discloses behavior: downloads PDF, renders pages to images, returns multimodal content, and warns about high token/vision usage. It does not mention any destructive actions, which is appropriate. Could be improved by noting that it doesn't modify the PDF.

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 opening statement, specific use cases, and a warning. Every sentence is necessary and front-loaded. No redundancy.

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?

Given no output schema, the description covers purpose, usage, behavior, parameter defaults, and return format ('sequence of texts and images'). It is complete enough for an agent to use effectively, though exact output structure could be clarified.

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 0%, so description must compensate. It mentions max_pages defaults to 3 and implies its purpose, but url is not described. This adds some value but does not fully clarify both parameters. Baseline 3 is appropriate.

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 is a multimodal vision tool for analyzing visual elements like graphs and tables, contrasting with text-only tools. It specifies the action (download PDF, render pages into images) and distinguishes from siblings by emphasizing visual analysis.

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

Usage Guidelines5/5

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

Explicitly says 'Use this if the user asks you to analyze a graph, table, format, or layout' and 'If the text extractor doesn't capture formatting, you can use this tool'. This provides clear when-to-use and when-not-to-use guidance, referencing alternatives implicitly. Also warns about high token usage.

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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