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pdf_extract

Downloads an arXiv paper PDF and parses its body text to return page count and a preview snippet, enabling quick browsing before deep reading.

Instructions

下载 arXiv 论文 PDF 并解析正文,返回页数与正文预览(论文精读前快速浏览用)。

  • arxiv_id: arXiv 编号,如 "2507.19570v1"

  • max_chars: 预览字符数上限(100-5000,默认 500)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
arxiv_idYes
max_charsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Install Server

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It clearly states the tool downloads a PDF, parses the body, and returns page count and preview, which is meaningful behavioral context. It does not mention failure modes, network dependency, or cleanup, but for a simple read-oriented extractor this is adequate.

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 compact and front-loaded: the main action appears in the first sentence, followed by a short, relevant parameter list. Every sentence earns its place with no redundant filler.

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?

For a simple two-parameter tool with an output schema, the description is nearly complete: it covers purpose, parameters, and the intended usage scenario. The main gap is the lack of explicit guidance on when to prefer sibling tools (e.g., paper_search) and any caveats about inaccessible or malformed PDFs.

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%, and the description fully compensates by explaining both parameters: arxiv_id with an example format and max_chars with its meaning ('preview character limit') plus range and default. This adds semantic value far beyond the bare 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 states a specific verb and resource: downloads an arXiv paper PDF, parses the body text, and returns page count plus a preview. It also frames the use case ('quick browsing before close reading'), which distinguishes it clearly from sibling tools like paper_search.

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 gives a clear context for use: '论文精读前快速浏览用' (for quick browsing before intensive reading). However, it does not explicitly name alternatives or state when not to use this tool, so it stops short of full when/when-not guidance.

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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