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paper_search

Search arXiv for academic papers by keyword, returning a structured list with title, authors, year, abstract, and link. Filter by category, year, or sort by relevance or date.

Instructions

按关键词在 arXiv 检索学术论文,返回结构化列表(标题/作者/年份/摘要/链接)。

  • query: 检索关键词,如 "model context protocol"

  • max_results: 最多返回条数(1-20,默认 5)

  • year_from: 起始年份(含),如 2023;留空不限

  • category: arXiv 分类,如 cs.AI、cs.SE;留空不限

  • sort_by: 排序方式,relevance(相关度)或 date(最新优先)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
sort_byNorelevance
categoryNo
year_fromNo
max_resultsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Install Server

TDQS

A4.6/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden. It discloses the return structure, sorting behavior, inclusive year filtering, and result count limits. It does not mention potential rate limits, API quirks, or error handling, but for a simple arXiv search this is a minor gap rather than a critical omission.

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 and well-structured: one introductory sentence stating the purpose, followed by a bullet list of parameters with clear explanations and examples. Information is front-loaded, and there is no redundant or verbose content.

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?

All five parameters are documented with constraints, defaults, and examples, and the return format is explicitly summarized. Although an output schema exists, the description still gives a helpful overview. An agent can invoke this tool correctly without needing to infer anything.

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%, so the description must compensate. It does so thoroughly: every parameter is explained in plain language with concrete examples (e.g., query example, category codes, year_from inclusive, max_results range/default). This fully makes up for the absent schema descriptions.

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 a specific verb-resource pair: search academic papers on arXiv by keyword and return a structured list (title/author/year/abstract/link). None of the sibling tools overlap with this functionality, so it is unambiguous and easily distinguishable.

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 does not explicitly state 'when to use' or name alternatives, but the sibling tools are unrelated (ping, echo, pdf_extract, etc.), so there is no real ambiguity. It provides practical usage context by explaining parameters, defaults, and examples, which guides correct invocation effectively.

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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