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dopawei

academic-mcp

by dopawei

search_wos

Perform advanced searches in Web of Science using field tag syntax (e.g., TS=, AU=, PY=) to find academic papers by topic, author, year, and more. Sort results by relevance, date, or citations.

Instructions

在 Web of Science 中进行高级检索。

使用 WoS 字段标签语法,例如: TS=(machine learning AND finance) AU=(Zhang Wei) AND PY=(2020-2025) TI=(neural network) AND SO=(Nature)

常用字段标签: TS=主题, TI=标题, AU=作者, SO=期刊, DO=DOI, PY=年份, AB=摘要, AK=作者关键词, OG=机构, FU=基金

Args: query: WoS 高级检索查询语句 sort_by: 排序 (relevance/date_newest/date_oldest/cited/usage) page_count: 页数 (1-5,每页约10-50条)

Returns: JSON 格式的搜索结果列表

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
sort_byNorelevance
page_countNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

No annotations are provided, so the description must bear full burden. It discloses that the tool returns JSON-formatted search results and requires a query string, and it shows sorting and pagination options. It does not mention authentication dependencies (login_wos exists) or rate limits, but the core behavior is well described.

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 efficiently structured with a concise overview, followed by field tag syntax explanations, examples, and parameter details. Every sentence adds value, there is no redundancy, and it is well organized for quick scanning.

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?

Given the complexity of the tool (advanced search with field tags) and the presence of an output schema (context signals indicate true), the description adequately covers the query syntax, sorting, and pagination. It does not require additional return value descriptions since the output schema exists. No major gaps are evident.

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 coverage is 0%, meaning the schema only provides type/default info and no descriptions. The description fully compensates by explaining each parameter: query syntax with field tags, sort_by options (relevance, date_newest, etc.), and page_count range (1-5). This adds significant meaning 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 clearly states the tool performs advanced search in Web of Science, provides example query syntax using WoS field tags, and explicitly lists common field tags. This distinguishes it from sibling tools like search_cnki or search_deepxiv, which target different databases.

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 includes detailed syntax and field tag examples, implying usage for WoS advanced search. However, it does not explicitly compare to sibling tools like search_literature or explain when to prefer this tool over them, leaving the agent to infer context.

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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