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renyumeng1

mcp-scholar

by renyumeng1
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python

summarize_papers

Read-onlyIdempotent

Search Google Scholar papers by topic and generate Markdown summaries with optional citation, date, or relevance sorting and year filters.

Instructions

搜索并总结特定主题的论文

Args:
    topic: 研究主题
    count: 返回结果数量，默认为5
    sort_by: 排序方式，可选值:
        - "relevance": 按相关性排序（默认）
        - "citations": 按引用量排序
        - "date": 按发表日期排序（新到旧）
        - "title": 按标题字母顺序排序
    year_start: 开始年份，可选
    year_end: 结束年份，可选

Returns:
    str: 论文总结的Markdown格式文本

Input Schema

NameRequiredDescriptionDefault
countNo
topicYes
sort_byNorelevance
year_endNo
year_startNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.2.2
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "properties": {
+    "result": {
+      "title": "Result",
+      "type": "string"
+    }
+  },
+  "required": [
+    "result"
+  ],
+  "title": "summarize_papersOutput",
+  "type": "object"
+}
  2. First observedv1.0.0

TDQS

B3.4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, openWorldHint, and idempotentHint, so the safety profile is largely covered. The description adds the return format (Markdown summary) and sorting/date-filter behavior, but does not disclose data source, freshness, summary generation method, or rate limits. With annotations covering the basics, a 3 is appropriate.

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 front-loaded with a clear one-sentence purpose, then structured Args and Returns. The sort_by list is verbose but earns its place because the schema lacks descriptions; overall it is efficient.

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?

An output schema exists, and the description also states the return is Markdown summary text. All 5 parameters are documented, including defaults and enum values. The main missing context is sibling differentiation, which is a usage-guideline issue rather than incomplete calling information.

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?

Schema description coverage is 0%, so the description must carry parameter meaning, and it does: it explains topic, count with default 5, sort_by with all four enum meanings and default, and optional year_start/year_end. Minor gaps like topic format (keywords vs phrase) remain, but the compensation is strong.

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 states a specific verb pair ('搜索并总结') and resource ('论文') scoped to a topic, so the agent knows it searches and summarizes papers rather than merely listing them. It does not differentiate itself from siblings like search_papers or scholar_search, which keeps it short of a 5.

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?

There is no explicit guidance on when to use this tool instead of search_papers, scholar_search, adaptive_search, or paper_detail. The purpose implies a use case, but alternatives and exclusions are absent.

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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