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TrendRadar MCP

TrendRadar MCP

Official
by snow-sprite
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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generate_summary_report

Generate daily or weekly summary reports of trending news to quickly identify hot topics. Optionally specify a custom date range for the analysis.

Instructions

每日/每周摘要生成器 - 自动生成热点摘要报告

Args: report_type: 报告类型（daily/weekly） date_range: 【对象类型】 自定义日期范围（可选） - 格式: {"start": "YYYY-MM-DD", "end": "YYYY-MM-DD"} - 示例: {"start": "2025-01-01", "end": "2025-01-07"} - 重要: 必须是对象格式，不能传递整数

Returns: JSON格式的摘要报告，包含Markdown格式内容

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "generate_summary_report"
  }
}

Input Schema

NameRequiredDescriptionDefault
date_rangeNo
report_typeNodaily

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv6.10.0

TDQS

A3.7/5.0
Behavior3/5

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

With no annotations, the description carries the behavioral burden. It adds useful details: the output is JSON containing Markdown, and date_range must be an object rather than an integer. It does not disclose side effects, permissions, or any processing limits.

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: a one-line purpose, then Args with clear formatting, then Returns. Every line adds value, and the object-format warning is high-signal.

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 tool with only two optional parameters and an output schema, it covers parameter formats and the return shape well. The main omissions are when-to-use guidance and side-effect/permission hints, which would make it fully self-contained.

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% and the schema is under-specified: report_type is a plain string and date_range is a loose anyOf. The description compensates strongly by defining report_type values as daily/weekly and giving the exact date_range object format, an example, and a warning against passing integers.

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?

States a specific verb and resource: it generates daily/weekly hotspot summary reports. The daily/weekly scope is concrete, though it does not explicitly distinguish itself from sibling analysis tools like analyze_topic_trend or aggregate_news.

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?

No guidance is given for when to use this tool instead of siblings such as analyze_data_insights or aggregate_news. It only lists parameter values, not use conditions, prerequisites, or exclusions.

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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