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iPythoning
by iPythoning

find_related_news

Find news articles related to a given headline using similarity matching. Optionally filter by date range, adjust similarity threshold, and include URLs in results.

Instructions

查找与指定新闻标题相关的其他新闻(支持当天和历史数据)

Args: reference_title: 参考新闻标题(完整或部分) date_range: 日期范围(可选) - 不指定: 只查询今天的数据 - "today", "yesterday", "last_week", "last_month": 预设值 - {"start": "YYYY-MM-DD", "end": "YYYY-MM-DD"}: 自定义范围 threshold: 相似度阈值,0-1之间,默认0.5(越高匹配越严格) limit: 返回条数限制,默认50 include_url: 是否包含URL链接,默认False(节省token)

Returns: JSON格式的相关新闻列表,按相似度排序

Examples: - find_related_news(reference_title="特斯拉降价") - find_related_news(reference_title="AI突破", date_range="last_week")

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
thresholdNo
date_rangeNo
include_urlNo
reference_titleYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv6.10.0

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations, the description carries the behavioral burden and covers defaults (date_range, limit, include_url), the semantics of threshold, and that results are sorted by similarity. It does not mention failure or edge-case behavior, but the disclosed defaults and return behavior are substantial.

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 organized with clear Args/Returns/Examples sections, uses short bullet-style entries, and includes two practical examples. Every line adds value and the purpose is front-loaded.

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?

For a five-parameter tool with no annotations, the description is complete: all parameters, return format, sorting behavior, and sample calls are provided. Given an output schema also exists, no critical calling information appears missing.

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 every parameter: reference_title, date_range variants, threshold scale and default, limit, and include_url token-saving purpose. This exceeds the structured schema, which only provides types and defaults.

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 names a specific action and resource ('查找与指定新闻标题相关的其他新闻') and clarifies it covers today and historical data. It distinguishes itself from generic search in the sibling list by emphasizing relatedness to a reference title, though it does not explicitly name a sibling alternative.

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?

It gives clear usage context: unspecified date means today, presets and custom ranges are available, and threshold controls strictness. It does not explicitly state when not to use this tool or compare it with search_news, but the related-news framing implies the intended scenario.

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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