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search_news

Search aggregated hot topics and RSS feeds across platforms using keyword, fuzzy, or entity modes. Filter by date, platform, and relevance to retrieve JSON news results.

Instructions

统一搜索接口,支持多种搜索模式,可同时搜索热榜和RSS

建议:使用自然语言日期时,先调用 resolve_date_range 获取精确日期范围。

Args: query: 搜索关键词或内容片段 search_mode: 搜索模式 - "keyword": 精确关键词匹配(默认) - "fuzzy": 模糊内容匹配 - "entity": 实体名称搜索(人物/地点/机构) date_range: 日期范围,格式 {"start": "YYYY-MM-DD", "end": "YYYY-MM-DD"},默认今天 platforms: 平台ID列表,如 ['zhihu', 'weibo'],不指定则使用所有平台 limit: 热榜返回条数限制,默认50 sort_by: 排序方式 - "relevance"(相关度)/ "weight"(权重)/ "date"(日期) threshold: 相似度阈值(仅fuzzy模式),0-1,默认0.6 include_url: 是否包含URL链接,默认False include_rss: 是否同时搜索RSS数据,默认False rss_limit: RSS返回条数限制,默认20

Returns: JSON格式的搜索结果,包含热榜新闻列表和可选的RSS结果

Examples: - search_news(query="AI") - search_news(query="AI", include_rss=True) - search_news(query="特斯拉", date_range={"start": "2025-01-01", "end": "2025-01-07"})

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
queryYes
sort_byNorelevance
platformsNo
rss_limitNo
thresholdNo
date_rangeNo
include_rssNo
include_urlNo
search_modeNokeyword

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations provided, the description carries the full disclosure burden and handles it well: it explains search modes, default date behavior, threshold semantics, include_rss behavior, and output type. It doesn't mention rate limits or error conditions, but for a read-style search tool, the key behavioral traits are covered.

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 long because 10 parameters need documentation, but every section earns its place: purpose statement, helper guidance, Args breakdown, Returns line, and illustrative examples. The structure is front-loaded and easily scannable.

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 10-parameter multi-mode search tool, the description is thorough: it covers modes, defaults, return format, platform examples, and natural-language-date handling. It stops just short of explaining when to prefer distinct siblings like search_rss or get_latest_news, and does not list available platform IDs.

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 fully document parameters, and it does. Every parameter has a meaning, format, default, and relevant examples, including mode-specific behaviors like threshold only applying to fuzzy mode.

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 names a concrete resource ('统一搜索接口' for news), specifies search modes, and states it can cover both hot-list and RSS data. This makes it clearly distinguishable from siblings like get_latest_news, search_rss, and get_news_by_date.

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 a clear, actionable recommendation to call resolve_date_range when using natural language dates, and the '统一搜索接口' framing signals it as the general search entry point. It does not explicitly enumerate alternatives or exclusion conditions, so it falls short of a 5.

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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