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read_articles_batch

Fetch full text from up to five article URLs in one batch, with automatic 5-second delays to avoid rate limiting. Returns structured content for comparison and analysis.

Instructions

批量读取多篇文章内容(最多 5 篇,间隔 5 秒)

逐篇请求文章内容,每篇之间自动间隔 5 秒以遵守速率限制。

典型使用流程:

  1. 先用 search_news(include_url=True) 搜索新闻获取多个链接

  2. 再用 read_articles_batch(urls=[...]) 批量读取正文

  3. AI 对多篇文章进行对比分析、综合报告

Args: urls: 文章链接列表(必需),最多处理 5 篇 timeout: 每篇的请求超时时间(秒),默认 30

Returns: JSON格式的批量读取结果,包含每篇的完整内容和状态

Examples: - read_articles_batch(urls=["https://a.com/1", "https://b.com/2"])

Note: - 单次最多读取 5 篇,超出部分会被跳过 - 5 篇约需 25-30 秒(每篇间隔 5 秒) - 单篇失败不影响其他篇的读取

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlsYes
timeoutNo

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 burden of behavioral disclosure. It transparently discloses the 5-second interval between requests to respect rate limits, the maximum of 5 articles with excess skipped, failure isolation (single article failure does not affect others), the default timeout, and the return format. This is a solid transparency level, though it omits potential details like authentication or handling of redirects, which are not critical for a read tool.

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 well-structured with a summary, typical usage flow, args, returns, example, and notes. It is front-loaded with the core summary. However, it repeats constraints (max 5, interval) in multiple sections, which adds slight redundancy. Overall it is organized but could be more concise.

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 batch tool, the description is complete. It covers the use case, a recommended workflow, all parameters, the return format (JSON with content and status), timing expectations (~25-30 seconds for 5 articles), failure behavior, and an example. An output schema exists, but the description provides sufficient detail on results, so nothing critical is missing for an agent to call it correctly.

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. It explains urls as a required list of article links with a maximum of 5, and timeout as the per-request timeout in seconds with a default of 30. It also provides an example usage. All meaningful parameter semantics are covered, exceeding the baseline expectation.

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 clearly states the purpose: batch read multiple article contents (up to 5, with 5-second intervals). The batch aspect distinguishes it from the sibling read_article, though it does not explicitly name the single-article alternative. The name and description make the distinction evident, so a 4 is appropriate for being clear but not fully explicit about sibling differentiation.

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?

The description provides a typical usage flow: first use search_news to get links, then call read_articles_batch with urls, and finally analyze the results. This gives clear context for when to use the tool. However, it does not explicitly state when not to use it (e.g., for a single article, use read_article) or mention alternative tools, so it is not 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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