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iPythoning
by iPythoning

get_latest_rss

Fetch RSS entries from chosen feeds over a specified period, with optional summaries. Filter by feed IDs, days, and result limit to get relevant content from sources like Hacker News.

Instructions

获取最新的 RSS 订阅数据(支持多日查询)

RSS 数据与热榜新闻分开存储,按时间流展示,适合获取特定来源的最新内容。

Args: feeds: RSS 源 ID 列表,如 ['hacker-news', '36kr'],不指定则返回所有源 days: 获取最近 N 天的数据,默认 1(仅今天),最大 30 天 limit: 返回条数限制,默认50,最大500 include_summary: 是否包含文章摘要,默认False(节省token)

Returns: JSON格式的 RSS 条目列表

Examples: - get_latest_rss() - get_latest_rss(days=7, feeds=['hacker-news'])

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNo
feedsNo
limitNo
include_summaryNo

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

A4.5/5.0
Behavior4/5

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

No annotations are provided, so the description carries the burden. It discloses storage separation, time-flow display, default/maximum values, and the token-saving effect of include_summary. As a read-only fetch tool, this is adequate, though it does not mention error or authentication behavior.

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 compact and front-loaded, with a clear purpose, structured Args, Returns, and Examples sections. Minor redundancy like 支持多日查询 repeating the days parameter details is acceptable but slightly unnecessary.

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?

All four parameters are documented with defaults and limits, return format is specified as JSON, and examples demonstrate typical calls. The presence of an output schema means detailed return-field documentation is unnecessary, making this complete for a read-only RSS fetching tool.

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%, but the description fully compensates by explaining every parameter: feeds with ID examples, days with range and default, limit with cap, and include_summary with its purpose. This goes far beyond the bare schema.

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 opens with a specific verb and resource: 获取最新的 RSS 订阅数据, and further clarifies that RSS data is stored separately from hot-list news and displayed as a time stream. This makes it easy to distinguish from siblings like get_latest_news and search_rss.

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 use case: retrieving recent content from specific RSS sources, and notes that RSS data is separate from hot-list news. However, it does not explicitly name alternatives such as search_rss or state when not to use this tool, so exclusions are missing.

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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