get_news_by_date

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 explains parameter defaults (e.g., date_range default 'today', limit default 50, include_url default False to save tokens), return format (JSON news list with title, platform, rank), and supported date input formats. It does not disclose potential errors or rate limits, but covers the key behavioral aspects well.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with a purpose statement followed by a clear Args section. Each parameter is explained concisely without redundancy. While not as terse as a two-sentence description, the length is justified by the complexity of the date_range formats and defaults. It is front-loaded with the purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (multiple date formats, platform filtering, limit constraints) and the lack of annotations, the description is remarkably complete. It covers behavior, parameters, defaults, and return format, making it self-sufficient for an agent to select and invoke the tool correctly. The existence of an output schema further reduces the need to describe return details beyond what's already provided.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema provides no descriptions (0% coverage), so the description must fully compensate. It does so admirably by detailing each parameter's supported formats, defaults, and semantics (e.g., date_range accepts range objects, natural language, single-day strings; platforms is a list of IDs; limit supports a max of 1000; include_url controls URL inclusion to save tokens). This exceeds the schema's bare type information.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it retrieves news data for a specified date for historical analysis and comparison. This distinguishes it from siblings like get_latest_news and get_trending_topics by explicitly scoping to date-specific data, making the purpose unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context ('用于历史数据分析和对比' — for historical data analysis and comparison), implying when to use this tool over date-agnostic alternatives. However, it does not explicitly name alternatives or provide exclusions, 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.