search_related_news_history

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

With no annotations provided, the description carries full responsibility for behavioral disclosure. It transparently explains the relevance threshold formula (70% keyword overlap + 30% text similarity), the fact that actual results may be fewer than the limit, the token-saving effect of include_url, and the return format (JSON with relevance scores and time distribution). It also describes the important data display strategy (show all by default, summarize only when explicitly requested). This is substantial behavioral context beyond a simple search operation.

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 clear Args and Returns sections, and a bolded '重要' block for the display strategy. Every sentence adds meaningful information: parameter details, return format, and behavioral notes. The length is justified given the number of parameters and the need to explain the mixed-similarity calculation and display rules. No fluff or repetition.

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 (5 parameters, custom threshold calculation, display strategy) and rich input schema, the description is remarkably complete. It covers the tool's purpose, all parameter semantics, output format, and a non-obvious display behavior. Even though an output schema exists, the description still describes the return content (relevance score and time distribution) which adds value. No significant aspects are missing.

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 input schema has 0% description coverage, meaning no per-parameter descriptions are provided in the schema. The tool description fully compensates by explaining every parameter in detail: reference_text, time_preset with all options and meanings, threshold with its calculation formula and effect on results, limit with its maximum and note that fewer may be returned, and include_url with its purpose. This is exemplary parameter documentation.

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 the tool's function: searching historical news based on a seed news text ('基于种子新闻，在历史数据中搜索相关新闻'). This is a specific verb+resource combination that accurately conveys the tool's purpose. However, it does not explicitly differentiate from sibling tools like search_news or find_similar_news, so it loses a point for lacking sibling distinction.

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 no guidance on when to use this tool versus alternatives. It explains parameter usage and the default display strategy, but does not mention when one would choose this over search_news, find_similar_news, or other siblings. There is no explicit when-to-use or exclusions, so it falls short of even 'clear context, no exclusions'.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.