compare_periods

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

No annotations are provided, so the description carries the full burden. It explains the return structure (JSON with periods, compare_type, and result) and details the three compare_type modes with their outputs. It does not explicitly state that the operation is read-only or describe error cases, but the analytical purpose implies no side effects and the return section adds meaningful behavioral context.

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 sections for purpose, usage scenarios, parameters, returns, and examples. It is front-loaded with the main purpose, and every section serves a clear function. Despite its length, it is appropriately sized for a tool with six parameters and three compare modes.

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?

The tool has 6 parameters and an output schema, yet the description still explains the return structure and provides three examples covering different compare_type values. It covers all essential aspects for correct invocation, including period formatting options and optional filters, making it complete for the tool's complexity.

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?

Schema has zero descriptions, but the description thoroughly documents all six parameters: period1/period2 accept either preset strings or date objects with start/end, compare_type has three documented values with a default of 'overview', platforms is shown as an example list, and top_n has a default of 10. This fully compensates for the schema's lack of detail.

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 '时期对比分析' and lists specific comparison dimensions (热点话题、平台活跃度、新闻数量). It distinguishes itself from sibling tools like analyze_topic_trend by explicitly focusing on comparing two discrete periods, and from get_news_by_date by focusing on multi-period comparison.

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 '使用场景' section provides concrete examples (本周vs上周, 某个话题两个时期, 各平台周期变化) and the compare_type parameter documents when each mode is appropriate (overview, topic_shift, platform_activity). It lacks explicit 'when not to use' alternatives, but the context is clear enough for correct selection.

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