analyze_topic_trend

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 discloses key behaviors: the need to call resolve_date_range for natural language dates, the default date range of 7 days, the constraint that granularity only supports 'day' due to data aggregation, and mode-specific defaults. It does not explicitly state that the tool is read-only, but this is implied by the analysis context. Overall, it adds significant behavioral context beyond the schema.

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 headings, lists, and examples. It is somewhat long but every section serves a purpose: the 'Important' notice for date range, the detailed Args list, Returns, and Examples. The examples repeat some information but demonstrate the two-step workflow, which is valuable for an 8-parameter tool with multiple 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?

Given the tool's complexity (8 parameters, 4 modes, prerequisite tool call), the description is quite complete. It covers all parameter semantics, defaults, modes, and provides a workflow example. It does not discuss error handling or edge cases (e.g., missing data), but an output schema exists to define return values, reducing the need for that in the description. Overall, it provides sufficient context for correct tool selection and invocation.

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 description coverage is 0%, so the description must fully compensate. It explains every parameter, its purpose, allowed values, defaults, and which analysis modes it applies to. For example, analysis_type enum values are defined, date_range format and acquisition method are provided, and mode-specific parameters like threshold and lookahead_hours are clarified. 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 it is a unified topic trend analysis tool with multiple analysis modes (trend, lifecycle, viral, predict). It is specific about the resource ('topic trend') and the action ('analyze'), and the modes distinguish it from sibling tools like analyze_sentiment or analyze_data_insights.

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 usage context, including when to call resolve_date_range first and which parameters apply to which mode. It includes two examples showing a recommended calling flow. However, it does not explicitly mention when not to use this tool or name alternative tools for other analysis types, so it lacks explicit exclusions.

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