analyze_topic_trend

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 parameters and return format but does not disclose potential side effects, required permissions, rate limits, or data freshness. It adequately describes behavior for a read-analysis tool but lacks depth.

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 (overview, suggestion, Args, Returns, Examples). It is informative without being overly verbose. A small amount of redundancy exists, but overall it is concise.

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 8 parameters, required 1, and existence of output schema, the description covers all parameters and provides examples. The return value is mentioned as JSON but not detailed; however, output schema exists to complement. The tool is well-documented for an agent to use correctly.

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%, but the description provides detailed explanations for all 8 parameters, including default values, formats, and mode-specific details (e.g., spike_threshold for viral, lookahead_hours for predict). This adds significant meaning beyond the schema.

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 integrating multiple analysis modes. The verb 'analyze' and resource 'topic trend' are specific. While it distinguishes subtypes within the tool, it does not explicitly differentiate from sibling tools like analyze_sentiment or get_trending_topics, but the purpose is clear.

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 advises using resolve_date_range for natural language dates, which is helpful. It provides examples but does not explicitly state when not to use this tool or name alternatives. The guidance is present but not exhaustive.

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