search_keyword_trends

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

No annotations are provided, so the description carries full burden. It explains the output (frequency by year, sector, top companies) but does not disclose authentication needs, rate limits, data recency, or whether it is read-only. While not misleading, more behavioral context would improve transparency.

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 three sentences, front-loaded with the core action and results. Every sentence adds value: purpose, output format, analogy, and usage examples. No redundant information.

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 is simple with one parameter and no output schema. The description explains the return structure (frequency by year, sector, top companies) adequately. It does not mention limits or error conditions, but for a search tool, this is sufficient.

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 covers the single parameter 'keyword' with examples. The description adds context by specifying the scope (64,000+ NZX announcements) and providing usage examples, which adds value beyond the schema's description.

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 purpose: searching keywords across NZX announcements and returning frequency trends by year, sector, and top companies. It uses a Google Trends analogy and provides example queries, effectively distinguishing it from sibling tools like search_announcements.

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 gives explicit usage examples ('when did companies start talking about AI?', 'which sector mentions climate risk most?'), guiding when to use. It does not explicitly state when not to use or mention alternatives, but the context of sibling tools implies differentiation.

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