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

With no annotations, the description must carry the burden of behavioral disclosure. It reveals the read-only nature (trend calculation), the title-mention filter, and monthly/weekly aggregation. However, it does not disclose edge cases, rate limits, or the exact calculation method, which is acceptable for a simple query tool but not comprehensive.

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?

Two concise sentences with the core purpose front-loaded. No fluff or redundancy; every word earns its place.

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 description omits mention of the since/until date-range parameters and does not explain the trend calculation details. While an output schema exists, the description fails to convey the full capability set of a 4-parameter tool, leaving gaps for an agent.

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 coverage is only 50% (topic and bucket have descriptions). The description does not elaborate on the since/until parameters or their expected formats. It merely echoes the bucket granularity without adding value beyond the schema, failing to compensate for the missing parameter descriptions.

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 computes a post-count trend for a topic on HN, filtered to title mentions. It uses a specific verb ('trend') and resource ('topic on HN'), which distinguishes it from some siblings, though it doesn't explicitly name alternatives.

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 implies use for trend analysis ('heating up or cooling down') but offers no explicit when-to-use guidance or differentiation from sibling tools like get_entity_trend or compare_entity_trends. No conditions or exclusions are mentioned.

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