detect_trending_formats

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It reveals that results are ranked by multiplier and compared against a roster baseline, but it does not explain what 'multiplier' means, how the baseline is calculated, or how date_range and sample_size parameters affect results. This is insufficient for a tool with no annotation safety signals.

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 a single, well-structured sentence that front-loads the action and unique value. Every word contributes to conveying the tool's purpose, with no filler or redundant repetition of the tool name.

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?

Despite having an output schema (so return values need not be described), the tool has 4 optional parameters with no documentation and no annotations. The description omits critical contextual details such as what 'roster baseline' means, how the date range is applied, and what a reasonable minimum sample size is. This is inadequate for a tool with analytical logic.

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?

Input schema has 4 parameters with 0% description coverage, and the tool description does not mention any parameter or how they influence the detection. The description adds zero value in explaining metric, date range, or min_sample_size semantics, leaving the agent to guess.

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: detecting format/hook tags whose average performance exceeds the roster baseline, ranked by multiplier. This is a specific verb-resource combination (detect + format/hook tags) and distinguishes it from siblings like top_performers, which likely rank creators or content.

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 usage (finding outperforming format tags) but provides no explicit guidance on when to use this tool versus alternatives like top_performers or get_performance_summary. There are no stated exclusions or alternative recommendations, leaving the agent to infer from the tool's specific purpose.

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