analytics

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

No annotations are provided, so the description should disclose behavioral traits such as side effects, data freshness, or access requirements. It only describes modes and parameters, lacking any explanation of behavior (e.g., whether it is read-only, or if it aggregates data over time).

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 structured with clear sections and bullet points, making it easy to scan. It is reasonably concise, though some repetition could be eliminated. Front-loaded with purpose, then details.

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 three parameters, no enums, and an output schema present (which covers return values), the description still fails to explain parameter semantics and lacks guidance on when to choose each mode. It feels incomplete for a multi-mode analytics tool.

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?

With 0% schema description coverage, the description must explain parameters. It lists parameters for each mode (e.g., optimization_type, limit) but does not define what optimization_type accepts (e.g., string values), its default, or the effect of limit. This is insufficient for correct usage.

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 provides analytics on optimization effectiveness and usage patterns, and it distinguishes two modes (optimization and usage), which helps differentiate it from sibling tools like 'optimize' or 'review' that focus on performing actions.

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 implicitly gives usage guidance by specifying which parameters go with which mode, but it does not explicitly state when to use this tool versus alternatives like 'optimize' or 'search', nor does it provide any when-not-to-use conditions.

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