Query Analytics

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

With no annotations provided, the description carries full responsibility for behavior disclosure. It does add the 30-day window and the type of data returned, which gives some transparency about the query scope. However, it does not disclose the response format, pagination, or behavior when date parameters are omitted or exceed the 30-day window, leaving ambiguity.

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-front-loaded sentence that states the action, resource, and key details without any superfluous information. Every word earns its place, making it highly concise and easy to parse.

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 relatively simple with only three parameters and no output schema, so the description covers the core purpose. However, the interplay between the '30-day window' and arbitrary startDate/endDate parameters is unclear—does it represent a default, a maximum, or a fixed range? Also, without an output schema, the description would benefit from explaining what the query returns for each metric value, but it does not.

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 already provides 100% coverage for all three parameters, so the baseline is 3. The description adds extra meaning by indicating the 30-day window, which likely relates to how startDate and endDate are interpreted, and by naming the metrics that correspond to the 'metric' enum options (e.g., daily, features). This goes beyond simply restating 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 the tool queries mock analytics data and specifies the exact metrics (daily active users, revenue, churn rate, feature usage) and a 30-day window. This uses a specific verb ('Query') and resource ('analytics data'), and it fully distinguishes itself from the sibling tools, none of which deal with analytics.

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?

Usage context is implied: use this tool to query analytics data. However, there is no explicit guidance on when to use it versus alternatives, nor any exclusions or prerequisites. The mention of 'mock' data hints that it is not for real data, but this is not stated as a direct usage guideline.

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