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

The readOnlyHint annotation already signals no side effects. The description adds meaningful behavioral detail by explaining that the response includes 'supportedMetrics' and the caveat about comparing only metrics both platforms report. This goes beyond the annotation to clarify data-availability behavior.

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 front-loaded with purpose and differentiation, and the technical note about supportedMetrics is necessary for correct usage. It is slightly dense but not verbose, with no redundant fluff.

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?

With an output schema present and the description outlining the return structure (per-platform rows, metric fields with previous/delta, supportedMetrics), the tool is fully specified for an agent to call and interpret results. No missing behavioral or data-format information.

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 JSON schema fully describes both parameters (from/to, ISO 8601, comparison window) with 100% coverage. The description adds no extra parameter semantics beyond repeating that there is no platform filter, so it stays at the baseline for high schema coverage.

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?

States a specific purpose: 'The overview metrics split per platform for a date window' and explicitly contrasts with the sibling 'Use get_analytics_overview for the combined total.' The use case 'for which platform performs best comparisons' makes the tool's role unambiguous.

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?

Provides explicit guidance to use get_analytics_overview for combined totals, the primary alternative. It also instructs to 'compare only metrics both platforms list there,' clarifying how to handle platform-specific metric availability, which is actionable usage advice.

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