mktg.query_analytics

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

No annotations are provided, so the description must fully disclose behavior. It mentions 'Query... and track' but does not confirm read-only nature, rate limits, pagination, or return size. The description is insufficient for an agent to understand side effects or constraints.

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 sentences with clear first sentence and supporting examples. No unnecessary words; efficiently conveys the tool's purpose.

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 has no output schema, so the description should explain return format (e.g., aggregated metrics or raw events). It does not. Also missing information on date range limitations or filtering behavior. Incomplete for a query tool with optional parameters.

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 input schema has 100% description coverage, so the schema already documents parameters. The description adds context by listing example event types, but this is already implied by the schema's description for event_type. No significant new meaning is added beyond 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 user analytics and event data, listing specific metrics (page views, API calls, feature usage, user engagement). This distinguishes it from sibling marketing tools focused on campaigns, social accounts, and emails, and aligns with the tool name.

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 analytics queries but provides no explicit when-to-use or when-not-to-use guidance. With many sibling tools, clearer differentiation would help, but the examples hint at appropriate scenarios.

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