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

Annotations already declare readOnlyHint=true, openWorldHint=false, and destructiveHint=false, so the safety profile is covered. The description adds a high-level list of returned metric categories, but it does not disclose operational behavior such as pagination, default date ranges, or whether the analysis is scoped to a single funnel.

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, front-loaded sentence fragment with no wasted words. It efficiently conveys the main metric categories, though it could be slightly more structured by explicitly stating that it retrieves statistics for a given funnel.

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?

For a 4-parameter read-only analytics tool with no output schema, the description is minimally adequate. It names the metric categories returned but omits operational details like date-range behavior, attribution model effects, and how results are scoped to a funnel, leaving gaps that the fully documented schema and annotations only partially fill.

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?

Schema description coverage is 100%, so all four parameters (funnel_id, startDate, endDate, opportunityModel) are already fully documented in the schema. The description adds no additional parameter meaning, which is acceptable given the complete 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?

The description states the analysis domain and lists the metrics covered (funnel conversions, ROI statistics, experiment performance). It is clear what the tool does, but it does not differentiate itself from siblings such as experiment_performance_stats, which likely overlaps on experiment performance.

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?

There is no guidance on when to use this tool versus alternatives, nor any mention of prerequisites, exclusions, or typical scenarios. The description only lists content, leaving the agent to infer usage context from the tool name and schema.

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