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

Annotations already indicate readOnlyHint=true and destructiveHint=false, so the description mainly adds the list of metric categories and opportunity models. It does not disclose return format, aggregation level, date-range defaults, or behavior when dates are omitted, leaving some behavioral 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 structured with clear labels and is reasonably short, but it repeats similar concepts: 'funnel conversion analysis' appears in the opening and in USE FOR, and ROI/metrics are restated. The content earns its place, yet some redundancy and the inaccurate REQUIRED statement reduce clarity.

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 description covers what the tool analyzes, required inputs, and the opportunity model enum, which is enough for basic invocation. However, there is no output schema and the description does not explain the return structure, pagination, or how results are grouped, leaving meaningful gaps for a comprehensive stats 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?

Schema coverage is 100%, so baseline is 3, but the description introduces a conflicting format: it says 'date range (YYYY-MM-DD to YYYY-MM-DD format)' while the schema specifies ISO 8601 timestamps for startDate/endDate. It also lists date range as REQUIRED even though only funnel_id is required in the schema, which could mislead an agent.

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 identifies the tool as funnel conversion analysis with specific outputs (conversions, ROI, experiment performance), and the title matches the operation. It does not explicitly differentiate from siblings like experiment_performance_stats or performance_metrics, which slightly overlaps in scope.

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 'USE FOR' section provides explicit contexts such as funnel conversion analysis, ROI metrics, pipeline attribution, and conversion rate optimization. However, it does not state when not to use this tool or point to alternatives for more specialized stats like experiment-only performance.

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