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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, so the safety profile is covered. The description adds valuable behavioral context: the non-additive nature of platform-reported figures, the fact that Meta and Google may double-claim orders, and that MerchantFlow-attributed revenue is null in this result. This goes beyond the annotations and helps the agent interpret results correctly.

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?

Three sentences with zero waste. The core purpose is front-loaded, the optional comparison is stated, and the critical non-additivity caveat is placed at the end where it can be absorbed without obscuring the main function. Every sentence earns its place.

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 is complete for a read-only analytics tool with a rich output schema. It explains the key metric (blended MER), the per-platform breakdown, the optional comparison, and the critical interpretation caveat (non-additive, null MerchantFlow revenue). The only minor gap is not describing the exact output shape, but the output schema exists and covers that.

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 the schema already documents all three parameters. The description adds context about the compare_to parameter ('optional comparison to the previous period') and the date range, but does not add syntax or format details beyond the schema. Baseline 3 is correct when the schema carries the parameter documentation burden.

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 a specific verb ('Get'), a specific resource (blended MER and per-platform spend over a date range), and adds a distinctive scope (optional comparison to previous period). It clearly distinguishes itself from sibling tools like get_ad_performance or get_revenue_breakdown by naming the exact metrics and the non-additive caveat.

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 when to use it: when you need blended MER and per-platform spend with optional period comparison. It does not explicitly name alternatives or exclusions, but the specificity of the metrics and the caveat about non-additivity give clear context. A 4 is appropriate because it lacks an explicit 'use this instead of X' statement but is otherwise clear.

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