Shopping product performance

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

Annotations already mark this as a read-only, non-destructive, open-world query. The description goes beyond that by disclosing the aggregation model ('each product summed over the campaigns it ran in'), the grain (item id), and the three output groupings, which is meaningful behavioral context for interpreting numbers.

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 short paragraphs with the metric scope front-loaded and the aggregation/return behavior following; the API reference link is the only marginal content and no sentence is wasted.

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 annotations covering safety and an output schema covering the response shape, the remaining burden is scope and semantics, which the description handles. Minor gap: no mention of pagination/limit interaction or how insights are prioritized.

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 limit, campaign_id, customer_id and both date fields are already documented. The description only adds a loose reference to date-range and item-id semantics, so the schema does the heavy lifting and the baseline 3 applies.

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 resource (per-product performance), an exact metric set (spend, clicks, conversions, CPA, ROAS), and the channel scope (Shopping and Performance Max), which separates it from siblings like get_pmax_performance or get_campaign_performance. An agent can identify what it returns without opening the schema.

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?

Usage is only implied: the promise of 'insights on what to do' with non-converting products suggests a diagnostic/reporting use case, but no alternative tool is named and no when-not condition is given, even though get_pmax_performance and get_campaign_performance overlap in scope.

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