get_shopping_performance

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

No annotations are provided, so the description bears the full burden of explaining behavior. It only states what the tool returns and its scope, without explaining pagination (page_token), optional customer context, data freshness, rate limits, or whether results are aggregated. The read-only nature is implied by 'metrics' but not made explicit.

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 concise sentence with minimal filler, and the key qualifiers ('product-level', 'campaign', 'date window') are front-loaded. Every phrase contributes meaning. However, it is so brief that it omits important behavioral detail, which prevents a 5.

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 6 parameters, no output schema, and no annotations, yet the description provides only a high-level summary. It does not explain how to specify the date window unambiguously, whether pagination is needed, or what 'product-level' means in terms of result granularity. Given the tool's complexity, this is insufficient for correct invocation.

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?

With 0% schema description coverage, the description must compensate for the parameter documentation gap, but it only mentions 'campaign' and 'date window' generically. It does not explain how last_n_days relates to date_range_start/date_range_end, what page_token does, or how customer_id affects the query. Parameter names are somewhat self-explanatory, but critical combinations and constraints are left undocumented.

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 communicates a specific verb ('get') and resource ('product-level shopping metrics') with clear scope ('for a campaign and date window'). It distinguishes itself from sibling tools like get_campaign_performance and get_ad_performance by using the term 'product-level shopping metrics'. However, it could be more explicit about exactly which metrics are returned.

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 offers no guidance on when to use this tool versus alternatives, nor does it mention exclusions or complementary tools. The intended context is vaguely implied by the phrase 'for a campaign and date window', but no explicit comparison to siblings is provided. An agent would have to infer usage from the tool name alone.

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