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

Goes well beyond the readOnly/openWorld annotations by disclosing default window (last 30 days), zero-fill semantics for inactive brands, and partial-failure tolerance (revoked OAuth or deactivated customerId don't block other brands). That failure-isolation detail is exactly the kind of context annotations cannot carry; rate limits and response shape are the only notable omissions.

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, each earning its place: what it returns, when it is useful, and the edge-case behavior. The most important information (aggregate scope and returned fields) is front-loaded.

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?

There is no output schema, so the description compensates by naming the returned fields (per-brand totals plus overall sum). Combined with the default-window and partial-failure notes, an agent has everything needed to call and interpret this tool correctly.

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 three date parameters are already documented in the schema. The description restates the 30-day default but adds no syntax, precedence rules between explicit dates and periodDays, or format guidance beyond what the schema provides — the baseline 3.

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 verb and resource ('Aggregate Google Ads performance across every brand on this account') and enumerates the returned metrics (spend, impressions, clicks, conversions), which lets an agent separate it from single-scope siblings like get_campaign_report or list_brands.

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?

Gives a concrete use case and implicitly contrasts with the alternative ('without asking for each brand individually'), so the agent knows to prefer this over per-brand calls. It stops short of naming a sibling tool or stating when-not-to-use it, e.g. for a single brand or campaign.

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