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

Annotations already declare readOnlyHint, idempotentHint, non-destructive and closed-world, so the safety profile is fully covered. The description adds that output includes data-source health and coverage, implying a freshness signal, but says nothing about pagination, limits, or what a call actually returns structurally.

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 dense sentences, zero filler: the first front-loads what is returned, the second states intended usage. Every clause 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?

With no output schema, the description correctly compensates by enumerating the aggregate fields returned, and annotations cover the safety profile. It is nearly complete, only missing window defaults/limits that live in the schema and any note on result shape beyond the metric list.

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% with a single optional 'days' parameter whose default, min and max are documented in the schema. The description references 'a window' but adds no format or interpretation detail beyond what the schema already provides, so 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 verb and resource ('Aggregate numbers for a window') and enumerates the returned metrics (alerts, high-severity count, brands hit, by chain, by match type, top brands, data-source health). This clearly delineates it from siblings like get_brand_report, but it never explicitly names an alternative, so it stops short of a 5.

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 clear when-to-use guidance: 'Use for overviews, trend questions and to check data freshness.' That covers the primary intents, but it offers no exclusions or explicit alternative routing (e.g., when to prefer get_brand_report or search_alerts).

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