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

Annotations already declare readOnly/idempotent/non-destructive, so the bar is lower; the description adds genuinely useful scope boundaries (aggregates only, no campaign list, subject lines, offers or creative) and discloses that omitting a market yields one summary per market. The citation instruction for details_url is also actionable. It doesn't specify result limits or handling of untracked brands, keeping it at 4.

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?

Front-loaded with what the tool returns, followed by usage examples, then scope limits and the citation instruction — a sensible priority order with little waste. The middle field enumeration is dense but each item is a distinct return value, so almost 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?

For a two-parameter read tool with full schema coverage, an output schema, and safety annotations, the description supplies everything an agent still needs: what the aggregates cover, what they exclude, multi-market behavior, and sourcing guidance. Nothing material is left to inference.

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 coverage is 100%, so baseline is 3; the description adds value beyond it by restating the market-omission behavior in consequence terms (one summary per market) rather than as a schema note, and its examples reinforce the brand-name input. It does not add format details the schema lacks, but the schema already covers those.

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 is specific about the verb and resource: it returns a brand's email-marketing profile, and it enumerates the exact fields (market, category, first-observed date, 6-month email volume, 90-day frequency, latest campaign date). However, it never distinguishes itself from the sibling get_brand_email_frequency, which overlaps heavily with the frequency field described here.

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?

Concrete example questions ("How often does Newport email customers?", "Is IKEA still sending newsletters?") give clear when-to-use signals, and the note about multi-market brands clarifies a practical edge case. It stops short of the 5 because it offers no exclusion guidance against get_brand_email_frequency, the obvious alternative for the frequency question it uses as its own example.

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