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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, so safety is covered. The description adds meaningful behavioral context: results are optionally country-filtered, each portal includes payout terms, sign-up bonus is only credited via its URL and should be shown as a clickable link, and null/0 semantics for minimum payout are explained. This exceeds the baseline for annotation-covered tools.

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 longer than strictly minimal, but every section earns its place: distinguishing siblings, usage examples, payout-term semantics, and the sign-up-bonus URL rule. The main sentence is dense and front-loaded with the core behavior before diving into payout details. Slight redundancy in the payout-term explanations could be tightened, but it is well organized.

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 list tool with one optional parameter, 100% schema coverage, an output schema, and read-only/idempotent annotations, the description fully covers what an agent needs: what data comes back, how to interpret null vs 0 values, how to present sign-up bonus links, and how to route to siblings. No significant gap remains.

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 the baseline is 3; the description adds value by explaining how to pass the country code ('gb', not 'uk'), gives concrete examples ('us', 'ca', 'de'), and tells when to omit it ('omit it to search all supported countries'). It also links the country_code parameter to the natural-language usage examples.

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 uses a specific verb ('Returns') and resource ('cashback portals GotCashback compares'), and immediately specifies the optional country scope and that each portal includes its payout terms. It clearly names sibling tools (get_cashback_rates_by_store_name, get_portals_by_name) to distinguish what it is not, so an agent can select it correctly.

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?

Provides explicit usage scenarios with example natural-language queries ('which cashback portals are there in Canada?', 'compare portals side by side'), and explicitly says when not to use it: for store rates call get_cashback_rates_by_store_name, for one named portal call get_portals_by_name. This is strong when-to-use vs alternative guidance.

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