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

Annotations already mark readOnlyHint=true and openWorldHint=true, and the description adds context about verified buyers and the nature of the output (companies sourcing a commodity). It does not contradict annotations and explains the data quality aspect, though it doesn't discuss rate limits or pagination.

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: what it does, when to use it, and input. Every sentence earns its place; front-loaded with the core purpose.

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 lookup tool with an output schema and annotations, the description covers purpose, usage, and input sufficiently. It lacks details on verification methodology or error handling, but the output schema likely covers return structure.

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 covers 100% of parameters with descriptions, and the description's 'Input: a country and an optional commodity filter' adds no new information beyond schema. The extra parameters (limit, async) are already described in schema, so baseline score of 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?

The description clearly identifies the tool as returning verified local buyers in a country for a given commodity, listing specific output fields (buyer type, city, website, etc.). This distinguishes it from sibling tools like ftg_seller_catalog (sellers) through the focus on buyers and sourcing demand.

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?

Explicitly states when to use: 'an agent builds a sourcing or export shortlist, or needs real B2B demand contacts in a market.' This provides clear use-case context, though it doesn't mention exclusions or alternative tools by name.

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