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

Beyond the read-only annotations, the description discloses real analytical behavior: what 'pick' means (Pareto frontier: no other market both bigger and better-replying), that Korea domestic and sanctioned markets are excluded from picks, that regional_hub markets overstate local demand, and the reply_scope='none' case where an industry has no emails and is therefore unranked. These are exactly the caveats an agent needs to interpret results without misreading them.

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 ranking basis is front-loaded, which is good, but the text is three long, jargon-heavy sentences dense with nested parentheticals ('reply_scope: industry = compared with...', 'regional_hub flags...'), making it slower to parse than necessary. Every clause carries information, but the packaging could be tightened into a short lead plus caveat list.

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 carries the burden of explaining return fields, and it does so for the non-obvious ones (pick, regional_hub, reply_scope, exclusions). It stops short of describing the overall result shape or ordering guarantees, but an agent can call it and interpret the output 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 coverage is 100% and both parameters (item, limit) are fully documented with examples and bounds, so the description need not add parameter detail. The one concept it expands, reply_scope, is not actually a declared input parameter, so it functions as output semantics rather than parameter semantics; 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?

The opening clause states the resource and the ranking basis ('Import markets for a product ranked by size, with 3-year growth, Korea's share and the reply rate'), which tells an agent exactly what comes back. It does not name or contrast with the closest siblings (market_scan, export_rank, buyer_targets), so differentiation relies on the agent already knowing those tools.

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?

There is no statement of when to use this tool rather than market_scan or export_rank, nor any prerequisite or exclusion guidance for the agent's decision. Usage is only inferable from the title 'Where to sell a product' and the ranked-markets content.

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