Recommend Suppliers

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true, but the description adds valuable behavioral context beyond this: it explains the ranking logic (prioritizes own-factory, then quality score, then capacity), describes error handling (returns empty data if no product match found), provides fallback guidance (try broader terms, limit to 3 calls), and specifies the return structure including ranking logic note. No contradiction with annotations.

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 well-structured with clear sections (USE WHEN, WORKFLOW, DIFFERENCE, RETURNS, ERRORS, FALLBACK) and each sentence adds value. It could be slightly more concise by integrating some sections, but overall it's efficiently organized and front-loaded with key information.

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?

Given the tool's complexity and lack of output schema, the description provides comprehensive context: it explains the recommendation logic, distinguishes from siblings, outlines usage scenarios, describes the return format, error behavior, and fallback strategies. This compensates well for the missing output schema and aligns with the rich annotations provided.

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 schema already documents all parameters thoroughly. The description doesn't add significant parameter-specific semantics beyond what's in the schema, though it implies the product parameter is central to the recommendation logic. This meets the baseline expectation when schema coverage is high.

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 explicitly states the tool's purpose as 'Smart supplier recommendation based on sourcing requirements' and distinguishes it from siblings by explaining it's for ranking by fit rather than filtering by exact criteria like search_suppliers or finding alternatives from known suppliers like find_alternatives. This provides clear differentiation and a specific verb+resource combination.

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?

The description includes explicit 'USE WHEN' scenarios with concrete examples, distinguishes when to use this tool versus search_suppliers and find_alternatives, and provides a 'WORKFLOW' section explaining it's the entry point for 'I need help finding a supplier' requests. It also mentions follow-up actions with get_supplier_detail or compare_suppliers.

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