Province Distribution

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true, covering safety and idempotency. The description adds valuable context beyond annotations: it specifies the ranking order (provinces ranked by supplier count with typical leaders), describes the return structure in detail, and clarifies this is for discovery purposes. No contradiction with annotations exists.

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 (purpose, USE WHEN, WORKFLOW, RETURNS, NOTE), each sentence adds value, and it's front-loaded with the core purpose. No redundant information or wasted words, making it efficient for an agent to parse.

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 moderate complexity (one optional parameter), rich annotations covering safety and idempotency, and no output schema, the description provides excellent completeness. It explains the purpose, usage scenarios, workflow integration, detailed return format, and behavioral notes like ranking, which compensates for the lack of output schema and gives the agent full context.

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% for the single parameter (product_type), with the schema already documenting it as a filter for product type. The description doesn't add any additional parameter semantics beyond what's in the schema, but with high coverage, the baseline is 3. The description focuses more on output and usage context.

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 states the tool's purpose with specific verb ('show') and resource ('supplier distribution across Chinese provinces'), distinguishing it from siblings like search_suppliers (which filters by province) or get_supplier_detail (which focuses on individual suppliers). It explicitly identifies the geographic scope and data type.

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 provides explicit guidance with a 'USE WHEN' section listing three specific scenarios (including Chinese phrases), a 'WORKFLOW' section explaining this is a standalone discovery tool to identify provinces before using search_suppliers, and clear differentiation from alternatives. It tells both when to use it and how it fits into a broader workflow.

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