Search Industrial Clusters

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true. The description adds valuable behavioral context beyond annotations: pagination behavior, return format details, error handling (empty array if no matches), fallback strategies, and language support (Chinese/English).

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?

Well-structured with clear sections (purpose, usage examples, coverage, returns, workflow, errors, fallback). Some redundancy exists (Chinese translation at end repeats purpose), but overall information density is high with minimal waste.

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 search tool with comprehensive annotations and 100% schema coverage, the description provides excellent context: clear purpose, usage scenarios, example clusters, return format, pagination, error handling, fallback strategies, workflow integration with siblings, and language support. No output schema exists, but the description documents the return structure adequately.

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 semantics beyond what's in the schema, though it provides context about specialization keywords through examples. Baseline 3 is appropriate when schema does the heavy lifting.

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 searches for 'Chinese apparel industrial clusters and textile markets' with specific examples of what it covers. It clearly distinguishes from siblings like 'search_fabrics' or 'search_suppliers' by focusing on clusters rather than individual suppliers or materials.

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 'USE WHEN' examples with concrete user queries, lists famous clusters covered, and gives clear workflow guidance ('Use this to discover clusters. Then use compare_clusters...'). It also specifies fallback strategies and language support.

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