Sensor Recommend

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 about what the tool returns (popular, well-supported options with platform compatibility info) and how results are sorted (by platform support count), which goes beyond what annotations provide.

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, exclusion, question answered, parameters, returns) and every sentence adds value. It's appropriately sized for a 6-parameter tool with complex options, though slightly lengthy due to the extensive measure type 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?

Given the tool's complexity (6 parameters, 0% schema coverage) and the presence of an output schema, the description is complete. It explains all parameters thoroughly, clarifies the tool's purpose and exclusions, and describes the return format and sorting logic, making the output schema sufficient for detailed response 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?

With 0% schema description coverage, the description carries the full burden of explaining parameters. It provides comprehensive details for all 6 parameters: query usage examples, measure types with extensive list and aliases, type examples, protocol options, platform filters, and limit default. This fully compensates for the schema's lack of descriptions.

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 specific verb ('Recommend') and resource ('sensor ICs and modules'), explicitly distinguishing it from sibling tools like jlc_search for buying parts. It answers a specific question pattern: 'What sensor should I use to measure X on my platform?'

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 on when to use this tool (for sensor recommendations based on measurement needs) and when not to use it ('NOT for buying parts — use jlc_search'). It names a specific alternative tool and defines the exact question this tool answers.

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