lookup_company

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

Without annotations, the description carries the behavioral disclosure burden. It explicitly discloses the substring matching behavior and the possibility of multiple results, which is key for managing expectations. It does not address error handling or return format, but an output schema exists to cover that.

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 two sentences plus an argument explanation, front-loaded with a clear purpose. Every sentence provides useful information without redundancy.

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 single-parameter simplicity and presence of an output schema, the description covers the essential context: what the tool does and how to formulate queries. The substring caveat prevents misuse. No significant gaps remain.

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?

The schema provides no description for the 'query' parameter (0% coverage), but the description fully compensates by explaining acceptable formats (4-6 digit code or name substring) with examples. This exceeds the baseline and is highly actionable.

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 function: 'Look up one company's salary disclosure by stock code or name.' It includes specific input formats and even notes substring matching, distinguishing it from sibling tools that likely provide aggregate or trend data.

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 implies usage for single-company lookups, with clear input guidance (stock code or name). It does not explicitly mention alternative tools, but the scope is evident. The caveat about short queries returning multiple companies provides additional context.

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