industry_stats

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

No annotations are provided, so the description carries the full burden. It states the tool summarizes pay distribution and explains its intended purpose, but it does not disclose specific output details or side effects. For a read-only summarization tool, this is adequate but not rich.

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 compact and well-structured: a purpose statement, a usage rationale, and a parameter list with examples. Every sentence adds value and there is no 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 tool's simplicity (one parameter, output schema exists), the description fully covers purpose, usage, and parameter semantics. The output schema handles return details, so the description is complete for an agent to select and invoke the tool correctly.

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 only defines 'industry' as a required string with no description. The description adds valuable guidance: 'Industry name or part of one' and provides concrete examples, clarifying that partial matches are acceptable.

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 first sentence 'Summarise the pay distribution within one industry' uses a specific verb and resource, clearly defining the tool's function. The second sentence adds the sector-baseline use case, which distinguishes it from sibling tools like lookup_company or top_by_median.

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 explicitly says to use this tool to judge whether a single company's pay is high or low for its sector, providing a clear when-to-use scenario. It does not explicitly name alternatives or exclusions, but the context is sufficient for most agents.

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