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

While there are no annotations, the description clearly defines the tool as a crucial reference point (a lookup/taxonomy tool) for utilizing parameters in other tools, which is a key behavioral characteristic beyond just 'listing'.

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 highly efficient, dedicating every word to explaining the tool's purpose and its vital role in parameter selection for other tools.

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 that the tool acts as a reference list for critical sibling tools like `sector_jobs`, providing the accurate sector terminology and structure is the most complete information needed for the agent to successfully interact with the ecosystem.

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 tool has 0 parameters and 100% schema coverage (baseline 3). The description compensates by explaining the semantic value of the output (the exact nomenclature for the sectors) which guides the agent in future actions.

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 tool explicitly states its function: listing 18 industry/sector classifications and their corresponding job counts. This is immediately clear and specific.

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?

It provides explicit instructions on how the output should be used: the terminology derived from this tool must be used when providing the 'sector' parameter in paid queries or other related tool calls.

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