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 adds useful behavioral details: the data is from 2023, and the tool always inlines a BFS attribution disclaimer. This goes beyond the basic input/output contract and helps set expectations, though it does not cover error handling or auth.

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 front-loaded with the core purpose, followed by dataset specifics and attribution behavior. Every sentence earns its place, with no padding or repetition.

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 lookup tool with two parameters and no output schema, the description covers the main return values and key data attributes (year, disclaimer). It is complete enough for an agent to invoke the tool correctly, though it could optionally mention error cases or the '999' canton code, but that is already in the schema.

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 coverage is 100%, and the description mentions the main parameter roles (NOGA division and optional canton) but adds no semantic detail beyond what the schema already provides. The schema itself includes descriptions and examples, so the description's contribution here is minimal but adequate.

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: retrieving Swiss enterprise statistics (STATENT, BFS) for a NOGA 2-digit division, optionally filtered by canton. It also specifies the concrete return values (establishments, jobs, FTE), making the purpose unambiguous and distinct from sibling tools.

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 clear usage context: it is used for Swiss enterprise statistics by NOGA division and optionally canton. It does not explicitly mention exclusions or alternatives, but the context is specific enough to guide an agent on when to invoke this tool.

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