datasets_jobs_companies

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

With no annotations provided, the description carries full burden. It discloses the data source (discovered company board registry), the meaning of sponsors_visa (certified DOL LCA filings), and the important caveat that results are historical evidence. It also provides enums for provider, status, and sort. It lacks explicit mention of pagination or rate limits, but those are partially covered by schema params.

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 dense but well-structured: opening verb phrase, then explanation of data, a usage tip, a caveat, and enum lists. The enum lists are long but necessary for tool usage. No redundant sentences, though the paragraph could be slightly tightened without losing information.

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 tool with 8 optional params, no required params, and no output schema, the description explains the core purpose, filters (especially provider/status/sort), and the nature of the data. It does not explain min_open_roles, but that is self-evident from the schema. The sibling context includes many job tools, and the description's emphasis on company-level evidence helps disambiguate.

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%, so baseline is 3. The description adds value by explaining sponsors_visa in detail (recent DOL LCA data), and critically provides the full provider enum which the schema only labels 'Provider filter.' This goes beyond what the schema offers, raising the score to 4.

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: 'Find which companies are hiring' and specifies it searches 'the discovered company board registry' returning companies, ATS providers, and open role counts. This specific verb+resource pairing distinguishes it from job-level search tools like datasets_jobs_search.

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 context (company-level analysis vs. specific role search) with 'This is company-level historical evidence, not a guarantee for a specific role or candidate,' but it does not explicitly name alternative tools or provide when-to-use/when-not-to-use guidance. The usage guidance is present implicitly but not contrasted with siblings.

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