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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds valuable behavioral context beyond annotations: it states the return is bounded and non-personal, that only companies with active jobs are returned, and that certain filters exclude companies with missing investor/stage data. It also warns that passing a bare string to list arguments is a validation error. This is strong additional behavioral disclosure, though it doesn't detail pagination or exact result shape, which the output schema likely covers.

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 well-structured with a clear opening sentence, a scope note, a type warning, and labeled filter sections. It is longer than minimal but every sentence adds meaningful information about behavior or parameter semantics. The only minor inefficiency is the slight redundancy between the opening scope statement and the 'Only companies with at least one active job' sentence, but this is acceptable for emphasis.

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 moderate complexity (4 optional parameters, no required params, output schema present), the description is complete. It covers what the tool returns, the filtering semantics, data-coverage caveats, and type requirements. The output schema handles return-value details, and annotations handle safety. An agent has everything needed to select and invoke this 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?

Schema description coverage is 0%, so the description carries the full burden of explaining parameters. It thoroughly explains query (substring of name/slug or whole sector word), investor (aliases resolve, ~83% population), and stage (exact enum list, case-insensitive, ~12% missing). It also clarifies the list-argument type requirement. The limit parameter is not explicitly described, but its name and default in the schema are self-explanatory, and the description's depth on the other three parameters more than compensates.

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 opens with a specific verb and resource: 'Search public Rocketlist hiring companies.' It immediately distinguishes itself from siblings by stating it returns bounded, non-personal company data and only companies with active jobs, which clearly separates it from get_company, get_job, and search_jobs.

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 states when to use this tool: to search public hiring companies, and it clarifies that only companies with at least one active job are returned, matching the company list on rocketlist.ai. It also provides detailed filter semantics and notes that certain filters exclude companies with missing data, giving clear guidance on when results may be incomplete. While it doesn't explicitly name sibling alternatives, the scope and filter behavior make usage conditions unambiguous.

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