Kooperativa: company past employees

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

With no annotations provided, the description carries the burden of behavioral disclosure. It discloses what each result contains (a past_positions array with specific roles) and notes the pagination style (has_more/next_page). This is meaningful behavioral context beyond the schema, though it does not cover edge cases like invalid company IDs or result ordering.

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?

Two sentences contain all essential information with no filler. The core purpose is front-loaded, followed by result shape and pagination behavior. Every sentence earns its place.

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 simple paginated list tool with no output schema, the description covers the main facts needed to call it: what it returns, the past_positions array, and pagination. It could be more complete by explicitly mapping page/per_page to the pagination mechanism or describing typical response fields, but nothing critical is missing for a basic invocation.

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 only 33%; company_id is documented in the schema, while page and per_page are not described. The description reinforces that company_id is numeric and mentions pagination, which indirectly relates to page/per_page, but it does not explicitly explain the pagination parameters or their semantics. This is partial compensation for a low-coverage schema.

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 uses a specific verb ('List'), identifies the resource ('people who previously worked at a company'), and explains the core concept with 'held a role there, since moved on'. It clearly distinguishes this from current-employee tools by emphasizing previously/ past positions, making sibling differentiation easy.

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 clearly frames when this tool is relevant: when listing former employees of a specific company. It does not explicitly name alternatives or exclusions, but the phrase 'since moved on' implies a boundary against current-employee tools, and the sibling names reinforce that context.

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