Get employees

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It meaningfully reveals that the tool automatically pages through the entire result set and combines it, which is non-obvious behavior. It does not discuss authentication, rate limits, or exact response shape, but for a simple read-only fetch the pagination disclosure is the most important behavioral trait.

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 tight sentences deliver the core behavior, pagination detail, and a concrete use case without any filler. The action and resource are front-loaded, and every clause 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 single-optional-parameter fetch tool with no output schema, the description is complete enough: it explains what is fetched, how pagination is handled, and what the results should be used for. The stated mapping use case also implies the important return fields (employee ID, name, job title, employment status), so an agent can call the tool and use its result appropriately.

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?

There is only one optional parameter, pageSize, and the input schema already describes it completely, including default and maximum values. The description's mention of automatic paging complements the schema, but it does not add new parameter-level meaning beyond what the schema already covers.

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: 'Fetch all employees from Keka HRIS.' It also clarifies scope (all employees, no filters) and introduces the intended mapping purpose, which clearly distinguishes it from sibling tools that handle timesheets, projects, clients, leaves, and holidays.

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 gives an explicit use case: 'Use this to map employee IDs found in timesheet data to names, job titles, and employment status.' It does not explicitly list when not to use it or name alternative tools, but the sibling set is sufficiently distinct and the stated use case is concrete enough for an agent to select it correctly.

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