List Keka Leave Requests

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 return-field context and filter behavior, but it does not disclose operational details like API latency, rate limits, or pagination behavior beyond the schema's defaults. This is acceptable given the strong annotation coverage, but not exceptional.

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 an opening summary, Args list, Returns line, and Examples section. The Args list duplicates schema information, which is slightly redundant, but it is not overly long and the examples earn their place by clarifying real usage.

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 filtered list tool with no output schema, the description is complete: it names the returned fields, explains the main filters, gives defaults for pagination and response format, and provides concrete examples. Combined with the rich input schema and annotations, the agent has what it needs to call the 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 100%, so the baseline is 3. The description's Args section largely restates the schema's parameter descriptions (e.g., comma-separated employee IDs, ISO 8601 dates, pageSize max 200) without adding deeper semantics. It does offer usage examples that clarify intent, but not enough to push above baseline.

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: 'Retrieve leave requests from Keka' with optional filters. It clearly identifies the resource as Keka leave requests, which distinguishes it from sibling tools like keka_list_leave_types and keka_get_leave_balances.

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 use-case examples ('View pending leaves for a team', 'See who is on leave this month') that tell the agent how to apply filters. It does not explicitly name alternatives or state when not to use this tool, but the context is clear enough for correct selection.

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