Retrieve the signed-in employee's Keka preferences, including dashboard settings for profile, leave, attendance, expenses, timesheets, assets, and payroll.
Signed-in employee's Keka preferences.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure, and it delivers none: no indication of what preference categories are returned, whether it is a safe read, auth requirements, or response shape.
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?
It is a single short fragment with no wasted words, but it is under-specified rather than genuinely concise – there is only one front-loaded clause and no supporting detail.
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 no-param read tool with no output schema, the description still leaves the agent unsure what 'preferences' actually covers (attendance, leave, notifications?) and provides no safety or return context to compensate for the absence of annotations.
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?
The tool takes zero parameters, so there is nothing for the description to clarify; the baseline of 4 applies. No parameter semantics are needed or missing.
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 names the resource ('Keka preferences') and scopes it to the signed-in employee, but it is a noun fragment with no verb and does not distinguish this tool from close siblings like get_payroll_preferences or get_feedback_settings, which are also 'preferences'.
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?
There is no statement of when to call this tool, what it is for in a workflow, or how it differs from the many other preference/settings getters in the sibling list. Usage can only be inferred from the name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.