Retrieve the signed-in employee's payroll preferences from Keka, including salary structure, deduction, and payout settings, without needing admin API keys.
Payroll preferences for the signed-in employee.
| 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 behavioral burden, and it discloses almost nothing. It implies a read (from the name) and that results are scoped to the caller, but says nothing about return shape, default/fallback behavior, or permissions.
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?
At six words it is admirably short with no wasted clauses, but the brevity comes from omission rather than tight writing, and it is a sentence fragment rather than a front-loaded statement of action.
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?
The tool is structurally simple (0 params) but has no output schema and no annotations, so the description is the only source of information an agent has. It never says what the payroll preferences contain or what is returned when none are configured, leaving the definition thin for even a simple read.
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 schema takes zero parameters, so there is nothing for the description to disambiguate; the baseline for a 0-param tool is 4. The description does at least confirm the implicit scoping (signed-in employee), consistent with an empty input 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 text is essentially the tool name expanded into a noun phrase: 'Payroll preferences' restates 'get_payroll_preferences' with no verb describing what the tool actually does. The only added information is the scope qualifier 'for the signed-in employee', which does not distinguish it from siblings like get_preferences or get_timesheet_profile.
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, when not to, or which sibling to prefer for related preference/profile data. The agent must infer usage entirely from the name in a list of ~40 similarly named get_* tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.