list_supported_attendance_formatsList the attendance-device export header shapes the WatheeqaHR analyzer is tested against (vendor, example header row, the column it treats as the employee ID). Use it to tell a user whether their device export is likely to work before they upload it.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, openWorldHint=false and destructiveHint=false, so the safety profile is covered. The description adds genuine context beyond them: the content of each entry (vendor, example header row, employee-ID column) and that the set is bounded to formats the analyzer is tested against, which tells the agent results are not exhaustive.
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 with zero waste: the first defines the returned data, the second defines the decision it supports. The scope qualifier is front-loaded and no sentence merely restates the title.
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?
With no parameters and no output schema, the description carries the burden of explaining what comes back, and it does so by naming the fields in each entry. It also conveys the 'tested against' limitation, which is the key caveat an agent needs before treating the list as exhaustive.
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?
Zero parameters, so there is nothing to disambiguate; baseline applies. The description correctly signals a no-argument call by describing a static, self-contained list.
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?
States a specific verb (List) and a precisely scoped resource: attendance-device export header shapes the analyzer is tested against, including the vendor/header-row/employee-ID column triple. That is far more informative than the title alone. It does not explicitly name analyze_attendance_file as the contrasting tool, so sibling differentiation is only implied.
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 second sentence gives a clear use case and timing: run it before a user uploads a device export to predict whether it will work. The alternative (analyzing the file itself) is implied by 'before they upload it' but never named, so the agent must infer the routing to analyze_attendance_file.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.