Retrieve complete details for a specific employee using their ID to access HR records and manage personnel information.
Get details of a specific employee.
Args:
employee_id: Employee ID
Returns:
Complete employee details
| Name | Required | Description | Default |
|---|---|---|---|
| employee_id | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but offers minimal behavioral insight. It implies a read operation ('Get details') but doesn't disclose authentication needs, rate limits, error conditions, or what 'Complete employee details' entails beyond the output schema. This is inadequate for a tool with behavioral implications.
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 efficiently structured with a clear purpose statement followed by Args and Returns sections, using minimal sentences that each add value. There's no redundant information, and it's front-loaded with the core functionality.
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?
Given the tool's low complexity (single parameter) and the presence of an output schema (which handles return values), the description is moderately complete. However, it lacks context on permissions, error handling, or sibling tool differentiation, which are gaps for a read operation in a system with many related tools.
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 description adds meaningful context for the single parameter by specifying 'Employee ID' in the Args section, which clarifies its purpose beyond the schema's generic 'Employee Id' title. With 0% schema description coverage and only one parameter, this adequately compensates, though it could detail format or validation rules.
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 clearly states the tool's purpose with a specific verb ('Get') and resource ('employee'), making it immediately understandable. However, it doesn't differentiate from sibling tools like 'list_employees' or 'get_contact', which would require more specificity about scope or data granularity.
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 no guidance on when to use this tool versus alternatives like 'list_employees' for multiple records or 'get_contact' for related data. There's no mention of prerequisites, context, or exclusions, leaving usage decisions entirely to the agent's inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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