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apply_leave

Submit leave requests for employees by providing employee ID and leave dates.

Instructions

Apply leave for an employee.
Args:
    emp_id: str
    leave_dates: List[datetime]
Returns:
    str

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
emp_idYes
leave_datesYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

B3.2/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden of disclosing behavior, but it only says 'Apply leave' and gives a return type. It does not explain side effects (e.g., whether leave is booked immediately, requires approval, or checks balance), prerequisites, or failure behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact and front-loads the main purpose in the first sentence, with a clean docstring layout. It is not overly long, though the Args/Returns lines are largely redundant with the structured schema and output schema.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a state-changing tool with no annotations, the description is too sparse: it omits context about leave-request rules, return-value semantics, and any validation or preconditions. The presence of an output schema offsets some need to describe return values, but behavioral context is still missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description should compensate, but the Args section merely repeats the schema's names and types without adding meaning. It does not explain what emp_id refers to, what date range is valid, or that leave_dates should be ISO-formatted strings, and the 'List[datetime]' type is potentially misleading given the schema's date-time string format.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a clear verb ('Apply') and resource ('leave') and specifies the target ('for an employee'), making the tool's function immediately understandable and distinct from the read-oriented sibling tools like get_leave_balance and get_leave_history.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The action-oriented description implies this tool is for submitting a leave request, in contrast to sibling get_leave_* tools that retrieve data, so an agent can infer when to use it. However, it provides no explicit guidance, alternative names, or conditions for when not to use it.

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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