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Glama

schedule_meeting

Schedule employee meetings by submitting employee ID, meeting date and time, and topic to manage HR calendars.

Instructions

Schedule a meeting for an employee.
Args:
    emp_id: str
    meeting_dt: datetime
    topic: str
Returns:
    str

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topicYes
emp_idYes
meeting_dtYes

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

C2.9/5.0
Behavior2/5

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

Annotations are absent, so the description must shoulder the burden of behavioral disclosure. It implies a write operation ('schedule') but says nothing about side effects, permission requirements, validation of employee existence, availability checks, or what the returned string represents.

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 core purpose in a single sentence. However, the Args/Returns block duplicates schema information and adds little value, slightly reducing the quality of the structure.

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?

Despite its simplicity, the description lacks important contextual details an agent needs to invoke it correctly, such as the format of meeting_dt, how the meeting is created, and whether it is appropriate for a given user request. The return value is stated, and an output schema exists, but behavioral and usage context are 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%, and the description's Args block only repeats the parameter names and Python types already present in the schema. It does not explain the meaning of emp_id, meeting_dt, or topic, nor any constraints such as date-time format or valid employee ID 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 first sentence 'Schedule a meeting for an employee' provides a specific verb and resource, making the tool's function unambiguous. The sibling tools (send_email, create_ticket, apply_leave) are clearly distinct in domain, so no confusion arises even without explicit differentiation.

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

Usage Guidelines2/5

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

There is no guidance about when to use this tool versus alternatives such as create_ticket or apply_leave, nor any exclusions or prerequisites. The description only states what it does, leaving the agent to infer usage context from the name.

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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