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getParticipantPreferences

Retrieve a participant's full scheduling preferences including working hours, blackout windows, buffer time, and maximum meetings per day to view or prepare for updates.

Instructions

Use this tool when you need to read a participant's scheduling preferences — working hours by day, blackout windows, buffer time between meetings, and maximum meetings per day. Important: getParticipant does not return preferences; you must call this tool separately. Call this before setParticipantPreferences if you only want to update some fields, since setParticipantPreferences replaces the entire preference object.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
participantIdYesUUID of the participant.
Behavior4/5

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

The description clearly implies a read-only operation by stating 'read a participant's scheduling preferences,' but it does not explicitly declare that the tool has no side effects, especially in the absence of annotations. While the read intent is unambiguous, a more explicit statement about non-mutation would increase transparency. Score 4 reflects minor omission.

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

Conciseness5/5

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

The description is three sentences, each serving a distinct purpose: stating the tool's function, warning about a sibling limitation, and providing usage best practices. There is no redundant or filler content, and the key information is front-loaded.

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

Completeness5/5

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

For a simple read tool with one parameter and no output schema, the description is complete. It explains what data is returned (preferences components) and supplies context about sibling tools and usage sequencing. No further details (e.g., error handling, pagination) are necessary given the tool's simplicity.

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

Parameters3/5

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

The input schema has 100% coverage with a single parameter (participantId) already documented as a required UUID. The description does not add any additional semantics about this parameter beyond what the schema already provides. The baseline for high coverage is 3.

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 explicitly states the tool reads a participant's scheduling preferences and lists the components (working hours, blackout windows, buffer time, max meetings per day). It distinguishes itself from the sibling getParticipant by noting that getParticipant does not return preferences, making the purpose clear and distinct.

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

Usage Guidelines5/5

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

The description provides explicit when-to-use guidance ('Use this tool when you need to read a participant's scheduling preferences'), a when-not-to-use note (getParticipant does not return preferences), and a usage recommendation relative to setParticipantPreferences ('Call this before setParticipantPreferences if you only want to update some fields, since setParticipantPreferences replaces the entire preference object'). This is comprehensive and educational.

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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