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ShearQuery — Barber & Beauty Industry Data

Register for the free LIVE training

register_for_live_training
Idempotent

Register someone for ShearQuery's FREE live training (Mondays 3 PM Eastern, Google Meet). Ask for their first name, email and mobile number first — all three are required — and register them only when they've said they want a seat. It signs them up for the next session still open and emails the confirmation; the Google Meet link arrives by email 24 hours before. It does NOT turn on text reminders: for those they tick the box at /live-training. On the ShearQuery website the person confirms with a button.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
emailYesTheir email address, exactly as they gave it.
first_nameYesTheir first name.
account_typeNoWhat they are, if they said (barber, stylist, shop owner, school, student…). Optional.
mobile_phoneYesTheir mobile number with area code.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.6/5.0
Behavior5/5

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

Beyond the annotations (openWorld, non-readOnly, non-destructive), it discloses concrete behavior: it signs up for the next still-open session, emails a confirmation, and the Google Meet link arrives 24 hours before. It explicitly excludes text reminders, preventing an agent from assuming opt-in side effects.

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 front-loaded with the core action and requirements, and each sentence carries useful information (timing, confirmation email, exclusion of SMS reminders). It is a bit long for a single-purpose registration tool but avoids redundancy.

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?

With no output schema, the description adequately covers the downstream effects an agent needs (confirmation email, link timing, no SMS opt-in). Nothing essential for correct invocation is missing.

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?

Schema description coverage is 100%, so all four parameters including the account_type enum are already documented. The description only reiterates that first name, email and mobile are required, adding no syntax or format detail beyond the schema. Baseline 3 applies when the schema does the heavy lifting.

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 states a specific verb and resource ('Register someone for ShearQuery's FREE live training') with concrete scope details (Mondays 3 PM Eastern, Google Meet). It is clearly distinguishable from siblings like promote_live_training and shearquery_training, which serve different intents.

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?

It gives explicit preconditions ('Ask for their first name, email and mobile number first — all three are required') and a gating condition ('register them only when they've said they want a seat'). It also states what the tool does NOT do and where to go instead ('does NOT turn on text reminders: for those they tick the box at /live-training').

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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