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ShearQuery — Barber & Beauty Industry Data

Invite a client to ShearQuery

invite_client_to_shearquery

For an APPROVED agency: email a barber, stylist, shop, salon or school an invite to join ShearQuery. When they join through it, the business is credited to this agency (and earns commission when it pays for a plan). Sends a real email from ShearQuery naming the agency — confirm the address and business name with the agency before calling. Limits: 50 a day, and not the same address twice in a week.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
emailYesThe client's email address.
business_nameNoTheir business or name, used in the greeting. Optional.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.7/5.0
Behavior5/5

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

Annotations only declare the generic safety profile (readOnly=false, openWorld=true, destructive=false), leaving rate/policy behavior unstated. The description fills that gap richly: a real email is sent naming the agency, the business is credited to the agency with commission on paid plans, and explicit limits of 50/day and one invite per address per week.

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?

Three sentences, front-loaded with eligibility and the core action, then consequences, then the operational caveat and limits. No filler; every clause carries decision-relevant information.

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?

No output schema exists, but the description covers prerequisites, side effects (real email, attribution, commission), verification step, and hard limits. Nothing an agent needs to invoke this correctly is missing.

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

Parameters4/5

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

Schema coverage is 100%, so the baseline is 3. The description goes beyond it by framing the email and business name as values that must be verified with the agency before calling, and clarifies business_name's role in the greeting, which the schema states only tersely.

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?

Specific verb (email an invite) plus resource (client: barber, stylist, shop, salon, school) and the join→attribution→commission outcome. An agent can distinguish this from siblings like propose_booking_link or find_prospects without opening any schema.

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

Usage Guidelines4/5

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

States the precondition clearly ('For an APPROVED agency') and adds a procedural gate ('confirm the address and business name with the agency before calling'). It does not name a rival tool to use instead, but the context is unambiguous for when this applies.

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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