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HairDora Salon Scheduling

List stylists who take appointments

list_providers
Read-onlyIdempotent

Use this when someone asks which stylists or hairdressers work at their salon or can be booked. Returns up to 100 hairdresser display names from the organization that owns the salon (no contact details or schedules). Not for stylists' days off.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
salonIdYesId of one of the user's salons, as the salon list returns it (24 lowercase hex characters)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
countYes
statusYes
hasMoreYes
providersYesDisplay names of organization members with the hairdresser role; roles are organization-wide, not per salon. Staff ids, contact details, avatar URLs, role records, schedules and organization data are excluded.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • changedInput schema / properties / salonId / description
      Previous value: -"Salon id returned by list_salons (24 lowercase hex characters)"New value: +"Id of one of the user's salons, as the salon list returns it (24 lowercase hex characters)"
    • addedOutput schema / properties / providers / description
      Added value: +"Display names of organization members with the hairdresser role; roles are organization-wide, not per salon. Staff ids, contact details, avatar URLs, role records, schedules and organization data are excluded."
  2. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), so the description's job is to add context. It does: a hard cap of 100 results, the org-level scope, and an explicit statement that contact details and schedules are NOT returned. That negative disclosure is genuinely useful for planning follow-up calls.

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 short sentences: trigger first, return shape and scope second, exclusion last. Every sentence carries distinct information and nothing is repeated from the name or annotations.

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 one-parameter read tool with full annotation coverage and an output schema, this is complete: the agent knows when to call it, what it gets back, what it won't get back, and the result cap. No further description is needed to invoke it correctly.

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% for the single salonId parameter, so the baseline is 3. The description adds only indirect value by tying the result set to the organization that owns the salon, implying salonId is the resolution key, but supplies no format or validation detail beyond the schema.

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?

States a specific verb and resource ('which stylists or hairdressers work at their salon or can be booked') and pins down the return set: up to 100 hairdresser display names scoped to the salon's owning organization. An agent can distinguish this from list_salons, list_services, or get_salon_availability without opening the 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?

Gives an explicit trigger ('when someone asks which stylists or hairdressers work at their salon') and an explicit exclusion ('Not for stylists' days off'), which implicitly routes to get_salon_availability. It does not name the alternative tool directly, so it falls short of a 5.

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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