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Agent Salon SF

Get stylist

get_stylist

One stylist, under the name the salon's booking system shows: salon, bookable status, specialty evidence with sources, services and prices, candidate start times from the published schedule, and booking link.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYesStylist slug, e.g. "hairshaper-shirley", or a display name like "Shirley"
formatNomarkdown

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.9/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It helpfully discloses the kinds of data returned, including 'specialty evidence with sources' and 'candidate start times from the published schedule,' which gives some sense of freshness and provenance. However, it omits error behavior for an unknown slug, whether the booking link is static, and any auth or rate-limit context.

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

Conciseness3/5

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

It is a single compact sentence fragment with no filler, and 'One stylist' is front-loaded. However, the colon-delimited field list reads like a data dump rather than a well-structured description, and the fragment lacks a clear action verb to anchor it.

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

Completeness3/5

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

For a two-parameter read lookup with no output schema, the description is reasonably complete about return contents. It still leaves out the meaning/behavior of the format parameter, error handling for invalid slugs, and any comparison with sibling tools, so it is adequate but not complete.

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 only 50%: the slug parameter is well documented in the schema (example and display-name fallback), but the format enum has no description. The tool description adds no parameter detail at all, so it does not compensate for the gap even though the enum values are largely self-explanatory.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies the resource as a single stylist and enumerates the specific detail it returns (salon, bookable status, services/prices, start times, booking link), which is much more specific than the tool name alone. It does not explicitly differentiate itself from siblings like get_salon or check_availability, keeping it from a 5.

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 on when to use this tool versus alternatives such as get_salon, check_availability, or get_booking_link. Usage is only implied by the tool name and the list of returned fields; no exclusions or prerequisites are stated.

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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