SeaWeb

search_salons

Read-onlyIdempotent

Search hair salons, barbershops and beauty salons by natural-language intent (e.g. "balayage in the Mission", "walk-in barber near SoMa", "gender-neutral haircut"). Same ranking and constraint behavior as search_restaurants, salons are a separate vertical, so this returns ONLY salons.

location: neighborhood filter (e.g. "Mission District", "SoMa", "The
  Castro"); empty (default) = all SF.
goal: discover|book (optional).
cuisine: reused as the SERVICE-TYPE slot, pass a service word to filter
  (e.g. "color", "balayage", "haircut", "perm", "beard trim").
price_max: budget cue as int 1-4 ($ through $$$$); 0 = unset.
dietary: unused for salons (no dietary tags); leave empty.
party_size: group-size mention ("for 2"); 0 = unset.
bookable: True only when the caller needs a live booking link.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`goal`	No
`intent`	Yes
`cuisine`	No
`dietary`	No
`bookable`	No
`location`	No
`price_max`	No
`party_size`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedSep 6, 2026

TDQS

A4.6/5.0

Behavior4/5

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

Annotations already declare read-only/idempotent/non-destructive; description adds useful behavior beyond that: same ranking/constraint behavior as search_restaurants, salons-only return set, and the cuisine slot being repurposed as a service-type filter while dietary is unused. That explains real quirks an agent would otherwise discover only after calling.

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 behavior statement is front-loaded, and the parameter block is a compact reference with short annotations per field. No filler or repetition; the length is justified by eight parameters and several domain-specific quirks.

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 an 8-parameter search tool with no schema descriptions, the description covers every parameter, the selection semantics, the vertical restriction, and the connection to search_restaurants. Since an output schema exists, return-value detail is not required here.

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

Parameters5/5

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

The schema has 0% coverage, and the description fully compensates by documenting every parameter with concrete examples and edge-case defaults (price_max 1-4/$-$$$$, bookable True only for live booking links, dietary unused). It even explains the reused 'cuisine' slot, which the schema alone would badly mislead on.

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 ('search') and resource ('hair salons, barbershops and beauty salons'), plus the vertical boundary: returns ONLY salons, unlike search_restaurants. The natural-language intent examples make the tool's function concrete.

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?

Clearly frames use as natural-language salon search and notes shared ranking/constraint behavior with search_restaurants. It does not explicitly name all alternative tools (e.g., filter_salons) or state when not to use it, but the vertical distinction and intent-based entry point are strong guidance.

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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