Skip to main content
Glama
samiashi
by samiashi

Find deals

find_deals
Read-only

Find watch listings priced below market by computing price stats and returning the cheapest options at or below the 25th percentile, showing savings vs the median.

Instructions

Find listings priced below market for a watch scope: computes full-range price stats (up to 3 polite requests), then returns the cheapest listings at or below the market p25 with their percentage below median. The one-call answer to 'find me a good deal on X'. Free-text scopes match fuzzily (a 'Black Bay 58 GMT' query can match plain Black Bay 58s) - prefer manufacturerIds + models or referenceNumber for precision.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
yearNo
queryNoFree-text scope, e.g. 'Rolex Submariner'
facetsNoFacet filters (caseMaterials, braceletMaterial, dialColors, gender, movementTypes, watchCategories, maxAgeInDays) - values via list_filters
modelsNoModel id from find_models
sampleNo'spread' (accurate market stats, up to 3 requests) or 'cheapest' (fast triage, 1 request)spread
priceToNo
benchmarkNoWith a countries filter, 'global' prices the local listings against the WORLDWIDE market (adds 1-3 requests) - the right mode for 'is this local price actually good?'scope
conditionNo
countriesNo
priceFromNo
maxResultsNoMax deals to return
manufacturerIdsNoBrand id from list_brands
referenceNumberNoReference number, e.g. '116610lv'

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
noteYes
dealsYesListings priced at or below the market p25, cheapest first
statsYes
coverageYes
currencyYes
benchmarkYesWhich market the stats describe; 'global' when local listings are ranked against the world
sourceUrlYes
totalCountYes
ignoredFacetsNoFacet keys that were ignored because they are not passthrough params (e.g. countryIds -> use 'countries', usedOrNew -> use 'condition')
benchmarkTotalCountNoTotal listings in the global benchmark population (only when benchmark='global')

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.6.0

TDQS

A4.7/5.0
Behavior5/5

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

The annotations already declare readOnlyHint=true and openWorldHint=true, and the description adds substantial beyond that: it discloses fuzzy free-text matching behavior, the up-to-3-polite-requests cost, the p25/median computation, and the benchmark mode nuance for local-vs-global pricing. No contradiction with annotations.

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 dense sentences front-load the tool's purpose and unique output, then add the most important usage caveat and precision guidance. Every sentence earns its place; there is no fluff or repetition of schema content.

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 13-parameter tool with an output schema, the description is remarkably complete: it explains the computation, the request cost, the fuzzy-match behavior, the preferred parameters, and the benchmark mode context. The output schema covers return-value details, so the description does not need to restate them.

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 62%, and the description adds meaningful guidance beyond the schema: free-text scopes match fuzzily, manufacturerIds/models/referenceNumber give precision, and benchmark=global with a countries filter prices against the worldwide market. It does not elaborate on every parameter, but it enriches the most decision-critical ones.

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 names the exact deliverable: listings priced below market, computed from full-range stats, with results at or below the market p25 and their percentage below median. It clearly defines the resource scope and output, and this unique p25/median behavior distinguishes it functionally from siblings like search_listings and get_price_stats.

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?

It gives clear when-to-use guidance: "The one-call answer to 'find me a good deal on X'." It also gives concrete preference guidance for precision: prefer manufacturerIds + models or referenceNumber over free-text. It does not explicitly name alternative tools or state when not to use it, so it stops 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.