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Find offers for what a user wants

find_offers

Turns the user's request, with any context they stated (location, dates, budget, party size, preferences), into an intent and returns the offers that fit, best first, each with a tracked link to show the user (tracked_url). Matching runs in the background; when no offers are back yet, call get_offers with the intent_id in a few seconds. It never buys anything. By using Arugula you agree to arugulanet.com/terms. Privacy: arugulanet.com/privacy.

Input Schema

NameRequiredDescriptionDefault
textYesWhat the user wants, in their own words, including where if it matters.
briefNotrue for a short answer: each offer's title, price, fit, how to buy and tracked link, without the explanations.
datesNoWhen: dates or times the user gave, for example 'before 9am tomorrow'.
budgetNoThe user's budget.
localeNoBCP 47 language tag of the text, for example en-SG.
countryNoThe user's country as ISO 3166-1 alpha-2, for example SG, only if the user said it or you know it from them; never your server's. Offers there are preferred; a place in the text still decides.
party_sizeNoHow many people.
preferencesNoAnything else the user prefers, in their words.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / country
      Added value: +{
      +  "description": "The user's country as ISO 3166-1 alpha-2, for example SG, only if the user said it or you know it from them; never your server's. Offers there are preferred; a place in the text still decides.",
      +  "type": "string"
      +}
  2. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Adds behavior the annotations do not convey: matching is asynchronous and requires polling, and the tool never completes a purchase (clarifying the readOnlyHint=false / destructiveHint=false combination as a non-read that writes intent state). Terms and privacy pointers are also disclosed. What is missing is whether repeated calls create duplicate intents, which matters given idempotentHint=false.

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

Conciseness4/5

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

The core purpose and the polling rule are front-loaded in the first two sentences. The closing terms/privacy sentence is boilerplate that dilutes an otherwise tight description, though it may be legally required.

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

Completeness4/5

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

With eight parameters, a nested budget object, and no output schema, the description covers the essential contract: what goes in, that offers come back ranked with a tracked_url, and that results may be deferred. It stops short of describing the brief-mode output shape, but the schema already carries that.

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%, so every parameter is already documented, and the baseline is 3. The description does add value by grouping the context dimensions the agent should extract (location, dates, budget, party size, preferences), but it offers no syntax or precedence guidance beyond what the schema states.

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 transformation ('turns the user's request ... into an intent') and a specific output ('returns the offers that fit, best first, each with a tracked link'). It also explicitly distinguishes itself from the sibling get_offers by framing that tool as the polling follow-up.

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 follow-up rule ('when no offers are back yet, call get_offers with the intent_id in a few seconds') and rules out purchase behavior. It does not address the other sibling, explain_match, so there is no coverage of every alternative, but the usage context is unambiguous.

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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