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Prezzinvista - Radar dei Volantini

Andamento del prezzo di un prodotto

get_price_trend
Read-onlyIdempotent

Use this when the user asks how much a common grocery or household product costs in Italy this week, whether it is getting cheaper or more expensive, or which chain has it cheapest: e.g. "how much does pasta cost this week", "is coffee more expensive than last week". Returns the typical (median) and lowest flyer price this week, the previous weeks and each chain this week, with the link to the product page on prezzinvista.it. Covers Italy only, and about two hundred staple products (pasta, caffè, olio di oliva, latte, detersivo, pannolini, …), named in Italian; specific brands and models are what search_flyer_offers looks up. In hosts that support MCP Apps the results are also shown to the user as a card with the weekly trend.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
productYesThe product, in Italian: e.g. "pasta", "caffè", "olio di oliva", "detersivo lavatrice".

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesThe product page on prezzinvista.it
weeksYesMost recent last
offersNoOffers this week
sourceNoWho to credit for the data
productYes
prices_areYesper kg, per l, per pack (groceries) or per item (appliances)
updated_atNoWhen the flyers were last read (ISO 8601). They are read again every three hours
change_noteNoWhen there is no percentage: how this week compares with the week before
change_percentNoThis week against the week before, only when the change is clear
stores_this_weekYesLowest first
typical_price_eurNoMedian flyer price this week
previous_typical_price_eurNoMedian the week before, when comparable

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive, and closed-world, so the safety profile is covered. The description adds valuable non-structured context: Italy-only coverage, a limited catalogue of ~200 Italian-named staples, and the MCP Apps card rendering. It does not mention rate limits or caching, but the annotation burden is largely met.

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?

Front-loads the when-to-use triggers and examples, then covers scope, alternative, and output. It is somewhat long and the parenthetical product list is close to redundant with the schema examples, but every sentence carries information.

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?

An output schema exists so return values need not be explained, yet the description still summarizes them (median/lowest, weekly and per-chain, link). Combined with the Italy-only and catalogue-size limits and the sibling routing, an agent has everything needed to call it correctly.

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 100% and the single param is documented in the schema, so baseline is 3. The description goes beyond it by clarifying the expected vocabulary is a fixed set of ~200 staple products named in Italian (with examples like detersivo, pannolini), which meaningfully constrains how to fill the parameter.

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 resource (weekly price trend of a product) with verb-like intent and explicitly scopes it: median/lowest flyer prices per week and per chain. It also distinguishes itself from the sibling search_flyer_offers, which handles specific brands and models.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives concrete trigger conditions ('how much does pasta cost this week', 'is coffee more expensive than last week') and names the alternative tool with the condition that selects it. Nothing is left to inference.

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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