BasketWatch

Recent price changes

recent_price_changes

Read-onlyIdempotent

Price movements at one supermarket between the latest nightly snapshot and the previous one: shelf price rises and falls with old price, new price and % change, and promotions starting or ending listed separately (an offer ending is not a price rise).

Args:
    store: "aldi" | "tesco" | "supervalu" | "dunnes" | "lidl".
    limit: how many movers to return (default 25).

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "store": "<store>"
    },
    "name": "recent_price_changes"
  }
}

Input Schema

Name	Required	Description	Default
`limit`	No
`store`	Yes

Output Schema

Name	Required	Description
`date`	No	Snapshot being reported
`prev_date`	No	Snapshot compared against
`promotions`	No	Offers starting or ending, not shelf moves
`shelf_decreases`	No
`shelf_increases`	No
`clubcard_changes`	No	Member price changes: Tesco Clubcard, SuperValu Real Rewards or Lidl Plus
`promotions_total`	No
`shelf_decreases_total`	No
`shelf_increases_total`	No
`clubcard_changes_total`	No

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedOct 18, 2026

changedOutput schema / properties / clubcard_changes / description

Previous value: -"Loyalty-card price changes, Tesco only"New value: +"Member price changes: Tesco Clubcard, SuperValu Real Rewards or Lidl Plus"

First observedOct 12, 2026

TDQS

A3.9/5.0

Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive, open-world, so the safety profile is covered. The description adds genuinely non-obvious behavioral context: the nightly-snapshot comparison basis, the fields returned (old price, new price, % change), that promotions are listed separately, and the semantic rule that an ending offer is not a price rise.

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?

Front-loaded with the core definition, then the promotion caveat, then a compact Args block. Every sentence carries information an agent needs; nothing is filler.

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?

An output schema exists, so return-value documentation is optional, and the description still sketches the shape usefully. What's missing is operational detail such as snapshot freshness/timezone or error behavior for an unrecognized store value, though the required-parameter contract is clear.

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 description coverage is 0% and the schema declares no enums, so the description carries the full burden — and it does: it enumerates the five valid store values and explains that limit is the number of movers returned with a default of 25. It stops short of stating bounds or format expectations for limit (min/max, pagination behavior).

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 states a specific verb+resource (price movements at one supermarket) and a precise comparison window (latest nightly snapshot vs. the previous one), which separates it from per-product history tools like get_price_history. It doesn't name the closest sibling (price_movements) explicitly, so the differentiation is inferred rather than stated.

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

Usage Guidelines3/5

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

Usage is only implied by the scope phrase 'between the latest nightly snapshot and the previous one' — an agent can infer this is a short-window, single-store view. There is no explicit when-to-use/when-not guidance and no mention of when to prefer price_movements, get_price_history, or get_promotions instead.

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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