product-intelligence

Get Price History Tool

get_price_history

Read-onlyIdempotent

Daily lowest observed price for a product over the last year, in one country. Use this to judge whether a current price or a claimed discount is actually good — compare today's price against the recent minimum. Recording started 2026-07-27, so earlier days are empty. Prices are integer minor units.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`country`	Yes	Country whose prices to return.
`product_id`	Yes	The Ponito product id (from search_products or get_product).

Output Schema

TableJSON Schema

Name	Required	Description	Default
`days`	Yes	One entry per day; recording started 2026-07-27, earlier days are absent.
`currency`	Yes	ISO currency of all prices in the series.

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedAug 12, 2026

changedInput schema / properties / country / enum

Previous value: -[
-  "CH",
-  "DE",
-  "FR",
-  "GB"
-]New value: +[
+  "CH",
+  "DE",
+  "FR",
+  "GB",
+  "AT",
+  "ES",
+  "NL"
+]

Changed1 schema field changedAug 5, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "properties": {
+    "currency": {
+      "description": "ISO currency of all prices in the series.",
+      "type": "string"
+    },
+    "days": {
+      "description": "One entry per day; recording started 2026-07-27, earlier days are absent.",
+      "items": {
+        "properties": {
+          "date": {
+            "description": "Day, formatted yyyy-MM-dd.",
+            "type": "string"
+          },
+          "min": {
+            "description": "Lowest valid price that day in minor units (cents/rappen); null when no shop had a valid price.",
+            "type": [
+              "integer",
+              "null"
+            ]
+          },
+          "observed": {
+            "description": "True when a price was directly observed that day; false when carried forward from a previous observation.",
+            "type": "boolean"
+          },
+          "shops": {
+            "description": "Shops with a valid price that day.",
+            "type": "integer"
+          }
+        },
+        "required": [
+          "date",
+          "min",
+          "shops",
+          "observed"
+        ],
+        "type": "object"
+      },
+      "type": "array"
+    }
+  },
+  "required": [
+    "currency",
+    "days"
+  ],
+  "type": "object"
+}

First observedAug 5, 2026

TDQS

A4.3/5.0

Behavior4/5

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

Annotations already indicate read-only, idempotent, non-destructive behavior. The description adds valuable context beyond annotations, such as the recording start date (2026-07-27) meaning earlier days are empty, and that prices are integer minor units. This helps set expectations without contradicting 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?

The description is three sentences, with the core function first, followed by usage guidance and a data caveat. Every sentence adds value and there is no 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?

Given the tool's low complexity (2 required params), rich annotations, and presence of an output schema, the description is complete. It covers purpose, usage, and an important data availability detail, making it fully sufficient for an agent to invoke correctly.

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 coverage is 100% with descriptions for both product_id (from search_products or get_product) and country (enum with valid countries). The description does not add significant parameter-level meaning beyond the schema, so baseline 3 is appropriate.

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 explicitly states it returns the daily lowest observed price for a product over the last year in one country. This clearly differentiates it from sibling tools get_product and search_products, which focus on product details and search, not historical price data.

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?

Provides explicit usage guidance: 'Use this to judge whether a current price or a claimed discount is actually good — compare today's price against the recent minimum.' However, it does not explicitly mention when not to use it or contrast with alternatives, so it's strong but not fully complete.

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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