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shopsavvy

ShopSavvy Data API MCP Server

Official
by shopsavvy

product_price_history

Retrieve historical pricing data for a product within a specific date range to analyze price trends and determine the best time to buy.

Instructions

Get historical pricing data for a product within a specific date range

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
end_dateYesEnd date in YYYY-MM-DD format (e.g., '2024-01-31')
retailerNoOptional: specific retailer domain name to filter results
identifierYesProduct identifier (barcode, ASIN, URL, model number, or ShopSavvy ID)
start_dateYesStart date in YYYY-MM-DD format (e.g., '2024-01-01')
Install Server

TDQS

B3.1/5.0
Behavior2/5

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

With no annotations provided, the description carries the full behavioral burden. It implies a read-only operation via 'Get', but does not disclose output format, pagination, possible aggregation of price history, date-range validation, or behavior with unsupported identifiers.

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 a single, compact sentence that directly conveys the tool's core purpose without repetition or filler. Every word contributes to meaning.

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

Completeness3/5

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

The description is adequate for a simple data-retrieval tool, but it lacks additional context such as what the history includes, how to interpret the returned data, or the role of the optional retailer parameter. With no output schema or annotations, a bit more context would improve completeness.

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 the schema already documents all parameters and their formats. The description adds no parameter-level meaning beyond the schema, matching the baseline expectation without enhancing it.

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 clearly states the action ('Get'), the resource ('historical pricing data'), and the scope ('within a specific date range'). It is distinct enough from siblings like product_lookup and product_offers, though it does not explicitly name or contrast them.

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

Usage Guidelines2/5

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

No guidance is given about when to choose this tool over siblings such as product_lookup or product_offers, nor are any exclusions or prerequisites mentioned. The usage context is only minimally implied by the phrase 'historical pricing data'.

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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