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Get price, dates and specs for a product

get_product_facts
Read-only

Official price (only when the maker announced or is selling it; otherwise labelled as an estimate), announcement and availability dates with their source, and specs. Every spec is marked Confirmed, Rumored, Our read or No source on file, with the source outlet and date.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
product_slugYesFrom list_products, e.g. 'apple-watch'

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, so the description doesn't need to restate safety. It adds valuable behavioral context: price may be an estimate if not officially announced, and every spec is marked with a confidence level and source. This goes beyond the schema and 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?

Two sentences, front-loaded with the most important content (price, dates, specs) and then the sourcing nuance. Every sentence earns its place; no filler or repetition of the schema.

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?

For a read-only single-parameter tool with no output schema, the description covers the key return values and their trust levels. It doesn't describe the exact response structure, but with no output schema and a simple parameter, the description is sufficient for an agent to select and invoke the tool 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 only parameter, product_slug, is already described with an example. The description adds context by implying the slug identifies the product whose facts are returned, but it doesn't need to add more because the schema fully documents 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?

The description states a specific verb ('Get') and resource ('product facts'), and enumerates the exact content: price, dates, and specs. It also distinguishes itself from siblings by focusing on facts with source labels, which is not covered by get_product or list_products.

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?

The description implies when to use this tool: when you need price, dates, or specs with sourcing. It does not explicitly name alternatives or exclusions, but the sibling list and the tool's specific scope make the usage context clear. A small gap is not stating when to prefer get_product or compare_products.

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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