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sklarstad

Sklarstad Storefront MCP

by sklarstad

get_product

Retrieve complete product details—summary, use cases, requirements, privacy, updates, pricing tiers, and checkout availability—to recommend the right tool accurately.

Instructions

Get full details for one product: summary, track record, what kinds of work it's built for, requirements, footage/data privacy, how it's updated, where to send feedback, availability, and every pricing tier with its description (and checkout URL once on sale).

Args: slug: A product slug from list_products, e.g. "film-shoot".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.1

TDQS

A4.4/5.0
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It discloses the breadth of returned information, including dynamic behavior like 'checkout URL once on sale.' It doesn't explicitly state read-only behavior, but 'Get' plus the non-mutating content list makes that implicit, and the output schema covers return structure.

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?

The description is front-loaded with the main purpose and effectively organized into a content list followed by an Args section. The list is long but every item adds information an agent would want; nothing is wasted.

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 one-parameter read tool with an output schema, the description is nearly complete: it names the required input, its source, an example, and the returned content. The only minor gap is not explicitly routing the agent to get_checkout_url when only a checkout link is needed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so the description must compensate, and it does. It explains that slug is 'A product slug from list_products' and gives a concrete example ('film-shoot'), adding meaning the schema's bare 'Slug' title does not provide.

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 uses a specific verb ('Get') and a specific resource ('full details for one product'), then enumerates exactly what details are included. This clearly distinguishes it from list_products (which lists products) and get_checkout_url (which is checkout-specific), even without opening the schema.

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 tells the agent to get the slug from list_products, which establishes a prerequisite and workflow context. It does not explicitly name get_checkout_url as an alternative, but the scope is clear enough that an agent would not confuse it with the siblings.

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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