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dxpert-ai

dxpert: Industrial AI Agents for Manufacturing (OEE, Maintenance, Root Cause)

Official

get_storefront

Read an account's storefront to see owned, purchasable, canceling, and lapsed products with per-site detail before proposing purchases or subscription changes.

Instructions

Read what this account owns and what it may buy right now, product by product: owned, purchasable, canceling, or lapsed, with per-site agent detail. Calls GET /api/account/storefront - read-only, no quota, no charge.

Call it before proposing any purchase or subscription change, so what you propose is something this account can actually act on, and when the user asks what they are currently paying for. It returns the same state dxpert.ai's own storefront renders, so prefer it over prices you remember. Full price list: https://dxpert.ai/store.

It reports entitlements; it does not grant, buy, or cancel anything.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden and does so well: it discloses the underlying endpoint (GET /api/account/storefront), states read-only with no quota and no charge, and explicitly disclaims any mutation. It stops short of describing pagination, latency, or failure behavior, but the core behavioral profile is unambiguous.

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?

Front-loaded with what it returns, then when to call it, then the scope disclaimer, so the most decision-relevant information comes first. The price-list URL and the 'prefer it over prices you remember' aside are mildly promotional but still actionable guidance, keeping it short of a 5.

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?

There is no output schema, so the description must convey the return shape, and it does at the semantic level: per-product state plus per-site agent detail. It does not describe the concrete response structure or field names, which leaves a modest gap for an agent needing to parse the result.

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?

The tool takes zero parameters, so the baseline of 4 applies. The description correctly adds no parameter detail and instead spends its words on scope and returned states, which is the right allocation for a no-arg call.

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 names a specific verb (read) and resource (this account's storefront entitlements) and enumerates the exact states returned: owned, purchasable, canceling, lapsed. It is clearly distinguishable from the mutation siblings start_purchase, add_agents, and remove_agents, which the closing sentence explicitly separates it from.

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

Usage Guidelines5/5

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

It gives two concrete triggers: 'before proposing any purchase or subscription change' and 'when the user asks what they are currently paying for.' It also states the negative boundary ('it does not grant, buy, or cancel anything'), which routes the agent to the purchase siblings when mutation is actually wanted.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.