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Kroger

by io.github.pipeworx-io
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Kroger Product Details

kroger_product_details
Read-onlyIdempotent

Get full detail for one grocery product by its product_id — price, promo price, stock level, size, categories, aisle location, images. Pass zip_code or location_id for store-specific price/stock. Example: kroger_product_details({ product_id: "0001111041700", zip_code: "45202" })

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
_apiKeyNoOptional: your own Kroger API credentials as "client_id:client_secret"
zip_codeNoUS ZIP code — nearest store auto-selected for price/stock
product_idYes13-digit Kroger product ID from kroger_product_search
location_idNoExact store location_id (overrides zip_code)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "product_id": "0001111041700",
+    "zip_code": "45202"
+  },
+  {
+    "location_id": "01400959",
+    "product_id": "0001111041700"
+  }
+]
  2. First observed

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint. Description adds that price/stock are store-specific and that location_id overrides zip_code, which is useful behavioral context beyond 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 efficient sentences, includes an example, no wasted words. Front-loaded with core function.

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?

No output schema, but description lists expected return fields (price, promo, stock, etc.) and explains store-specific logic. Complete for a product detail lookup tool.

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 100%, but description adds an operational example and clarifies that location_id overrides zip_code and product_id comes from kroger_product_search, significantly aiding parameter understanding.

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?

Description clearly states verb 'Get' and resource 'full detail for one grocery product', listing specific fields (price, promo price, stock, etc.). It implicitly distinguishes from kroger_product_search (requires product_id) and kroger_store_locator.

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?

Description explains when to use zip_code or location_id for store-specific data, includes an example. Missing explicit when-not-to-use or alternatives, but sibling tools provide context.

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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