Skip to main content
Glama

get_product_details

Retrieve comprehensive product details including nutrition facts, ingredients, and pricing for Aldi items using product IDs.

Instructions

Get detailed information about a specific Aldi product including nutrition facts, ingredients, and price.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
product_idYesThe product ID (from search_products results)
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It describes a read-only operation ('Get detailed information'), but does not address potential behavioral traits such as error handling, authentication needs, rate limits, or what happens if the product_id is invalid. For a tool with zero annotation coverage, this is a significant gap in transparency.

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, efficient sentence that is front-loaded with the core purpose and includes specific details without any wasted words. Every part of the sentence contributes to understanding the tool's function.

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?

Given the tool's low complexity (single parameter, no output schema, no annotations), the description is adequate for basic understanding but incomplete. It lacks details on behavioral aspects like error handling or return format, which are important for a tool with no annotations or output schema, leaving gaps in contextual 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?

The input schema has 100% description coverage, with the parameter 'product_id' well-documented in the schema. The description adds minimal value beyond the schema by implying the product_id comes 'from search_products results', but does not provide additional syntax or format details. Baseline 3 is appropriate when the schema does the heavy lifting.

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 clearly states the specific action ('Get detailed information') and resource ('about a specific Aldi product'), with explicit details on what information is included ('nutrition facts, ingredients, and price'). It distinguishes this tool from sibling tools like 'search_products' by focusing on detailed retrieval rather than searching.

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 usage context by specifying it's for a 'specific Aldi product' and referencing 'product_id (from search_products results)', suggesting this tool is used after searching. However, it does not explicitly state when to use alternatives like 'check_product_availability' or provide exclusions, leaving some guidance gaps.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/markswendsen-code/mcp-aldi'

If you have feedback or need assistance with the MCP directory API, please join our Discord server