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FadiSheh

Lufa Farms MCP Server

by FadiSheh

lufa_get_product_details

Retrieve complete product details such as name, price, producer, category, weight, and organic status using a product ID from the marketplace catalog.

Instructions

Get detailed information for a specific product.

Returns name, price, producer, category, weight, and organic status, looked up from the full marketplace catalog.

Args: product_id: Product ID from lufa_get_products or lufa_search_products.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
product_idYes
Behavior4/5

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

No annotations are provided, so the description carries the burden of disclosing behavior. It states that the tool is a read-only lookup ('Get', 'Returns', 'looked up from the full marketplace catalog'). It does not describe error scenarios (e.g., product not found) or auth requirements, but for a simple get-by-ID tool, this is sufficient context.

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 concise and front-loaded: the first sentence states the purpose, the second lists return fields, and the third provides source context. The Args section is minimal and relevant. No redundant sentences or unnecessary detail.

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?

For a simple tool with one parameter, no output schema, and no annotations, the description covers all essential aspects: what it does, what it returns (specific fields), and where the input ID comes from. It is complete enough for an agent to invoke it correctly without ambiguity.

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 description coverage is 0%, but the description includes an Args section that explains the product_id parameter's origin ('Product ID from lufa_get_products or lufa_search_products'), adding significant meaning beyond the schema's bare 'string' type. This tells the agent where to obtain a valid value.

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 tool's function: 'Get detailed information for a specific product.' It specifies the resource (product) and the verb (get), and lists the return fields (name, price, producer, category, weight, organic status). This clearly distinguishes it from sibling tools like lufa_get_products (lists) and lufa_search_products (search), as it focuses on a single product by ID.

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 provides clear context by stating that the product_id comes from lufa_get_products or lufa_search_products, implying this tool is used after obtaining a specific product ID. It does not explicitly mention alternative tools or when not to use it, but the prerequisite and purpose are clear enough for an agent to infer the appropriate usage.

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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