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kishimoto-banana

Shopify Python MCP Server

update_product

Modify Shopify product details including titles, descriptions, variants, inventory, and images. Use this tool to update essential data like status, vendor, and tags for streamlined product management.

Instructions

商品を更新する

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
body_htmlNo商品の説明(HTML形式)
imagesNo画像
optionsNoオプション
product_idYes商品ID
product_typeNo商品タイプ
statusNoステータス
tagsNoタグ(カンマ区切り)
titleNo商品名
variantsNoバリエーション
vendorNoベンダー名
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure but offers none. '更新する' (update) implies a mutation operation, but the description doesn't mention permission requirements, whether updates are partial or complete, side effects, error conditions, or response format. For a mutation tool with 10 parameters and no annotations, 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 extremely concise at just three Japanese characters. While this represents under-specification rather than ideal conciseness, according to the scoring framework, it's not penalized in this dimension. The description wastes no words and is front-loaded, earning full points for conciseness despite its inadequacy in other areas.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity (10 parameters, mutation operation), lack of annotations, and absence of an output schema, the description is severely incomplete. It doesn't explain what the tool returns, error conditions, or behavioral constraints. For a product update tool in what appears to be an e-commerce context, this minimal description leaves critical gaps for an agent to understand how to use it effectively.

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?

Schema description coverage is 100%, so the schema already documents all 10 parameters thoroughly with Japanese descriptions. The tool description adds no additional parameter context beyond what's in the schema. According to scoring rules, when schema coverage is high (>80%), the baseline is 3 even with no parameter information in the description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose2/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description '商品を更新する' (Update product) is a tautology that essentially restates the tool name 'update_product' in Japanese. It doesn't specify what aspects of a product can be updated or differentiate this tool from its sibling 'create_product' beyond the basic verb. The purpose is clear at a high level but lacks specificity about scope or capabilities.

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

Usage Guidelines1/5

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

The description provides no guidance on when to use this tool versus alternatives like 'create_product' or 'get_product'. There's no mention of prerequisites (e.g., needing an existing product ID), constraints, or typical use cases. An agent would have to infer usage from the parameter schema alone.

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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