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shopify_update_metafield

Create or update metafields on Shopify resources such as products, customers, orders, variants, or collections by providing owner ID, namespace, key, and value.

Instructions

Create or update a metafield on a Shopify resource.

Args: owner_type: One of: PRODUCT, CUSTOMER, ORDER, VARIANT, COLLECTION. Defaults to PRODUCT. owner_id (required): Resource ID (numeric or GID). namespace (required): Metafield namespace. key (required): Metafield key. value (required): Metafield value (string-encoded per the type). type: Metafield type (e.g. single_line_text_field, number_integer, json). Defaults to single_line_text_field.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
owner_typeNo
owner_idNo
namespaceNo
keyNo
valueNo
typeNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations exist, so the description bears full responsibility. It reveals the tool performs a write operation (create/update) but does not disclose idempotency, required permissions, rate limits, error behaviors, or side effects (e.g., whether updating triggers webhooks).

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: one sentence for purpose followed by a bullet-like list of parameters with clear explanations. Every sentence adds value with no redundancy.

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?

The description covers all parameters but lacks behavioral context such as idempotency, validation rules, or return value structure. Since an output schema exists, the agent can infer return type, but for a complex mutation tool with 6 parameters and no annotations, additional context would be beneficial.

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?

Despite 0% schema description coverage, the description adds useful meaning by listing each parameter (owner_type, owner_id, namespace, key, value, type) and providing default values for owner_type and type. This compensates well for the missing schema descriptions.

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

Purpose4/5

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

The description clearly states the action ('Create or update') and resource ('metafield on a Shopify resource'), which is specific and distinguishes it from read-only sibling tools like shopify_get_metafields. However, it does not explicitly differentiate from other mutation tools.

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus alternatives such as shopify_get_metafields or shopify_list_metafield_definitions. There is no mention of prerequisites, when-not-to-use, or conditional considerations.

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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