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attribute_create

Define one or more product attributes by specifying localized names, types, and optional values via a JSON array.

Instructions

Create one or more product attributes.

Parameters

data : JSON array of attribute objects. Each object may include: - name (dict, keyed by language e.g. {"ro": "Culoare", "en": "Color"}) - type (string) attribute type (e.g. "select", "text", "multiselect") - values (array of value objects, each with a localised "name" dict)

Example

'[{"name": {"ro": "Culoare", "en": "Color"}, "type": "select", "values": [{"name": {"ro": "Rosu", "en": "Red"}}, {"name": {"ro": "Albastru", "en": "Blue"}}]}]'

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

No annotations provided, so description carries full burden. It only states 'Create' but does not disclose behavioral traits like permissions, idempotency, error handling, or rate limits.

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?

Description is well-organized with bullet points and a code block example. Each line adds value; no unnecessary content.

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

Completeness4/5

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

Given the presence of an output schema (not shown), the description adequately covers input. However, it lacks details on error cases, validation rules, or constraints (e.g., duplicate attributes).

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?

Input schema only defines 'data' as a string with 0% schema coverage. Description adds detailed structure (JSON array of attribute objects with name, type, values) and a clear example, significantly compensating for the schema gap.

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 'Create one or more product attributes' with a specific verb and resource. It distinguishes itself from sibling tools like attribute_list and attribute_update.

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 explicit guidance on when to use this tool vs alternatives. Does not mention prerequisites, idempotency, or that attribute_list should be used first to check for existing attributes.

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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