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Custom Fields Get By Entity Id

tiendanube_custom_fields_get_by_entity_id
Read-onlyIdempotent

Retrieves the custom field values for a specific Tiendanube entity, such as a product, customer, order, category, or variant, using its ID. Use it to inspect custom metadata for one record.

Instructions

Get the custom field values of one entity instance (e.g. one product). HTTP: GET /{entity}/{entity_id}/custom-fields Required scope: read_products/write_products (categories, products, products/variants) | read_customers/write_customers (customers) | read_orders/write_orders (orders) API version: 2025-03

Input Schema

NameRequiredDescriptionDefault
entityYesEntity whose custom fields are managed (categories | customers | orders | products | products/variants)
fieldsNoComma-separated list of fields to return, to reduce payload size (e.g. 'id,name,variants')
entity_idYesID of the product/customer/order/category/variant
response_formatNoOutput format: 'json' (default, full data) or 'markdown' (human-readable)json

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already declare readOnly/idempotent/non-destructive, so the description's job is the extra context it does provide: required OAuth scopes broken out per entity family and the API version (2025-03). It does not mention rate limits or response/pagination behavior, but the auth requirement is a real addition beyond annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the purpose, then the HTTP route, then scope requirements and API version as separate lines. Four lines with no filler; the scope line is dense but each element is actionable.

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 read-only 4-parameter lookup with full schema coverage and complete annotations, the description supplies exactly the missing operational context: route, per-entity scopes, and API version. No output schema exists, but a keyed lookup's result shape is implied by the purpose statement.

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% and every parameter (entity enum, entity_id, fields, response_format) is already documented in the schema. The description adds no syntax or format detail beyond echoing example entity values, so the baseline of 3 applies.

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?

States a specific verb and resource: 'Get the custom field values of one entity instance', with a concrete example (one product). Combined with the endpoint path it clearly separates this from definition-oriented siblings, though it never names those siblings explicitly.

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

Usage Guidelines3/5

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

The per-entity scope list implies which entity types are readable and under what permissions, but there is no explicit 'use this when…' guidance or a named alternative such as custom_fields_list or custom_field_defs_get. The agent must infer the choice from the name and the endpoint line.

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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