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conekta

Conekta MCP Server

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by conekta

update_customer

Modify customer information in Conekta by updating specific fields like name, email, phone, or custom reference using the customer ID.

Instructions

Update an existing customer. Only provided fields are updated.

Args: customer_id: The Conekta customer ID name: New customer name email: New customer email phone: New customer phone custom_reference: New custom reference

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
customer_idYes
nameNo
emailNo
phoneNo
custom_referenceNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are provided, so the description carries full burden. It states 'Only provided fields are updated' which is useful behavioral context about partial updates. However, it lacks critical information: authentication requirements, rate limits, error conditions, whether the operation is idempotent, or what happens if invalid data is provided. For a mutation tool with zero annotation coverage, this is insufficient.

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?

The description is appropriately sized and front-loaded with the core purpose in the first sentence. The parameter list is organized but could be more integrated. No wasted sentences, though the 'Args:' section formatting is slightly redundant with the schema.

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?

Given this is a mutation tool with no annotations, 5 parameters (1 required), 0% schema coverage, but with an output schema, the description is minimally adequate. It covers the partial update behavior and parameter meanings but lacks important context about authentication, errors, and system behavior. The output schema existence reduces the need to describe return values.

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?

Schema description coverage is 0%, so the description must compensate. It lists all 5 parameters with brief explanations, adding meaning beyond the bare schema. The description clarifies that customer_id identifies the target and other fields represent new values. However, it doesn't explain format constraints (e.g., email validation) or the implications of null values.

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 'Update an existing customer' which specifies the verb (update) and resource (customer). It distinguishes from siblings like create_customer (creation vs. update) and get_customer (read vs. write). However, it doesn't explicitly differentiate from other update tools like update_order or update_subscription beyond the resource name.

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?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing an existing customer_id), when not to use it (e.g., for creating new customers), or compare it to related tools like create_customer or get_customer. The agent must infer usage from the tool name 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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