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conekta

Conekta MCP Server

Official
by conekta

cancel_subscription

Cancel a subscription in Conekta by providing customer and subscription IDs. This tool stops recurring payments and ends subscription services.

Instructions

Cancel a subscription.

Args: customer_id: The Conekta customer ID subscription_id: The subscription ID to cancel

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
customer_idYes
subscription_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
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. It states the action is 'cancel' but doesn't clarify if this is reversible, requires specific permissions, triggers notifications, affects billing, or has rate limits. For a destructive operation with zero annotation coverage, this leaves critical behavioral traits undocumented.

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 concise with a clear title phrase followed by parameter listings. Every sentence serves a purpose: the first states the action, and the Args section documents parameters. However, the structure could be more front-loaded by integrating parameter context into the main description rather than a separate section.

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 destructive operation with no annotations, 0% schema coverage, but an output schema exists, the description is minimally adequate. The output schema likely covers return values, reducing the need for that in the description. However, for a subscription cancellation tool, it should address behavioral aspects like permanence, billing implications, and error conditions more thoroughly.

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 0%, so the schema provides no parameter documentation. The description adds basic semantics by identifying parameters as 'customer_id' and 'subscription_id', but doesn't explain format (e.g., UUID), sourcing (where to find these IDs), or validation rules. It partially compensates for the schema gap but leaves important details unspecified.

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 ('Cancel') and resource ('a subscription'), making the purpose immediately understandable. It distinguishes this from siblings like 'pause_subscription' and 'resume_subscription' by specifying termination rather than temporary suspension. However, it doesn't explicitly contrast with 'cancel_order' or 'cancel_checkout', leaving some sibling differentiation incomplete.

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 like 'pause_subscription' or 'cancel_order'. It doesn't mention prerequisites (e.g., subscription must be active), consequences (e.g., immediate termination vs. end of billing period), or recovery options. The agent must infer usage from context 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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