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pachatraining-mcp

pachatraining-mcp

Cancel an enrollment

cancel_enrollment

Cancels a trainee’s session enrollment after confirmation and reports why cancellation fails if the enrollment is already cancelled or the session is completed or cancelled.

Instructions

Cancel one enrollment of a trainee in a session, after the user confirms it. The server asks the user itself: do not ask for a confirmation in the conversation.

An enrollment already cancelled, or in a session completed or cancelled, cannot be cancelled: the result then says why.

Input Schema

NameRequiredDescriptionDefault
as_ofYesToday's date, as an ISO date: it becomes the cancellation date.
reasonYesWhy the enrollment is cancelled.
enrollment_idYesId of the enrollment to cancel.

Output Schema

NameRequiredDescriptionDefault
messageYes
cancelledYes
enrollment_idYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.9/5.0
Behavior4/5

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

Beyond the annotations, it discloses a non-obvious interaction behavior (server-initiated confirmation) and a precondition failure mode that returns an explanatory result, consistent with idempotentHint=false. It does not state whether a cancellation can be reversed or whether the reason is surfaced externally, which limits it to a 4.

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?

Two short sentences, front-loaded with the action and followed by the confirmation-handling instruction, with zero redundant wording. The second paragraph on invalid states is well separated from the core instruction.

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?

For a three-required-parameter mutation with an output schema and full annotation coverage, this is essentially complete: it covers the action, the confirmation protocol, and the failure conditions. Return values need not be explained because an output schema exists.

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 each parameter is already documented in the schema, including that as_of becomes the cancellation date. The description adds no further meaning about the parameters, so the baseline 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?

The description opens with a specific verb and resource: 'Cancel one enrollment of a trainee in a session', which is more precise than the title alone and makes the single-record scope explicit. It does not name or differentiate itself from the nearest sibling (cancelled_enrollments), so an agent must infer that this is the action tool and that one is a listing.

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

Usage Guidelines4/5

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

It clearly states the operating context: act only after user confirmation, but do not solicit that confirmation in conversation since the server handles it. It also documents the conditions under which the call is invalid (already-cancelled enrollment, or a session that is completed or cancelled). It gives no explicit alternative tool for those blocked cases, which keeps it from a 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.