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create_support_ticket

Destructive

Raise a support ticket with Ankra's support team on the user's behalf - the same request ankra support create files. Use it when the user asks to contact support, report a platform problem to Ankra, or escalate something the platform cannot fix itself; do not use it for work the AI board should track (file_ticket). Write a specific subject and a description with the evidence: what was expected, what happened, when, and which cluster or resource. The ticket reaches the support team and the user receives a confirmation email. Defaults to the session's cluster when none is given.

Input Schema

NameRequiredDescriptionDefault
subjectYesShort summary of the issue (at most 200 characters).
categoryNoThe kind of request (default 'technical').
severityNoHow urgent it is for the user. Omit to let support triage it.
cluster_idNoThe cluster the request concerns (UUID). Defaults to the session's cluster when scoped.
descriptionYesWhat was expected, what happened, when, and the evidence (markdown, at most 10000 characters).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations cover the safety profile (readOnlyHint=false, destructiveHint=true, idempotentHint=false), so the description isn't obliged to restate mutability. It still adds real behavioral context: the ticket reaches the support team, the user receives a confirmation email, and cluster_id defaults to the session's cluster. It does not address whether repeated calls duplicate tickets, which would have made it a 5.

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 action and the when-to-use routing before the drafting advice; every sentence carries information. It is a dense run-on paragraph, so it falls short of a crisp 5, but nothing is filler.

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 mutating, no-output-schema tool, the definition covers recipient, confirmation behavior, routing alternative, defaults, and content expectations — enough to call it correctly. It omits failure/permission behavior, which keeps it below a 5.

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 100%, so baseline would be 3, but the description adds genuine meaning: it specifies what a good subject looks like and enumerates the evidence the description field should contain (expected, actual, when, cluster/resource), plus the cluster_id fallback behavior. That is more than the schema conveys on its own.

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?

States a specific verb and resource ('Raise a support ticket with Ankra's support team on the user's behalf') and even anchors it to the equivalent CLI command ('ankra support create'). It explicitly differentiates from the closest sibling, file_ticket, so an agent can route without opening schemas.

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

Usage Guidelines5/5

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

Provides explicit when-to-use triggers (user asks to contact support, report a platform problem, escalate something the platform cannot fix) and an explicit when-not ('do not use it for work the AI board should track (file_ticket)'). It also prescribes content expectations for the ticket, which is actionable guidance beyond mere routing.

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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