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Classification Create

classification_create

Create a classification to organize support conversations, set AI reply behavior, and assign conversations to team members automatically.

Instructions

Create a classification.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesName of the classification.
colorNoColor index shown in the app.
aiReplyNotrue lets the AI answer conversations of this classification automatically.
promptIdNoPrompt id the AI uses for replies here (see prompt_list).
autoCloseNotrue closes a conversation automatically after the AI replied.
templateIdNoTemplate id used for replies here (see template_list).
descriptionNoWhat kind of conversations belong here; the AI uses it to classify incoming messages.
aiReplyDraftNotrue makes the AI prepare a draft for the team instead of sending its reply.
organizationIdYesThe organization id. Use organization_list to find it.
defaultMemberIdNoMember id these conversations are assigned to by default (see member_list).
sentimentAnalysisNotrue enables sentiment analysis for these conversations.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.3/5.0
Behavior2/5

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

Annotations already declare readOnlyHint=false, idempotentHint=false, destructiveHint=false, so the agent knows this is a non-destructive, non-idempotent write. The description adds nothing on top — no note about validation failures, required prior setup, or what happens on duplicate names — despite being free to do so.

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

Conciseness3/5

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

One sentence with zero waste and the action front-loaded, but it is under-specified rather than genuinely concise; there is no content to be efficient about.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For an 11-parameter creation tool with no output schema, the agent gets almost nothing about the concept of a 'classification', required setup ordering, or failure modes. Annotations cover the safety profile, but the description should do more for a mutation of this surface area.

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% across all 11 parameters, including cross-references (prompt_list, template_list, member_list), so the schema carries the full burden. The description contributes no additional parameter meaning, making the baseline 3 appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose2/5

Does the description clearly state what the tool does and how it differs from similar tools?

"Create a classification" merely restates the tool name and title with no additional scope, field, or resource detail. It does not distinguish this from relatives like classification_update, classification_get, or classification_delete beyond what their names already convey.

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?

There is no when-to-use guidance, no prerequisites (e.g. that organizationId/promptId/templateId must reference existing entities), and no mention of alternatives. The create semantics are inferable from the name alone.

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