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Update a conversation

update_conversation
DestructiveIdempotent

Change a conversation: its status (open, pending, closed), priority, tags (the full list replaces the old one), unread mark, mode (ai answers or human team), or whether training learns from it. Only the fields you pass change.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeNoai: the AI agent answers the next message; human: the team does.
tagsNoEvery tag the conversation should have.
learnNofalse is "Don't learn from this": Training skips the conversation.
statusNo
unreadNo
priorityNo
conversationIdYesConversation id from list_conversations.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare destructiveHint=true and idempotentHint=true, so the safety bar is partly met. The description still earns credit by disclosing partial-update semantics ('Only the fields you pass change') and the replace-not-append behavior of tags, which is exactly the destructive nuance an agent needs; it says nothing about permissions or return behavior.

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

Conciseness5/5

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

Two sentences, front-loaded with the action and resource, with the field list and the crucial partial-update caveat placed last where it is most needed. No 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 mutation tool with no output schema, no nested objects, and 7 parameters, the description is close to sufficient: it covers partial-update behavior and field semantics. Missing permission requirements and any hint of the response shape keep it from being complete.

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?

With schema description coverage at 57%, the description must compensate, and it does: it supplies the status enum values (open/pending/closed), explains mode in business terms, and clarifies tags as a full replacement. Priority and unread remain undescribed beyond their enums, keeping it short of a 5.

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?

States a specific verb and resource ('Change a conversation') and enumerates exactly which attributes can be changed, which is more precise than the bare title. It does not, however, differentiate itself from overlapping siblings such as assign_conversation, mark_conversation_read, or snooze_conversation, which cover a subset of the same surface.

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

Usage Guidelines3/5

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

Usage is only implied: the field list tells the agent what can be edited but not when to prefer this tool over assign_conversation or mark_conversation_read, nor any preconditions. No when-not guidance or alternatives are named.

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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