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Give a thread back to the queue

unassign_conversation

Takes the name off a thread: nobody is handling it, and it goes back to the queue for whoever picks it up. It closes no door, the thread having been readable by everybody working that queue the whole time. Replayed on a thread nobody had taken, it answers the same thing. To give several threads back to the queue, give conversation_id the list of their ids, in ONE call rather than one call per thread: the answer then lists in "results" the outcome of each thread in the order given ("ok", with its "result" or its "error") and counts "succeeded" and "failed". Each thread passes exactly the checks it would alone, so one refused or out of reach ("not found") leaves the others done, and the call is an error only when none succeeded.

Input Schema

NameRequiredDescriptionDefault
conversation_idYesThe id of the conversation, as list_conversations gives it, or a list of up to 50 ids to do the same to every one of them in a single call.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior5/5

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

With no annotations, the description carries the full burden and does well: it discloses idempotent replay ('answers the same thing'), non-destructive visibility ('closes no door'), batch partial-failure semantics, and when the call is an error. It lacks only secondary details like permission requirements or notification effects.

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?

Purpose is front-loaded in the first sentence. Every later sentence adds behavioral or batch information, though the prose is indirect and ornate ('closes no door', 'the thread having been readable...') rather than tightly written.

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 one-parameter mutation with no annotations and no output schema, the description covers the important batch return/error behavior and idempotency. It does not fully describe the single-conversation success response or permission requirements, so it is strong but not 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?

Schema coverage is 100%, so the baseline is 3; the description goes further by explaining that conversation_id may be a list and what the list response looks like (results order, succeeded/failed counts). It does not add id format details beyond what the schema already says.

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?

The first sentence states a specific action on a specific resource ('takes the name off a thread') and its immediate consequence (returns to the queue). It implicitly contrasts with assign_conversation and delete_conversation by describing unassignment and saying no door is closed.

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?

It explains batch usage ('give conversation_id the list... ONE call rather than one call per thread') but does not explicitly say when to choose this over assign_conversation or set_conversation_status, nor list prerequisites. Usage is implied by the effect rather than stated as a decision rule.

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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