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mq_logout

Disconnect from the Agent-MQ message queue server to end communication sessions between AI coding agents.

Instructions

Disconnect from server

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The handler implementation for the 'mq_logout' tool. It clears the server and token from the configuration.
    server.tool("mq_logout", "Disconnect from server", {}, async () => {
      client.saveConfig({ server: "", token: "" });
      return { content: [{ type: "text", text: JSON.stringify({ status: "ok" }) }] };
    });
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. 'Disconnect from server' implies a state-changing operation that likely terminates a connection, but it doesn't specify whether this is destructive (e.g., clears session data), has side effects (e.g., pending messages might be lost), requires authentication, or what happens on success/failure. For a mutation tool with zero annotation coverage, this is inadequate.

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?

The description is a single, efficient sentence with zero wasted words. It's front-loaded with the core action and target, making it immediately understandable. Every word earns its place.

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?

Given that this is a mutation tool (implied by 'Disconnect') with no annotations and no output schema, the description is incomplete. It doesn't explain what 'disconnect' entails behaviorally (e.g., does it log out a user, close a network connection, or clear cached data?), what the expected outcome is, or potential errors. For a tool that likely changes system state, more context is needed.

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?

The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description doesn't add parameter information, which is appropriate here. A baseline of 4 is applied for zero-parameter tools, as the description doesn't need to compensate for any gaps.

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

Purpose3/5

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

The description 'Disconnect from server' clearly states the action (disconnect) and target (server), which is a specific verb+resource. However, it doesn't differentiate from sibling tools like 'mq_login' beyond the obvious inverse relationship, and 'server' is somewhat vague compared to more specific resources like 'MQ connection' or 'message queue session'.

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?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., must be logged in first via 'mq_login'), post-conditions, or when not to use it (e.g., if already disconnected). The agent must infer usage from the tool name alone.

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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