zulip

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stop_typing

Stop the typing indicator in Zulip conversations when work is complete but no message will be sent, preventing unnecessary notifications.

Instructions

Stop the typing indicator in the current conversation. Call this when you've finished working but aren't about to send a message (e.g. before listen(), or if you decided not to reply after all). Note: sending a message (reply/send_message) implicitly clears typing on the client side, so you don't need this before reply().

Returns: Confirmation or error message.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "stop_typing"
  }
}

Input Schema

Name	Required	Description	Default
No arguments

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Apr 15, 2026

TDQS

A4.7/5.0

Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively explains that this tool stops a typing indicator, clarifies that it's not needed before sending messages (which handle it implicitly), and mentions the return value ('Confirmation or error message'). However, it doesn't detail potential side effects, error conditions, or rate limits.

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 front-loaded with the core purpose, followed by usage guidelines and notes, all in four concise sentences. Every sentence adds value without redundancy, making it efficient and well-structured.

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

Completeness5/5

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

Given the tool's low complexity (0 parameters), no annotations, and the presence of an output schema (implied by 'Returns:'), the description is complete. It covers purpose, usage, behavioral context, and return values adequately for this simple tool.

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 tool has 0 parameters with 100% schema description coverage, so the baseline is 4. The description doesn't need to explain parameters, and it correctly notes there are none by omission, maintaining focus on usage context.

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 description clearly states the tool's purpose with a specific verb ('Stop') and resource ('typing indicator in the current conversation'). It distinguishes from siblings like 'typing' (which starts the indicator) and 'reply/send_message' (which implicitly clears typing), making the differentiation explicit.

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?

The description provides explicit guidance on when to use this tool ('when you've finished working but aren't about to send a message'), when not to use it ('you don't need this before reply()'), and alternatives ('sending a message implicitly clears typing'). It includes specific examples like 'before listen()' or 'if you decided not to reply after all'.

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