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chatgpt-web

chatgpt-web

by FirstWari
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

stop

Halt an in-progress ChatGPT reply in a chat to prevent unwanted output and regain control of the conversation.

Instructions

Stop the reply currently being generated in a chat.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "chat": "<chat>"
    },
    "name": "stop"
  }
}

Input Schema

NameRequiredDescriptionDefault
chatYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3/5.0
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. It states the core effect—stopping a reply—but does not mention what happens to the partial reply, whether the action is reversible, or any side effects. This is thin for a mutating control operation.

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, front-loaded sentence with no wasted words. It directly states the action and target, which is appropriate for a simple tool.

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?

Despite the tool being simple, the lack of annotations and output schema means the description should provide more behavioral and usage context. It does not explain what happens to the partially generated reply, whether the stop is permanent, or how to identify the right chat. This leaves meaningful gaps for an agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has a single 'chat' string with no description (0% coverage), so the description must compensate for parameter meaning. It only says 'in a chat,' which adds minimal context about the parameter, but it does not clarify the expected format, identifier type, or how the chat is specified.

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?

The description uses a specific verb 'stop' and a specific resource 'the reply currently being generated in a chat,' making the core operation clear. It does not explicitly differentiate from siblings like 'wait' or 'get_reply,' but the action is unambiguous.

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?

The phrase 'currently being generated' implies the tool should only be used mid-generation, which provides some usage context. However, there are no explicit when-to-use/when-not-to-use instructions or references to alternative tools such as 'wait' or 'get_reply.'

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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