> ## Documentation Index > Fetch the complete documentation index at: https://docs.monobot.ai/llms.txt > Use this file to discover all available pages before exploring further. # General The **General** tab allows you to configure the core settings of your AI agent, including identity, behavior, and default interaction parameters. General Settings Tab ## Basic Settings * **Agent Title**: Defines the name of your AI agent as it appears across the platform and in interactions. * **Organization**: Assigns the agent to a specific organization for management, billing, and access control. ## Location & Contact Settings * **Timezone**: Sets the default timezone used for all date and time-related operations (e.g., scheduling, timestamps, availability). * **Phone Number**: Assigns a phone number to enable voice interactions and call handling for the agent. ## Large Language Model Settings Large Language Model Settings allow you to configure how the agent generates responses, reasons through tasks, and communicates with users. * **Large Language Model**: Selects the AI model that powers the agent’s responses and reasoning capabilities. * **API Version**: Defines which API version is used for LLM requests. This can affect supported parameters, response behavior, and available model features. * **Temperature**: Adjusts response creativity. Higher values make responses more creative and varied, while lower values make responses more consistent and deterministic. * **Reasoning Effort**: Controls how much reasoning the model applies before generating a response. Higher effort can improve complex task handling but may increase response time and cost. * **Verbosity**: Controls how detailed the model’s responses should be. Lower values produce shorter answers, while higher values generate more expanded and detailed responses. * **Web Search**: Enables or disables web search capability for the model, when supported. This allows the agent to retrieve fresh or external information during conversations. ## Welcome Message * **Welcome Message**: Defines the first message users see when starting an interaction with the agent. ## Prompt Instruction * **Prompt Instruction**: Defines the core behavior, personality, and rules of the AI agent. * Controls how the agent communicates, what it is allowed to do, and how it handles different scenarios. * Used to enforce constraints (e.g., no hallucination, use only provided data). * Guides data collection, conversation flow, and response style. ### Dynamic Variables (@) You can use **dynamic variables** inside the prompt by typing `@` and selecting from the available options. These variables allow you to inject real-time data into the prompt. Examples of commonly used variables: * **@Full Date**: Inserts the current date. * **@Time 12-hour**: Inserts the current time in 12-hour format. * **@Time 24-hour**: Inserts the current time in 24-hour format. * **@Current Day of Week**: Inserts the current weekday. * **@Next Day of Week**: Inserts the next weekday relative to the current date. * **@Conversation Type**: Provides the current interaction type (Chat, Call). * **@Timezone**: Returns the configured timezone. * **@Language**: Returns the current conversation language. * **@Language Code**: Returns the language code of the current language. * **@Flow Prompt**: Inserts the prompt configured for the current flow. * **@Category Prompt**: Inserts the prompt configured for the selected category. * **@If Statement**: Inserts a conditional expression for dynamic content rendering. These variables help make the agent more context-aware and enable dynamic, time-sensitive behavior. *** ## Notes * The **Prompt Instruction** is the most important setting and directly impacts agent performance. * The **Temperature** setting should be lower for structured tasks (e.g., booking) and higher for creative conversations. * Dynamic variables (`@`) should be used when the agent needs real-time context (e.g., date, time, or interaction type). * Ensure the **Timezone** is correctly set to avoid issues with scheduling and time-based logic. This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.