> ## Documentation Index
> Fetch the complete documentation index at: https://docs.subverseai.com/llms.txt
> Use this file to discover all available pages before exploring further.
# Background Agent Configuration
> Full configuration reference for Background Agents
## Identity
| Field | Type | Default | Description |
| ------------ | -------- | -------------- | ---------------------------------------------------------------------------------------------------------------------- |
| Name | Text | — (required) | Unique identifier. Lowercase letters, numbers, and underscores only (e.g. `data_processor`). Must start with a letter. |
| Description | Text | `""` | Internal description of what task this agent performs. |
| Architecture | Dropdown | `Prompt Based` | **Prompt Based** uses a system prompt. **Conversational Flow** uses a visual node-based builder. |
| Debug Mode | Toggle | Off | Outputs extra internal logs. Useful when building and testing workflows. |
***
## Agent Settings
| Field | Type | Default | Description |
| ---------------- | --------- | ------------------ | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| Greeting Message | Text | `""` | The initial prompt or task description sent to the agent when it is invoked. |
| Greeting Type | Dropdown | `Prompt` | **Prompt** — agent generates a response based on the context. **Say** — outputs exact text (rarely used for background agents). |
| Who Speaks First | Dropdown | `SubVerseAI Agent` | Keep as **SubVerseAI Agent** so the agent begins processing immediately when triggered. |
| System Prompt | Text area | Empty | The main system prompt. Describe clearly what input the agent receives, what to do with it, and what output to produce. Use the **Refine using AI** button for assistance. |
***
## Large Language Model Preferences
| Field | Type | Default | Description |
| -------------- | -------- | ------------ | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| LLM Model | Dropdown | — (required) | The AI model powering this agent. Choose a capable model for complex tasks. Each model shows its speed and reasoning ratings. |
| Thinking Level | Dropdown | `Default` | Extended reasoning depth. Options: **Default**, **Low**, **Medium**, **High**, **Very High**. For complex tasks like document analysis or data reasoning, use **High** or **Very High**. |
| Max Tokens | Number | None | Maximum tokens the LLM can generate per response. Leave blank to use the model's default. |
| Temperature | Slider | `0.5` | Response creativity. For structured tasks (classification, extraction) use `0.0`–`0.3`. For generative tasks (drafting, summarizing) use `0.5`–`0.8`. |
***
## Session Settings
| Field | Type | Default | Description |
| ------------------------------- | -------- | --------- | ---------------------------------------------------------------------------------------------------------------- |
| Communication Method | Dropdown | `Two Way` | **Two Way** — agent exchanges messages internally as part of its task. **One Way** — agent only produces output. |
| Session Timeout (mins) | Number | None | Minutes after which an idle background task is ended automatically. |
| Remember Customer Interactions | Toggle | Off | Save a summary of this execution to memory when the task completes. |
| Use Customer Interaction Memory | Toggle | Off | Pull past execution summaries into context when this agent is triggered again for the same user or entity. |
***
## Knowledgebase Settings
| Field | Type | Default | Description |
| -------------- | -------- | ------- | ------------------------------------------------------------------------------------------------------------------------------------------- |
| Knowledge Base | Dropdown | None | Attach a Knowledge Base. The agent will search it as part of completing its task. Useful for question-answering or document-grounded tasks. |
***
## Function Settings
| Field | Type | Default | Description |
| ----------------- | ------------ | ------- | --------------------------------------------------------------------------------------------------------- |
| Pre Call Tools | Multi-select | Empty | LLM tools that run before the agent starts its task (e.g. fetch data from an external system). |
| During Call Tools | Multi-select | Empty | Tools the agent can call while executing (e.g. write to a database, call an external API, send an email). |
| Post Call Tools | Multi-select | Empty | LLM tools that run after the task completes (e.g. store results, notify another system). |
***
## Agent Security Settings
| Field | Type | Default | Description |
| ---------------------------- | --------- | ------- | -------------------------------------------------------------------------------------------------------- |
| Allow List (Allowed Callers) | Text area | Empty | Regex patterns for sources allowed to trigger this agent, separated by commas. Leave empty to allow all. |
| Block List (Blocked Callers) | Text area | Empty | Regex patterns for sources that are blocked, separated by commas. Takes priority over Allow List. |
***
## Post Call Data Analysis
After each execution, the agent can automatically analyze the output and extract structured data.
| Field | Type | Description |
| ---------- | ----------- | -------------------------------------------------------------------------------------------------------------------------------------------------- |
| LLM Model | Dropdown | The AI model used to run the post-execution analysis. Can differ from the main agent model. |
| Parameters | Form / JSON | Define the data points to extract from each execution. Switch between **Form** (add parameters one by one) and **JSON** (paste a raw JSON schema). |
**Parameter fields:**
| Field | Description |
| -------------- | --------------------------------------------------------------------- |
| Parameter Name | The key name for this data point (e.g. `task_completion`, `summary`). |
| Details | Description of what this parameter represents and how to extract it. |
| Type | Data type: `string`, `boolean`, `number`, etc. |
| Required | Whether this parameter must be present in every analysis output. |