> ## Documentation Index
> Fetch the complete documentation index at: https://docs-v1.agno.com/llms.txt
> Use this file to discover all available pages before exploring further.
# Prompts
We prompt Agents using `description` and `instructions` and a number of other settings. These settings are used to build the **system** message that is sent to the language model.
Understanding how these prompts are created will help you build better Agents.
The 2 key parameters are:
1. **Description**: A description that guides the overall behaviour of the agent.
2. **Instructions**: A list of precise, task-specific instructions on how to achieve its goal.
Description and instructions only provide a formatting benefit, we do not alter or abstract any information and you can always set the `system_message` to provide your own system prompt.
## System message
The system message is created using `description`, `instructions` and a number of other settings. The `description` is added to the start of the system message and `instructions` are added as a list after `Instructions`. For example:
```python instructions.py theme={null}
from agno.agent import Agent
agent = Agent(
description="You are a famous short story writer asked to write for a magazine",
instructions=["You are a pilot on a plane flying from Hawaii to Japan."],
markdown=True,
debug_mode=True,
)
agent.print_response("Tell me a 2 sentence horror story.", stream=True)
```
Will translate to (set `debug_mode=True` to view the logs):
```js theme={null}
DEBUG ============== system ==============
DEBUG You are a famous short story writer asked to write for a magazine
## Instructions
- You are a pilot on a plane flying from Hawaii to Japan.
- Use markdown to format your answers.
DEBUG ============== user ==============
DEBUG Tell me a 2 sentence horror story.
DEBUG ============== assistant ==============
DEBUG As the autopilot disengaged inexplicably mid-flight over the Pacific, the pilot glanced at the copilot's seat
only to find it empty despite his every recall of a full crew boarding. Hands trembling, he looked into the
cockpit's rearview mirror and found his own reflection grinning back with blood-red eyes, whispering,
"There's no escape, not at 30,000 feet."
DEBUG **************** METRICS START ****************
DEBUG * Time to first token: 0.4518s
DEBUG * Time to generate response: 1.2594s
DEBUG * Tokens per second: 63.5243 tokens/s
DEBUG * Input tokens: 59
DEBUG * Output tokens: 80
DEBUG * Total tokens: 139
DEBUG * Prompt tokens details: {'cached_tokens': 0}
DEBUG * Completion tokens details: {'reasoning_tokens': 0}
DEBUG **************** METRICS END ******************
```
## Set the system message directly
You can manually set the system message using the `system_message` parameter.
```python theme={null}
from agno.agent import Agent
agent = Agent(system_message="Share a 2 sentence story about")
agent.print_response("Love in the year 12000.")
```
Some models via some model providers, like `llama-3.2-11b-vision-preview` on Groq, require no system message with other messages. To remove the system message, set `create_default_system_message=False` and `system_message=None`. Additionally, if `markdown=True` is set, it will add a system message, so either remove it or explicitly disable the system message.
## User message
The input `message` sent to the `Agent.run()` or `Agent.print_response()` functions is used as the user message.
## Default system message
The Agent creates a default system message that can be customized using the following parameters:
| Parameter | Type | Default | Description |
| ------------------------------- | ----------- | -------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `description` | `str` | `None` | A description of the Agent that is added to the start of the system message. |
| `goal` | `str` | `None` | Describe the task the agent should achieve. |
| `instructions` | `List[str]` | `None` | List of instructions added to the system prompt in `` tags. Default instructions are also created depending on values for `markdown`, `output_model` etc. |
| `additional_context` | `str` | `None` | Additional context added to the end of the system message. |
| `expected_output` | `str` | `None` | Provide the expected output from the Agent. This is added to the end of the system message. |
| `markdown` | `bool` | `False` | Add an instruction to format the output using markdown. |
| `add_datetime_to_instructions` | `bool` | `False` | If True, add the current datetime to the prompt to give the agent a sense of time. This allows for relative times like "tomorrow" to be used in the prompt |
| `system_message` | `str` | `None` | System prompt: provide the system prompt as a string |
| `system_message_role` | `str` | `system` | Role for the system message. |
| `create_default_system_message` | `bool` | `True` | If True, build a default system prompt using agent settings and use that. |
Disable the default system message by setting `create_default_system_message=False`.
## Default user message
The Agent creates a default user message, which is either the input message or a message with the `context` if `enable_rag=True`. The default user message can be customized using:
| Parameter | Type | Default | Description |
| ----------------------------- | ------------------------- | -------- | ---------------------------------------------------------------------------------------------------------------------------- |
| `context` | `str` | `None` | Additional context added to the end of the user message. |
| `add_context` | `bool` | `False` | If True, add the context to the user prompt. |
| `resolve_context` | `bool` | `True` | If True, resolve the context (i.e. call any functions in the context) before adding it to the user prompt. |
| `add_references` | `bool` | `False` | Enable RAG by adding references from the knowledge base to the prompt. |
| `retriever` | `Callable` | `None` | Function to get references to add to the user\_message. This function, if provided, is called when `add_references` is True. |
| `references_format` | `Literal["json", "yaml"]` | `"json"` | Format of the references. |
| `add_history_to_messages` | `bool` | `False` | If true, adds the chat history to the messages sent to the Model. |
| `num_history_responses` | `int` | `3` | Number of historical responses to add to the messages. |
| `user_message` | `Union[List, Dict, str]` | `None` | Provide the user prompt as a string. Note: this will ignore the message sent to the run function. |
| `user_message_role` | `str` | `user` | Role for the user message. |
| `create_default_user_message` | `bool` | `True` | If True, build a default user prompt using references and chat history. |
Disable the default user message by setting `create_default_user_message=False`.