Instructions

Agents can have their System Instructions set in a number of flexible ways to make building useful .

When defining an Agent, you can load the instruction as either a String, Path or AnyUrl.

Instructions support embedding the current date, as well as content from other URLs. This is really helpful if you want to refer to files on GitHub, or assemble useful prompts/content in Gists etc.

Simple String

@fast.agent(name="example",
    instruction="""
You are a helpful AI Agent.
""")

With current date

@fast.agent(name="example",
    instruction="""
You are a helpful AI Agent. 
Your reliable knowledge cut-off date is December 2024. 
Todays date is {{currentDate}}.
""")

Will produce: You are a helpful AI Agent. Your reliable knowledge cut-off date is December 2024. Todays date is 25 July 2025.

With URL

@fast.agent(name="mcp-expert",
    instruction="""
You are have expert knowledge of the 
MCP (Model Context Protocol) schema.

{{url:https://raw.githubusercontent.com/modelcontextprotocol/modelcontextprotocol/refs/heads/main/schema/2025-06-18/schema.ts}}

Answer any questions about the protocol by referring
to and quoting the schema where necessary.
""")

You can store the prompt in an external file for easy editing - including template variables:

From file

from pathlib import Path

@fast.agent(name="mcp-expert",
    instruction=Path("./mcp-expert.md"))
""")

mcp-expert.md

You are have expert knowledge of the MCP (Model Context Protocol) schema.

{{url:https://raw.githubusercontent.com/modelcontextprotocol/modelcontextprotocol/refs/heads/main/schema/2025-06-18/schema.ts}}

Answer any questions about the protocol by referring to and quoting the schema where necessary.
Your knowledge cut-off is December 2024, todays date is {{currentDate}}

Or you can load the prompt directly from a URL:

From URL

from pydantic import AnyUrl

@fast.agent(name="mcp-expert",
    instruction=AnyUrl("https://gist.githubusercontent.com/evalstate/d432921aaaee2c305cf46ae320840360/raw/eb9c7ff93adc780171bfb0ae2560be2178304f16/gistfile1.txt"))

# --> fast-agent system prompt demo

You can start an agent with instructions from a file using the fast-agent commmand:

fast-agent --instructions=mcp-expert.md

This can be combined with other options to specify model and available servers:

fast-agent -i mcp-expert.md --model sonnet --url https://hf.co/mcp

Starts an interactive agent session, with the MCP Schema loaded, attached to Sonnet with the Hugging Face MCP Server.

You can even specify multiple models to directly compare their outputs:

Read more about the fast-agent command here.