System Prompts

Agents can have their System Instructions set and customised in a number of flexible ways. The default System Prompt caters or Agent Skills, MCP Server Instructions, AGENTS.md and Shell access.

Template Variables

The following variables are available in System Prompt templates:

Variable	Description	Notes
`{{file:path}}`	Reads and embeds local file contents (errors if file missing)	Must be a relative path (resolved relative to `workspaceRoot`)
`{{file_silent:path}}`	Reads and embeds local file contents (empty if file missing)	Must be a relative path (resolved relative to `workspaceRoot`)
`{{url:https://...}}`	Fetches and embeds content from a URL
`{{serverInstructions}}`	MCP server instructions with available tools	Warning displayed in `/mcp` if Instructions are present and template variable missing
`{{agentSkills}}`	Agent skill manifests with descriptions
`{{workspaceRoot}}`	Current working directory / workspace root	Set by Client in ACP Mode
`{{hostPlatform}}`	Host platform information
`{{pythonVer}}`	Python version
`{{env}}`	Formatted environment block with all environment details
`{{currentDate}}`	Current date in long format

Example {{env}} output:

Environment:
- Workspace root: /home/user/project
- Client: Zed 0.232
- Host platform: Linux-6.6.87.2-microsoft-standard-WSL2

Note on file templates: File paths in {{file:...}} and {{file_silent:...}} must be relative paths. They will be resolved relative to the workspaceRoot at runtime. Absolute paths are not allowed and will raise an error.

Viewing the System Prompt The System Prompt can be inspected with the /system command from fast-agent or the /status system Slash Command in ACP Mode.

The default System Prompt used with fast-agent go or fast-agent-acp is:

Default System Prompt

You are a helpful AI Agent.

{{serverInstructions}}
{{agentSkills}}
{{file_silent:AGENTS.md}}
{{env}}

The current date is {{currentDate}}."""

Using Instructions

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
fast-agent -i 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.

Instructions

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

Instructions Parallel

Read more about the fast-agent command here.