Agent Templates

Agent Templates#

Agent templates define reusable agent configurations using Markdown with YAML frontmatter.

Location#

Agent templates are stored in .pantheon/agents/:

.pantheon/
└── agents/
    ├── assistant.md
    ├── developer.md
    └── researcher.md

Template Format#

Basic Structure#

---
name: My Agent
model: openai/gpt-4o
icon: 🤖
---

# Instructions

You are a helpful assistant.

## Your Responsibilities
- Help users with their tasks
- Be concise and accurate

Frontmatter Fields#

Field	Required	Description
`name`	Yes	Display name for the agent
`model`	No	Model to use (e.g., `openai/gpt-4o`, `anthropic/claude-3-opus`)
`icon`	No	Emoji icon for display
`toolsets`	No	List of toolsets to enable
`mcp_servers`	No	List of MCP servers to connect
`temperature`	No	Model temperature (0.0-2.0)
`max_tokens`	No	Maximum response tokens

Instructions Section#

The markdown content after the frontmatter becomes the agent’s system instructions.

Use clear, structured instructions:

---
name: Code Reviewer
model: openai/gpt-4o
---

You are an expert code reviewer.

## Your Role
Review code for:
- Correctness and bugs
- Performance issues
- Security vulnerabilities
- Code style and best practices

## Review Format
For each issue found:
1. Describe the problem
2. Explain why it's an issue
3. Suggest a fix

## Guidelines
- Be constructive, not critical
- Prioritize important issues
- Acknowledge good patterns

Examples#

Developer Agent#

---
name: Developer
model: openai/gpt-4o
icon: 👨‍💻
toolsets:
  - file_manager
  - shell
  - python_interpreter
---

You are an expert software developer.

## Capabilities
- Write clean, well-documented code
- Debug and fix issues
- Refactor for better design

## Guidelines
- Follow project conventions
- Write tests for new features
- Keep changes minimal and focused

Research Agent#

---
name: Researcher
model: openai/gpt-4o
icon: 🔍
toolsets:
  - web_browse
  - file_manager
---

You are a research assistant.

## Your Role
- Search for information
- Summarize findings
- Cite sources

## Output Format
Present findings with:
- Key points summary
- Detailed analysis
- Source references

Data Analyst#

---
name: Data Analyst
model: openai/gpt-4o
icon: 📊
toolsets:
  - python_interpreter
  - notebook
  - file_manager
---

You are a data analysis expert.

## Capabilities
- Data cleaning and transformation
- Statistical analysis
- Visualization creation

## Tools
Use pandas, numpy, matplotlib, seaborn for analysis.

Using Toolsets#

Enable built-in toolsets:

toolsets:
  - file_manager      # File read/write/search
  - shell             # Shell command execution
  - python_interpreter # Python code execution
  - notebook          # Jupyter notebook operations
  - web_browse        # Web search and fetch

Using MCP Servers#

Connect to MCP servers defined in mcp.json:

mcp_servers:
  - filesystem        # Server name from mcp.json
  - github

Using Prompt Snippets#

Reference reusable prompts with {{snippet_name}}:

---
name: Worker
model: openai/gpt-4o
---

You are a task worker.

{{work_strategy}}

{{output_format}}

The snippets are loaded from .pantheon/prompts/work_strategy and .pantheon/prompts/output_format.

Usage#

REPL:

pantheon cli --template developer

ChatRoom:

pantheon ui --auto-start-nats --auto-ui --template developer

Python API:

from pantheon.factory import load_agent

agent = load_agent("developer")
response = await agent.run("Help me write a function")

Best Practices#

Clear Role Definition: Start with a clear statement of who the agent is
Specific Guidelines: Provide concrete guidelines for behavior
Output Format: Specify expected output format when relevant
Minimal Toolsets: Only include toolsets the agent actually needs
Structured Markdown: Use headers and lists for readability