cagent examples
Table of contents
Get inspiration from the following agent examples.
Agentic development team
dev-team.yaml
agents:
root:
model: claude
description: Technical lead coordinating development
instruction: |
You are a technical lead managing a development team.
Coordinate tasks between developers and ensure quality.
sub_agents: [developer, reviewer, tester]
developer:
model: claude
description: Expert software developer
instruction: |
You are an expert developer. Write clean, efficient code
and follow best practices.
toolsets:
- type: filesystem
- type: shell
- type: think
reviewer:
model: gpt4
description: Code review specialist
instruction: |
You are a code review expert. Focus on code quality,
security, and maintainability.
toolsets:
- type: filesystem
tester:
model: gpt4
description: Quality assurance engineer
instruction: |
You are a QA engineer. Write tests and ensure
software quality.
toolsets:
- type: shell
- type: todo
models:
gpt4:
provider: openai
model: gpt-4o
claude:
provider: anthropic
model: claude-sonnet-4-0
max_tokens: 64000
Research assistant
research-assistant.yaml
agents:
root:
model: claude
description: Research assistant with web access
instruction: |
You are a research assistant. Help users find information,
analyze data, and provide insights.
toolsets:
- type: mcp
command: mcp-web-search
args: ["--provider", "duckduckgo"]
- type: todo
- type: memory
path: "./research_memory.db"
models:
claude:
provider: anthropic
model: claude-sonnet-4-0
max_tokens: 64000
Technical blog writer
tech-blog-writer.yaml
#!/usr/bin/env cagent run
version: "1"
agents:
root:
model: anthropic
description: Writes technical blog posts
instruction: |
You are the leader of a team of AI agents for a technical blog writing workflow.
Here are the members in your team:
<team_members>
- web_search_agent: Searches the web
- writer: Writes a 750-word technical blog post based on the chosen prompt
</team_members>
<WORKFLOW>
1. Call the `web_search_agent` agent to search the web to get
important information about the task that is asked
2. Call the `writer` agent to write a 750-word technical blog
post based on the research done by the web_search_agent
</WORKFLOW>
- Use the transfer_to_agent tool to call the right agent at the right
time to complete the workflow.
- DO NOT transfer to multiple members at once
- ONLY CALL ONE AGENT AT A TIME
- When using the `transfer_to_agent` tool, make exactly one call
and wait for the result before making another. Do not batch or
parallelize tool calls.
sub_agents:
- web_search_agent
- writer
toolsets:
- type: think
web_search_agent:
model: anthropic
add_date: true
description: Search the web for information
instruction: |
Search the web for information
Always include sources
toolsets:
- type: mcp
command: uvx
args: ["duckduckgo-mcp-server"]
writer:
model: anthropic
description: Writes a 750-word technical blog post based on the chosen prompt.
instruction: |
You are an agent that receives a single technical writing prompt
and generates a detailed, informative, and well-structured technical blog post.
- Ensure the content is technically accurate and includes relevant
code examples, diagrams, or technical explanations where appropriate.
- Structure the blog post with clear sections, including an introduction,
main content, and conclusion.
- Use technical terminology appropriately and explain complex concepts clearly.
- Include practical examples and real-world applications where relevant.
- Make sure the content is engaging for a technical audience while
maintaining professional standards.
Constraints:
- DO NOT use lists
models:
anthropic:
provider: anthropic
model: claude-3-5-sonnet-latest
See more examples in the repository.