cagent examples
Get inspiration from the following agent examples.
```yaml {title="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
```yaml {title="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
```yaml {title="tech-blog-writer.yaml"}
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.