Team Skills

from agno.agent import Agent
from agno.models.openai import OpenAIResponses
from agno.skills import Skills, LocalSkills
from agno.team import Team

implementer = Agent(
    name="Implementer",
    role="Write code based on review feedback",
    model=OpenAIResponses(id="gpt-4o"),
)

team = Team(
    name="Code Review Team",
    model=OpenAIResponses(id="gpt-4o"),
    members=[implementer],
    skills=Skills(loaders=[LocalSkills("/path/to/skills")]),
    instructions=[
        "Use your skills to review code, then delegate implementation to the Implementer.",
    ],
)

team.print_response("Review this function and improve it", stream=True)

from pathlib import Path

from agno.agent import Agent
from agno.models.openai import OpenAIResponses
from agno.skills import Skills, LocalSkills
from agno.team import Team

skills_dir = Path(__file__).parent / "sample_skills"

implementer = Agent(
    name="Implementer",
    role="Write code based on the review feedback",
    model=OpenAIResponses(id="gpt-4o"),
    instructions=[
        "You write clean, well-tested Python code.",
        "When given review feedback, produce an improved version of the code.",
    ],
)

review_team = Team(
    name="Code Review Team",
    model=OpenAIResponses(id="gpt-4o"),
    members=[implementer],
    skills=Skills(loaders=[LocalSkills(str(skills_dir))]),
    instructions=[
        "You are a team leader with access to code review skills.",
        "Use your skills to review code, then delegate implementation work to the Implementer.",
    ],
    markdown=True,
    show_members_responses=True,
)

if __name__ == "__main__":
    review_team.print_response(
        "Review this Python code and suggest improvements, "
        "then have the Implementer write the improved version:\n\n"
        "```python\n"
        "def calculate_total(items):\n"
        "    total = 0\n"
        "    for i in range(len(items)):\n"
        "        total = total + items[i]['price'] * items[i]['quantity']\n"
        "    return total\n"
        "```",
        stream=True,
    )