Files
agent-framework/python/samples/02-agents/skills/basic_skill/basic_skill.py
T
SergeyMenshykh 4dc35e9bb0 Python: Support Agent Skills (#4210)
* Python: Support Agent Skills

Add FileAgentSkillsProvider, a context provider that discovers and exposes
Agent Skills from filesystem directories following the Agent Skills
specification (https://agentskills.io/) progressive disclosure pattern:
advertise, load, read resources.

Changes:
- FileAgentSkillsProvider - discovers SKILL.md files from configured
  directories, advertises skills via system prompt injection, and provides
  load_skill / read_skill_resource tools for on-demand access.
- Internal helpers for skill discovery, frontmatter parsing, and secure
  resource reading (path traversal / symlink guards).
- Unit tests covering discovery, loading, resource reading, and security
  scenarios.
- Sample (basic_file_skills) demonstrating usage with an expense-report skill.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* Python: Move skills sample to samples/02-agents/basic_skills/

Align sample directory name with .NET equivalent (Agent_Step01_BasicSkills).

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* fix code quality checks

* address pr review comment and code quality check issue

* address pr review comments

* move the sample to the skills folder

* update readme

* reame consts and use types for them

* leverage pathlib for working with files

* refactor the test

* supply schema to functions

* update readme

* update sample name

* address pr review comments

* fix failing lint check

* address failing check

---------

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-02-25 13:02:26 +00:00

89 lines
3.2 KiB
Python

# Copyright (c) Microsoft. All rights reserved.
import asyncio
import os
from pathlib import Path
from agent_framework import Agent, FileAgentSkillsProvider
from agent_framework.azure import AzureOpenAIResponsesClient
from azure.identity import AzureCliCredential
from dotenv import load_dotenv
# Load environment variables from .env file
load_dotenv()
"""
Agent Skills Sample
This sample demonstrates how to use file-based Agent Skills with a FileAgentSkillsProvider.
Agent Skills are modular packages of instructions and resources that extend an agent's
capabilities. They follow the progressive disclosure pattern:
1. Advertise — skill names and descriptions are injected into the system prompt
2. Load — full instructions are loaded on-demand via the load_skill tool
3. Read resources — supplementary files are read via the read_skill_resource tool
This sample includes the expense-report skill:
- Policy-based expense filing with references and assets
"""
async def main() -> None:
"""Run the Agent Skills demo."""
# --- Configuration ---
endpoint = os.environ["AZURE_AI_PROJECT_ENDPOINT"]
deployment = os.environ.get("AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME", "gpt-4o-mini")
# --- 1. Create the chat client ---
client = AzureOpenAIResponsesClient(
project_endpoint=endpoint,
deployment_name=deployment,
credential=AzureCliCredential(),
)
# --- 2. Create the skills provider ---
# Discovers skills from the 'skills' directory and makes them available to the agent
skills_dir = Path(__file__).parent / "skills"
skills_provider = FileAgentSkillsProvider(skill_paths=str(skills_dir))
# --- 3. Create the agent with skills ---
async with Agent(
client=client,
instructions="You are a helpful assistant.",
context_providers=[skills_provider],
) as agent:
# --- Example 1: Expense policy question (loads FAQ resource) ---
print("Example 1: Checking expense policy FAQ")
print("---------------------------------------")
response1 = await agent.run(
"Are tips reimbursable? I left a 25% tip on a taxi ride and want to know if that's covered."
)
print(f"Agent: {response1}\n")
# --- Example 2: Filing an expense report (uses template asset) ---
print("Example 2: Filing an expense report")
print("---------------------------------------")
session = agent.create_session()
response2 = await agent.run(
"I had 3 client dinners and a $1,200 flight last week. "
"Return a draft expense report and ask about any missing details.",
session=session,
)
print(f"Agent: {response2}\n")
if __name__ == "__main__":
asyncio.run(main())
"""
Sample output:
Example 1: Checking expense policy FAQ
---------------------------------------
Agent: Tips up to 20% are reimbursable for meals, taxi/ride-share, and hotel housekeeping.
Since you left a 25% tip, the portion above 20% would require written justification...
Example 2: Filing an expense report
---------------------------------------
Agent: Here's a draft expense report based on what you've told me. I'll need a few more details...
"""