Lab 39.5: Loading and Using Agent Skills

Goal

In this lab, you will create a simple ADK Skill on your file system and configure an agent to use it via the SkillToolset.

Step 1: Create the Project

1. Create a new agent project:

   adk create skills_agent

   Choose the Programmatic (Python script) option.

2. Navigate to the directory:

   cd skills_agent

Step 2: Create the Skill Directory

We need to create the physical structure for our skill.

1. Inside skills_agent, create a directory called skills:

   mkdir skills

2. Inside skills, create a directory for our specific skill:

   mkdir skills/greeting_skill

3. Inside skills/greeting_skill, create the required SKILL.md file:

   touch skills/greeting_skill/SKILL.md

Step 3: Write the Skill Instructions

Open skills/greeting_skill/SKILL.md in your editor and paste the following content. This defines the metadata (how the agent knows when to use it) and the body (the actual instructions).

---
name: greeting_skill
description: A friendly greeting skill that can say hello to a specific person. Use this skill whenever the user asks to be greeted or says hello.
---

# Greeting Skill Instructions

You are now using the Greeting Skill!

Step 1: Read the user's input to see if they provided a name.
Step 2: Respond with a very enthusiastic, friendly greeting using emojis (like 👋 and ✨).
Step 3: If you don't know their name, greet them as "friend".

Step 4: Configure the Agent

Exercise: Open your main agent.py file. Your task is to load the skill from the directory and provide it to the agent.

import pathlib
from google.adk.agents import Agent
from google.adk.skills import load_skill_from_dir
from google.adk.tools.skill_toolset import SkillToolset
from google.adk.code_executors.unsafe_local_code_executor import UnsafeLocalCodeExecutor

# TODO: 1. Load the skill from the directory you created.
# Hint: Use pathlib.Path(__file__).parent / "skills" / "greeting_skill"
greeting_skill = None

# TODO: 2. Create the SkillToolset.
# Pass your loaded skill in a list to the `skills` parameter.
# We must include the code_executor even if we don't have scripts yet.
my_skill_toolset = None

# TODO: 3. Configure the Agent.
# Add your `my_skill_toolset` to the agent's `tools` list.
root_agent = Agent(
    model="gemini-2.5-flash",
    name="skill_user_agent",
    description="An agent that can use specialized skills.",
    # Add tools here
)

(Note: The full implementation is available in the lab-solution.md if you need a hint.)

Step 5: Test the Skill

1. Set up your .env file.
2. Navigate to the parent directory (cd ..) and start the Dev UI:

   adk web skills_agent

3. Interact with the system:
   • Say "Hello there, my name is Alex."
   • You should receive a highly enthusiastic response with emojis, proving the agent loaded and followed the SKILL.md instructions!
4. Examine the Trace View:
   • Look at the trace. You should see the agent making a "tool call" to activate the greeting_skill. This is progressive disclosure in action!

Self-Reflection Questions

• Look at your SKILL.md file. Which part of it is loaded into the agent's context before the user says hello? Which part is loaded after?
• Why do we have to wrap the skill in a SkillToolset before giving it to the agent? (Think about the other things a toolset might manage, like code executors or additional tools).

---

🕵️ Hidden Solution 🕵️

Looking for the solution? Here's a hint (Base64 decode me): L2RvYy1hZGstdHJhaW5pbmcvbW9kdWxlMzkuNS1hZ2VudC1za2lsbHMvbGFiLXNvbHV0aW9u

The direct link is: Lab Solution