Skip to main content
Skills are loaded using the Skills class with one or more SkillLoader instances set as loaders. Currently, LocalSkills is available for loading skills from the filesystem.

​
Basic Usage

from agno.agent import Agent
from agno.models.openai import OpenAIChat
from agno.skills import Skills, LocalSkills

# Load skills from a directory
agent = Agent(
    model=OpenAIChat(id="gpt-4o"),
    skills=Skills(loaders=[LocalSkills("/path/to/skills")])
)

​
LocalSkills Loader

The LocalSkills loader reads skills from the local filesystem.

​
Loading from a Directory of Skills

If you have multiple skills in subdirectories: 
skills/
├── code-review/
│   └── SKILL.md
├── git-workflow/
│   └── SKILL.md
└── testing/
    └── SKILL.md

from agno.skills import Skills, LocalSkills

# Load all skills from the directory
skills = Skills(loaders=[LocalSkills("/path/to/skills")])

​
Loading a Single Skill

If you want to load just one skill: 
from agno.skills import Skills, LocalSkills

# Load a single skill directory
skills = Skills(loaders=[LocalSkills("/path/to/skills/code-review")])

​
Multiple Loaders

You can combine multiple loaders to load skills from different locations: 
from agno.skills import Skills, LocalSkills

skills = Skills(loaders=[
    LocalSkills("/path/to/shared-skills"),
    LocalSkills("/path/to/project-skills"),
])
If skills from different loaders have the same name, the later loader’s skill will overwrite the earlier one.

​
Agent Tools

When you add skills to an agent, it automatically gets access to these tools:
ToolDescription
get_skill_instructions(skill_name)Load full instructions for a skill
get_skill_reference(skill_name, reference_path)Load a reference document
get_skill_script(skill_name, script_path, execute, args, timeout)Read or execute a script

​
Example: Using Skill Tools

from agno.agent import Agent
from agno.models.openai import OpenAIChat
from agno.skills import Skills, LocalSkills

agent = Agent(
    model=OpenAIChat(id="gpt-4o"),
    skills=Skills(loaders=[LocalSkills("/path/to/skills")]),
    instructions=[
        "You have access to specialized skills.",
        "Use get_skill_instructions to load full guidance when needed.",
    ],
)

# The agent will automatically use skills when relevant
agent.print_response("Review this code for best practices: def foo(): pass")

​
System Prompt Integration

Skills metadata is automatically added to the agent’s system prompt. The agent sees:
  • Skill names and descriptions
  • Available scripts and references
  • Instructions on how to load full skill details
This allows the agent to discover and use skills without loading everything upfront.

​
Reloading Skills

If your skills change at runtime, you can reload them: 
from agno.skills import Skills, LocalSkills

skills = Skills(loaders=[LocalSkills("/path/to/skills")])

# ... skills are modified on disk ...

# Reload to pick up changes
skills.reload()

​
Error Handling

Skills are validated when loaded. If validation fails, a SkillValidationError is raised: 
from agno.skills import Skills, LocalSkills, SkillValidationError

try:
    skills = Skills(loaders=[LocalSkills("/path/to/skills")])
except SkillValidationError as e:
    print(f"Skill validation failed: {e}")
    print(f"Errors: {e.errors}")

​
Complete Example

from pathlib import Path
from agno.agent import Agent
from agno.models.openai import OpenAIChat
from agno.skills import Skills, LocalSkills

# Get skills directory relative to this file
skills_dir = Path(__file__).parent / "skills"

# Create agent with skills
agent = Agent(
    name="Code Assistant",
    model=OpenAIChat(id="gpt-4o"),
    skills=Skills(loaders=[LocalSkills(str(skills_dir))]),
    instructions=[
        "You are a helpful coding assistant with access to specialized skills."
    ],
    markdown=True,
)

if __name__ == "__main__":
    agent.print_response(
        "Review this Python function:\n\n"
        "def calc(x,y): return x+y"
    )