> ## Documentation Index
> Fetch the complete documentation index at: https://phidatainc-agui.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Loading Skills

> Load skills into agents using LocalSkills and the Skills orchestrator.

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

```python theme={null}
from agno.agent import Agent
from agno.models.openai import OpenAIResponses
from agno.skills import Skills, LocalSkills

# Load skills from a directory
agent = Agent(
    model=OpenAIResponses(id="gpt-5.2"),
    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
```

```python theme={null}
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:

```python theme={null}
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:

```python theme={null}
from agno.skills import Skills, LocalSkills

skills = Skills(loaders=[
    LocalSkills("/path/to/shared-skills"),
    LocalSkills("/path/to/project-skills"),
])
```

<Note>
  If skills from different loaders have the same name, the later loader's skill will overwrite the earlier one.
</Note>

## Agent Tools

When you add skills to an agent, it automatically gets access to these tools:

| Tool                                                                | Description                        |
| ------------------------------------------------------------------- | ---------------------------------- |
| `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

```python theme={null}
from agno.agent import Agent
from agno.models.openai import OpenAIResponses
from agno.skills import Skills, LocalSkills

agent = Agent(
    model=OpenAIResponses(id="gpt-5.2"),
    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:

```python theme={null}
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:

```python theme={null}
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

```python theme={null}
from pathlib import Path
from agno.agent import Agent
from agno.models.openai import OpenAIResponses
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=OpenAIResponses(id="gpt-5.2"),
    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"
    )
```