> ## Documentation Index
> Fetch the complete documentation index at: https://docs.openhands.dev/llms.txt
> Use this file to discover all available pages before exploring further.

# Agent Skills & Context

> Skills add specialized behaviors, domain knowledge, and context-aware triggers to your agent through structured prompts.

export const path_to_script_3 = "examples/05_skills_and_plugins/01_loading_agentskills/main.py"

export const path_to_script_2 = "examples/01_standalone_sdk/03_activate_skill.py"

export const path_to_script_1 = "examples/01_standalone_sdk/43_mixed_marketplace_skills/main.py"

export const path_to_script_0 = "examples/05_skills_and_plugins/03_managing_installed_skills/main.py"

This guide shows how to implement skills in the SDK. For conceptual overview, see [Skills Overview](/overview/skills).

OpenHands supports an **extended version** of the [AgentSkills standard](https://agentskills.io/specification) with optional keyword triggers.

## Skill Injection Behavior

Understanding where skill content appears in the prompt is critical. The behavior differs based on skill format and trigger configuration:

| Skill Format                 | Trigger      | Where Content Appears                                                                                   | Model Mediated?                      |
| ---------------------------- | ------------ | ------------------------------------------------------------------------------------------------------- | ------------------------------------ |
| **AgentSkills** (`SKILL.md`) | Any          | `<available_skills>` (description only)                                                                 | ✅ Yes — agent calls `invoke_skill()` |
| **AgentSkills** (`SKILL.md`) | Has triggers | `<available_skills>` + auto-inject on match                                                             | ✅ Yes                                |
| **Legacy** (inline/`*.md`)   | `None`       | **`<REPO_CONTEXT>` (full content in the initial system prompt; included in LLM context for each turn)** | ❌ No                                 |
| **Legacy** (inline/`*.md`)   | Has triggers | `<available_skills>` + auto-inject on match                                                             | ✅ Yes                                |

<Warning>
  **Token Usage Warning**: Legacy skills with `trigger=None` add their **full content** to `<REPO_CONTEXT>` in the initial `SystemPromptEvent`. That system message remains part of the conversation context for subsequent LLM calls, so the content still affects token usage on each turn. Consider using AgentSkills format (`SKILL.md`) for progressive disclosure instead.
</Warning>

### Prompt Structure

Skills appear in different parts of the system prompt:

```xml icon="file" theme={null}
<!-- System Prompt Structure -->

<REPO_CONTEXT>
  <!-- Legacy trigger=None skills: FULL content in the initial system prompt;
       included in LLM context for each turn while retained in history -->
  [BEGIN context from [agents]]
  ... AGENTS.md content ...
  [END Context]
</REPO_CONTEXT>

<SKILLS>
  <available_skills>
    <!-- AgentSkills + legacy with triggers: description only -->
    <skill>
      <name>github</name>
      <description>Interact with GitHub...</description>
    </skill>
  </available_skills>
</SKILLS>
```

When a trigger matches, content is injected into the **user message**:

```xml icon="file" theme={null}
<EXTRA_INFO>
The following information has been included based on a keyword match for "github".
Skill location: /path/to/skill
... skill content ...
</EXTRA_INFO>
```

## Context Loading Methods

| Method                     | When Content Loads    | Use Case                            |
| -------------------------- | --------------------- | ----------------------------------- |
| **Always-loaded**          | At conversation start | Repository rules, coding standards  |
| **Trigger-loaded**         | When keywords match   | Specialized tasks, domain knowledge |
| **Progressive disclosure** | Agent reads on demand | Large reference docs (AgentSkills)  |

## Always-Loaded Context

Content that's always in the system prompt.

### Option 1: `AGENTS.md` (Auto-loaded)

Place `AGENTS.md` at your repo root - it's loaded automatically. See [Permanent Context](/overview/skills/repo).

```python icon="python" focus={3, 4} theme={null}
from openhands.sdk.context.skills import load_project_skills

# Automatically finds AGENTS.md, CLAUDE.md, GEMINI.md at workspace root
skills = load_project_skills(workspace_dir="/path/to/repo")
agent_context = AgentContext(skills=skills)
```

### Option 2: Inline Skill (Code-defined)

```python icon="python" focus={5-11} theme={null}
from openhands.sdk import AgentContext
from openhands.sdk.context import Skill

agent_context = AgentContext(
    skills=[
        Skill(
            name="code-style",
            content="Always use type hints in Python.",
            trigger=None,  # No trigger = always loaded
        ),
    ]
)
```

<Warning>
  **Important**: Inline skills with `trigger=None` use **legacy format** behavior — full content is added to `<REPO_CONTEXT>` in the initial system prompt and remains part of the conversation context for subsequent LLM calls. For large skills, consider using the AgentSkills `SKILL.md` format for progressive disclosure.
</Warning>

## Trigger-Loaded Context

Content injected when keywords appear in user messages. See [Keyword-Triggered Skills](/overview/skills/keyword).

```python icon="python" focus={6} theme={null}
from openhands.sdk.context import Skill, KeywordTrigger

Skill(
    name="encryption-helper",
    content="Use the encrypt.sh script to encrypt messages.",
    trigger=KeywordTrigger(keywords=["encrypt", "decrypt"]),
)
```

When user says "encrypt this", the content is injected into the message:

```xml icon="file" theme={null}
<EXTRA_INFO>
The following information has been included based on a keyword match for "encrypt".
Skill location: /path/to/encryption-helper

Use the encrypt.sh script to encrypt messages.
</EXTRA_INFO>
```

## Progressive Disclosure (AgentSkills Standard)

For the agent to trigger skills, use the [AgentSkills standard](https://agentskills.io/specification) `SKILL.md` format. The agent sees a summary and reads full content on demand.

```python icon="python" theme={null}
from openhands.sdk.context.skills import load_skills_from_dir

# Load SKILL.md files from a directory
_, _, agent_skills = load_skills_from_dir("/path/to/skills")
agent_context = AgentContext(skills=list(agent_skills.values()))
```

Skills are listed in the system prompt:

```xml icon="file" theme={null}
<available_skills>
  <skill>
    <name>code-style</name>
    <description>Project coding standards.</description>
    <location>/path/to/code-style/SKILL.md</location>
  </skill>
</available_skills>
```

<Tip>
  Add `triggers` to a SKILL.md for **both** progressive disclosure AND automatic injection when keywords match.
</Tip>

## Managing Installed Skills

You can install AgentSkills into a persistent directory and manage them through
`openhands.sdk.skills`. Skills are stored under
`~/.openhands/skills/installed/` with a `.installed.json` metadata file that
records an `enabled` flag. `list_installed_skills()` returns all installed
skills, while `load_installed_skills()` returns only those with
`enabled=true`.

The public lifecycle API includes `install_skill()`, `update_skill()`,
`enable_skill()`, `disable_skill()`, and `uninstall_skill()`, which gives the
CLI a clean SDK surface for `/skill install`, `/skill enable`,
`/skill disable`, and `/skill uninstall`.

### Installed Skill Lifecycle Example

This example mirrors the installed-plugin lifecycle example, but for
AgentSkills. It installs sample skills, lists them, toggles the
persistent `enabled` flag, and uninstalls one skill while leaving the
other available.

<Note>
  Source: [examples/05\_skills\_and\_plugins/03\_managing\_installed\_skills/main.py](https://github.com/OpenHands/software-agent-sdk/blob/main/examples/05_skills_and_plugins/03_managing_installed_skills/main.py)
</Note>

```python icon="python" expandable examples/05_skills_and_plugins/03_managing_installed_skills/main.py theme={null}
"""Example: Installing and Managing Skills

This example demonstrates installed skill lifecycle operations in the SDK:

1. Install skills from local paths into persistent storage
2. List tracked skills and load only the enabled ones
3. Inspect the `.installed.json` metadata file and `enabled` flag
4. Disable and re-enable a skill without reinstalling it
5. Uninstall a skill while leaving other installed skills available

For marketplace installation flows, see:
`examples/01_standalone_sdk/43_mixed_marketplace_skills/`.
"""

import json
import tempfile
from pathlib import Path

from openhands.sdk.skills import (
    disable_skill,
    enable_skill,
    install_skill,
    list_installed_skills,
    load_installed_skills,
    uninstall_skill,
)


script_dir = Path(__file__).resolve().parent
example_skills_dir = script_dir.parent / "01_loading_agentskills" / "example_skills"


def print_state(label: str, installed_dir: Path) -> None:
    """Print tracked, loaded, and persisted skill state."""
    print(f"\n{label}")
    print("-" * len(label))

    installed = list_installed_skills(installed_dir=installed_dir)
    print("Tracked skills:")
    for info in installed:
        print(f"  - {info.name} (enabled={info.enabled}, source={info.source})")

    loaded = load_installed_skills(installed_dir=installed_dir)
    print(f"Loaded skills: {[skill.name for skill in loaded]}")

    metadata = json.loads((installed_dir / ".installed.json").read_text())
    print("Metadata file:")
    print(json.dumps(metadata, indent=2))


def demo_install_skills(installed_dir: Path) -> list[str]:
    """Install the sample skills into the isolated installed directory."""
    print("\n" + "=" * 60)
    print("DEMO 1: Installing local skills")
    print("=" * 60)

    installed_names: list[str] = []
    for skill_dir in sorted(example_skills_dir.iterdir()):
        if not skill_dir.is_dir():
            continue
        info = install_skill(source=str(skill_dir), installed_dir=installed_dir)
        installed_names.append(info.name)
        print(f"✓ Installed: {info.name}")
        print(f"  Source: {info.source}")
        print(f"  Path: {info.install_path}")

    return installed_names


def demo_list_and_load_skills(installed_dir: Path) -> None:
    """List tracked skills and load them as runtime Skill objects."""
    print("\n" + "=" * 60)
    print("DEMO 2: Listing and loading installed skills")
    print("=" * 60)

    installed = list_installed_skills(installed_dir=installed_dir)
    print("Tracked skills:")
    for info in installed:
        desc = (info.description or "No description")[:60]
        print(f"  - {info.name} (enabled={info.enabled})")
        print(f"    Description: {desc}...")

    loaded = load_installed_skills(installed_dir=installed_dir)
    print(f"\nLoaded {len(loaded)} skill(s):")
    for skill in loaded:
        desc = (skill.description or "No description")[:60]
        print(f"  - {skill.name}: {desc}...")


def demo_enable_disable_skill(installed_dir: Path, skill_name: str) -> None:
    """Disable then re-enable a skill and show the persisted metadata."""
    print("\n" + "=" * 60)
    print("DEMO 3: Disabling and re-enabling a skill")
    print("=" * 60)

    print_state("Before disable", installed_dir)

    assert disable_skill(skill_name, installed_dir=installed_dir) is True
    print_state("After disable", installed_dir)
    assert skill_name not in [
        skill.name for skill in load_installed_skills(installed_dir=installed_dir)
    ]

    metadata = json.loads((installed_dir / ".installed.json").read_text())
    assert metadata["skills"][skill_name]["enabled"] is False

    assert enable_skill(skill_name, installed_dir=installed_dir) is True
    print_state("After re-enable", installed_dir)

    metadata = json.loads((installed_dir / ".installed.json").read_text())
    assert metadata["skills"][skill_name]["enabled"] is True
    assert skill_name in [
        skill.name for skill in load_installed_skills(installed_dir=installed_dir)
    ]


def demo_uninstall_skill(
    installed_dir: Path, skill_name: str, remaining_skill_name: str
) -> None:
    """Uninstall one skill and confirm the other skill remains available."""
    print("\n" + "=" * 60)
    print("DEMO 4: Uninstalling a skill")
    print("=" * 60)

    assert uninstall_skill(skill_name, installed_dir=installed_dir) is True
    print_state("After uninstall", installed_dir)

    assert not (installed_dir / skill_name).exists()
    metadata = json.loads((installed_dir / ".installed.json").read_text())
    assert skill_name not in metadata["skills"]
    assert remaining_skill_name in metadata["skills"]


if __name__ == "__main__":
    with tempfile.TemporaryDirectory() as tmpdir:
        installed_dir = Path(tmpdir) / "installed-skills"
        installed_dir.mkdir(parents=True)

        installed_names = demo_install_skills(installed_dir)
        demo_list_and_load_skills(installed_dir)
        demo_enable_disable_skill(installed_dir, skill_name="rot13-encryption")
        demo_uninstall_skill(
            installed_dir,
            skill_name="rot13-encryption",
            remaining_skill_name="code-style-guide",
        )

        remaining_names = [
            info.name for info in list_installed_skills(installed_dir=installed_dir)
        ]
        assert remaining_names == ["code-style-guide"]
        assert sorted(installed_names) == ["code-style-guide", "rot13-encryption"]

    print("\nEXAMPLE_COST: 0")
```

You can run the example code as-is.

<Note>
  The model name should follow the [LiteLLM convention](https://models.litellm.ai/): `provider/model_name` (e.g., `anthropic/claude-sonnet-4-5-20250929`, `openai/gpt-4o`).
  The `LLM_API_KEY` should be the API key for your chosen provider.
</Note>

<CodeGroup>
  <CodeBlock language="bash" filename="Bring-your-own provider key" icon="terminal" wrap>
    {`export LLM_API_KEY="your-api-key"\nexport LLM_MODEL="anthropic/claude-sonnet-4-5-20250929"  # or openai/gpt-4o, etc.\ncd software-agent-sdk\nuv run python ${path_to_script_0}`}
  </CodeBlock>

  <CodeBlock language="bash" filename="OpenHands Cloud" icon="terminal" wrap>
    {`# https://app.all-hands.dev/settings/api-keys\nexport LLM_API_KEY="your-openhands-api-key"\nexport LLM_MODEL="openhands/claude-sonnet-4-5-20250929"\ncd software-agent-sdk\nuv run python ${path_to_script_0}`}
  </CodeBlock>
</CodeGroup>

<Tip>
  **ChatGPT Plus/Pro subscribers**: You can use `LLM.subscription_login()` to authenticate with your ChatGPT account and access Codex models without consuming API credits. See the [LLM Subscriptions guide](/sdk/guides/llm-subscriptions) for details.
</Tip>

### Installing Skills from a Marketplace

Use a marketplace when you want to install a curated mix of local and remote
AgentSkills in one step. The example below shows how to define a marketplace,
install all listed skills, and inspect the installed metadata.

<Note>
  Source: [examples/01\_standalone\_sdk/43\_mixed\_marketplace\_skills/main.py](https://github.com/OpenHands/software-agent-sdk/blob/main/examples/01_standalone_sdk/43_mixed_marketplace_skills/main.py)
</Note>

```python icon="python" expandable examples/01_standalone_sdk/43_mixed_marketplace_skills/main.py theme={null}
"""Example: Mixed Marketplace with Local and Remote Skills

This example demonstrates how to create a marketplace that includes both:
1. Local skills hosted in your project directory
2. Remote skills from GitHub (OpenHands/extensions repository)

The marketplace.json schema supports source paths in these formats:
- Local paths: ./path, ../path, /absolute/path, ~/path, file:///path
- GitHub URLs: https://github.com/{owner}/{repo}/blob/{branch}/{path}

This pattern is useful for teams that want to:
- Maintain their own custom skills locally
- Reference specific skills from remote repositories
- Create a curated skill set for their specific workflows

Directory Structure:
    43_mixed_marketplace_skills/
    ├── .plugin/
    │   └── marketplace.json     # Marketplace with local and remote skills
    ├── skills/
    │   └── greeting-helper/
    │       └── SKILL.md         # Local skill content
    ├── main.py                  # This file
    └── README.md                # Documentation

Usage:
    # Install all skills from marketplace to ~/.openhands/skills/installed/
    python main.py --install

    # Force reinstall (overwrite existing)
    python main.py --install --force

    # Show installed skills
    python main.py --list
"""

import sys
from pathlib import Path

from openhands.sdk.plugin import Marketplace
from openhands.sdk.skills import (
    install_skills_from_marketplace,
    list_installed_skills,
)


def main():
    script_dir = Path(__file__).parent

    if "--list" in sys.argv:
        # List installed skills
        print("=" * 80)
        print("Installed Skills")
        print("=" * 80)
        installed = list_installed_skills()
        if not installed:
            print("\nNo skills installed.")
            print("Run with --install to install skills from the marketplace.")
        else:
            for info in installed:
                desc = (info.description or "No description")[:60]
                print(f"\n  {info.name}")
                print(f"    Description: {desc}...")
                print(f"    Source: {info.source}")
        return

    if "--install" in sys.argv:
        # Install skills from marketplace
        print("=" * 80)
        print("Installing Skills from Marketplace")
        print("=" * 80)
        print(f"\nMarketplace directory: {script_dir}")

        force = "--force" in sys.argv
        installed = install_skills_from_marketplace(script_dir, force=force)

        print(f"\n\nInstalled {len(installed)} skills:")
        for info in installed:
            print(f"  - {info.name}")

        # Show all installed skills
        print("\n" + "=" * 80)
        print("All Installed Skills")
        print("=" * 80)
        all_installed = list_installed_skills()
        for info in all_installed:
            desc = (info.description or "No description")[:50]
            print(f"  - {info.name}: {desc}...")
        return

    # Default: show marketplace info
    print("=" * 80)
    print("Marketplace Information")
    print("=" * 80)
    print(f"\nMarketplace directory: {script_dir}")

    marketplace = Marketplace.load(script_dir)
    print(f"Name: {marketplace.name}")
    print(f"Description: {marketplace.description}")
    print(f"Skills defined: {len(marketplace.skills)}")

    print("\nSkills:")
    for entry in marketplace.skills:
        source_type = "remote" if entry.source.startswith("http") else "local"
        print(f"  - {entry.name} ({source_type})")
        print(f"    Source: {entry.source}")
        if entry.description:
            print(f"    Description: {entry.description}")

    print("\n" + "-" * 80)
    print("Usage:")
    print("  python main.py --install        # Install all skills")
    print("  python main.py --install --force # Force reinstall")
    print("  python main.py --list           # List installed skills")


if __name__ == "__main__":
    main()
```

You can run the example code as-is.

<Note>
  The model name should follow the [LiteLLM convention](https://models.litellm.ai/): `provider/model_name` (e.g., `anthropic/claude-sonnet-4-5-20250929`, `openai/gpt-4o`).
  The `LLM_API_KEY` should be the API key for your chosen provider.
</Note>

<CodeGroup>
  <CodeBlock language="bash" filename="Bring-your-own provider key" icon="terminal" wrap>
    {`export LLM_API_KEY="your-api-key"\nexport LLM_MODEL="anthropic/claude-sonnet-4-5-20250929"  # or openai/gpt-4o, etc.\ncd software-agent-sdk\nuv run python ${path_to_script_1}`}
  </CodeBlock>

  <CodeBlock language="bash" filename="OpenHands Cloud" icon="terminal" wrap>
    {`# https://app.all-hands.dev/settings/api-keys\nexport LLM_API_KEY="your-openhands-api-key"\nexport LLM_MODEL="openhands/claude-sonnet-4-5-20250929"\ncd software-agent-sdk\nuv run python ${path_to_script_1}`}
  </CodeBlock>
</CodeGroup>

<Tip>
  **ChatGPT Plus/Pro subscribers**: You can use `LLM.subscription_login()` to authenticate with your ChatGPT account and access Codex models without consuming API credits. See the [LLM Subscriptions guide](/sdk/guides/llm-subscriptions) for details.
</Tip>

***

## Full Example

<Note>
  Full example: [examples/01\_standalone\_sdk/03\_activate\_skill.py](https://github.com/OpenHands/software-agent-sdk/blob/main/examples/01_standalone_sdk/03_activate_skill.py)
</Note>

```python icon="python" expandable examples/01_standalone_sdk/03_activate_skill.py theme={null}
import os

from pydantic import SecretStr

from openhands.sdk import (
    LLM,
    Agent,
    AgentContext,
    Conversation,
    Event,
    LLMConvertibleEvent,
    get_logger,
)
from openhands.sdk.context import (
    KeywordTrigger,
    Skill,
)
from openhands.sdk.tool import Tool
from openhands.tools.file_editor import FileEditorTool
from openhands.tools.terminal import TerminalTool


logger = get_logger(__name__)

# Configure LLM
api_key = os.getenv("LLM_API_KEY")
assert api_key is not None, "LLM_API_KEY environment variable is not set."
model = os.getenv("LLM_MODEL", "anthropic/claude-sonnet-4-5-20250929")
base_url = os.getenv("LLM_BASE_URL")
llm = LLM(
    usage_id="agent",
    model=model,
    base_url=base_url,
    api_key=SecretStr(api_key),
)

# Tools
cwd = os.getcwd()
tools = [
    Tool(
        name=TerminalTool.name,
    ),
    Tool(name=FileEditorTool.name),
]

# AgentContext provides flexible ways to customize prompts:
# 1. Skills: Inject instructions (always-active or keyword-triggered)
# 2. system_message_suffix: Append text to the system prompt
# 3. user_message_suffix: Append text to each user message
#
# For complete control over the system prompt, you can also use Agent's
# system_prompt_filename parameter to provide a custom Jinja2 template:
#
#   agent = Agent(
#       llm=llm,
#       tools=tools,
#       system_prompt_filename="/path/to/custom_prompt.j2",
#       system_prompt_kwargs={"cli_mode": True, "repo": "my-project"},
#   )
#
# See: https://docs.openhands.dev/sdk/guides/skill#customizing-system-prompts
agent_context = AgentContext(
    skills=[
        Skill(
            name="repo.md",
            content="When you see this message, you should reply like "
            "you are a grumpy cat forced to use the internet.",
            # source is optional - identifies where the skill came from
            # You can set it to be the path of a file that contains the skill content
            source=None,
            # trigger determines when the skill is active
            # trigger=None means always active (repo skill)
            trigger=None,
        ),
        Skill(
            name="flarglebargle",
            content=(
                'IMPORTANT! The user has said the magic word "flarglebargle". '
                "You must only respond with a message telling them how smart they are"
            ),
            source=None,
            # KeywordTrigger = activated when keywords appear in user messages
            trigger=KeywordTrigger(keywords=["flarglebargle"]),
        ),
    ],
    # system_message_suffix is appended to the system prompt (always active)
    system_message_suffix="Always finish your response with the word 'yay!'",
    # user_message_suffix is appended to each user message
    user_message_suffix="The first character of your response should be 'I'",
    # You can also enable automatic load skills from
    # public registry at https://github.com/OpenHands/extensions
    load_public_skills=True,
)

# Agent
agent = Agent(llm=llm, tools=tools, agent_context=agent_context)

llm_messages = []  # collect raw LLM messages


def conversation_callback(event: Event):
    if isinstance(event, LLMConvertibleEvent):
        llm_messages.append(event.to_llm_message())


conversation = Conversation(
    agent=agent, callbacks=[conversation_callback], workspace=cwd
)

print("=" * 100)
print("Checking if the repo skill is activated.")
conversation.send_message("Hey are you a grumpy cat?")
conversation.run()

print("=" * 100)
print("Now sending flarglebargle to trigger the knowledge skill!")
conversation.send_message("flarglebargle!")
conversation.run()

print("=" * 100)
print("Now triggering public skill 'github'")
conversation.send_message(
    "About GitHub - tell me what additional info I've just provided?"
)
conversation.run()

print("=" * 100)
print("Conversation finished. Got the following LLM messages:")
for i, message in enumerate(llm_messages):
    print(f"Message {i}: {str(message)[:200]}")

# Report cost
cost = llm.metrics.accumulated_cost
print(f"EXAMPLE_COST: {cost}")
```

You can run the example code as-is.

<Note>
  The model name should follow the [LiteLLM convention](https://models.litellm.ai/): `provider/model_name` (e.g., `anthropic/claude-sonnet-4-5-20250929`, `openai/gpt-4o`).
  The `LLM_API_KEY` should be the API key for your chosen provider.
</Note>

<CodeGroup>
  <CodeBlock language="bash" filename="Bring-your-own provider key" icon="terminal" wrap>
    {`export LLM_API_KEY="your-api-key"\nexport LLM_MODEL="anthropic/claude-sonnet-4-5-20250929"  # or openai/gpt-4o, etc.\ncd software-agent-sdk\nuv run python ${path_to_script_2}`}
  </CodeBlock>

  <CodeBlock language="bash" filename="OpenHands Cloud" icon="terminal" wrap>
    {`# https://app.all-hands.dev/settings/api-keys\nexport LLM_API_KEY="your-openhands-api-key"\nexport LLM_MODEL="openhands/claude-sonnet-4-5-20250929"\ncd software-agent-sdk\nuv run python ${path_to_script_2}`}
  </CodeBlock>
</CodeGroup>

<Tip>
  **ChatGPT Plus/Pro subscribers**: You can use `LLM.subscription_login()` to authenticate with your ChatGPT account and access Codex models without consuming API credits. See the [LLM Subscriptions guide](/sdk/guides/llm-subscriptions) for details.
</Tip>

### Creating Skills

Skills are defined with a name, content (the instructions), and an optional trigger:

```python icon="python" focus={3-14} theme={null}
agent_context = AgentContext(
    skills=[
        Skill(
            name="AGENTS.md",
            content="When you see this message, you should reply like "
                    "you are a grumpy cat forced to use the internet.",
            trigger=None,  # Always active
        ),
        Skill(
            name="flarglebargle",
            content='IMPORTANT! The user has said the magic word "flarglebargle". '
                    "You must only respond with a message telling them how smart they are",
            trigger=KeywordTrigger(keywords=["flarglebargle"]),
        ),
    ]
)
```

### Keyword Triggers

Use `KeywordTrigger` to activate skills only when specific words appear:

```python icon="python" focus={4} theme={null}
Skill(
    name="magic-word",
    content="Special instructions when magic word is detected",
    trigger=KeywordTrigger(keywords=["flarglebargle", "sesame"]),
)
```

## File-Based Skills (`SKILL.md`)

For reusable skills, use the [AgentSkills standard](https://agentskills.io/specification) directory format.

<Note>
  Full example: [examples/05\_skills\_and\_plugins/01\_loading\_agentskills/main.py](https://github.com/OpenHands/software-agent-sdk/blob/main/examples/05_skills_and_plugins/01_loading_agentskills/main.py)
</Note>

### Directory Structure

Each skill is a directory containing:

<Tree>
  <Tree.Folder name="my-skill/" defaultOpen>
    <Tree.File name="SKILL.md" />

    <Tree.Folder name="scripts/" defaultOpen>
      <Tree.File name="helper.sh" />
    </Tree.Folder>

    <Tree.Folder name="references/" defaultOpen>
      <Tree.File name="examples.md" />
    </Tree.Folder>

    <Tree.Folder name="assets/" defaultOpen>
      <Tree.File name="config.json" />
    </Tree.Folder>
  </Tree.Folder>
</Tree>

where

| Component     | Required | Description                       |
| ------------- | -------- | --------------------------------- |
| `SKILL.md`    | Yes      | Skill definition with frontmatter |
| `scripts/`    | No       | Executable scripts                |
| `references/` | No       | Reference documentation           |
| `assets/`     | No       | Static assets                     |

### `SKILL.md` Format

The `SKILL.md` file defines the skill with YAML frontmatter:

```md icon="markdown" theme={null}
---
name: my-skill                    # Required (standard)
description: >                    # Required (standard)
  A brief description of what this skill does and when to use it.
license: MIT                      # Optional (standard)
compatibility: Requires bash      # Optional (standard)
metadata:                         # Optional (standard)
  author: your-name
  version: "1.0"
triggers:                         # Optional (OpenHands extension)
  - keyword1
  - keyword2
---

# Skill Content

Instructions and documentation for the agent...
```

#### Frontmatter Fields

| Field           | Required | Description                                                      |
| --------------- | -------- | ---------------------------------------------------------------- |
| `name`          | Yes      | Skill identifier (lowercase + hyphens)                           |
| `description`   | Yes      | What the skill does (shown to agent)                             |
| `triggers`      | No       | Keywords that auto-activate this skill (**OpenHands extension**) |
| `license`       | No       | License name                                                     |
| `compatibility` | No       | Environment requirements                                         |
| `metadata`      | No       | Custom key-value pairs                                           |

<Tip>
  Add `triggers` to make your SKILL.md keyword-activated by matching a user prompt. Without triggers, the skill can only be triggered by the agent, not the user.
</Tip>

### Loading Skills

Use `load_skills_from_dir()` to load all skills from a directory:

```python icon="python" expandable examples/05_skills_and_plugins/01_loading_agentskills/main.py theme={null}
"""Example: Loading Skills from Disk (AgentSkills Standard)

This example demonstrates how to load skills following the AgentSkills standard
from a directory on disk.

Skills are modular, self-contained packages that extend an agent's capabilities
by providing specialized knowledge, workflows, and tools. They follow the
AgentSkills standard which includes:
- SKILL.md file with frontmatter metadata (name, description, triggers)
- Optional resource directories: scripts/, references/, assets/

The example_skills/ directory contains two skills:
- rot13-encryption: Has triggers (encrypt, decrypt) - listed in <available_skills>
  AND content auto-injected when triggered
- code-style-guide: No triggers - listed in <available_skills> for on-demand access

All SKILL.md files follow the AgentSkills progressive disclosure model:
they are listed in <available_skills> with name, description, and location.
Skills with triggers get the best of both worlds: automatic content injection
when triggered, plus the agent can proactively read them anytime.
"""

import os
import sys
from pathlib import Path

from pydantic import SecretStr

from openhands.sdk import LLM, Agent, AgentContext, Conversation
from openhands.sdk.context.skills import (
    discover_skill_resources,
    load_skills_from_dir,
)
from openhands.sdk.tool import Tool
from openhands.tools.file_editor import FileEditorTool
from openhands.tools.terminal import TerminalTool


# Get the directory containing this script
script_dir = Path(__file__).parent
example_skills_dir = script_dir / "example_skills"

# =========================================================================
# Part 1: Loading Skills from a Directory
# =========================================================================
print("=" * 80)
print("Part 1: Loading Skills from a Directory")
print("=" * 80)

print(f"Loading skills from: {example_skills_dir}")

# Discover resources in the skill directory
skill_subdir = example_skills_dir / "rot13-encryption"
resources = discover_skill_resources(skill_subdir)
print("\nDiscovered resources in rot13-encryption/:")
print(f"  - scripts: {resources.scripts}")
print(f"  - references: {resources.references}")
print(f"  - assets: {resources.assets}")

# Load skills from the directory
repo_skills, knowledge_skills, agent_skills = load_skills_from_dir(example_skills_dir)

print("\nLoaded skills from directory:")
print(f"  - Repo skills: {list(repo_skills.keys())}")
print(f"  - Knowledge skills: {list(knowledge_skills.keys())}")
print(f"  - Agent skills (SKILL.md): {list(agent_skills.keys())}")

# Access the loaded skill and show all AgentSkills standard fields
if agent_skills:
    skill_name = next(iter(agent_skills))
    loaded_skill = agent_skills[skill_name]
    print(f"\nDetails for '{skill_name}' (AgentSkills standard fields):")
    print(f"  - Name: {loaded_skill.name}")
    desc = loaded_skill.description or ""
    print(f"  - Description: {desc[:70]}...")
    print(f"  - License: {loaded_skill.license}")
    print(f"  - Compatibility: {loaded_skill.compatibility}")
    print(f"  - Metadata: {loaded_skill.metadata}")
    if loaded_skill.resources:
        print("  - Resources:")
        print(f"    - Scripts: {loaded_skill.resources.scripts}")
        print(f"    - References: {loaded_skill.resources.references}")
        print(f"    - Assets: {loaded_skill.resources.assets}")
        print(f"    - Skill root: {loaded_skill.resources.skill_root}")

# =========================================================================
# Part 2: Using Skills with an Agent
# =========================================================================
print("\n" + "=" * 80)
print("Part 2: Using Skills with an Agent")
print("=" * 80)

# Check for API key
api_key = os.getenv("LLM_API_KEY")
if not api_key:
    print("Skipping agent demo (LLM_API_KEY not set)")
    print("\nTo run the full demo, set the LLM_API_KEY environment variable:")
    print("  export LLM_API_KEY=your-api-key")
    sys.exit(0)

# Configure LLM
model = os.getenv("LLM_MODEL", "anthropic/claude-sonnet-4-5-20250929")
llm = LLM(
    usage_id="skills-demo",
    model=model,
    api_key=SecretStr(api_key),
    base_url=os.getenv("LLM_BASE_URL"),
)

# Create agent context with loaded skills
agent_context = AgentContext(
    skills=list(agent_skills.values()),
    # Disable public skills for this demo to keep output focused
    load_public_skills=False,
)

# Create agent with tools so it can read skill resources
tools = [
    Tool(name=TerminalTool.name),
    Tool(name=FileEditorTool.name),
]
agent = Agent(llm=llm, tools=tools, agent_context=agent_context)

# Create conversation
conversation = Conversation(agent=agent, workspace=os.getcwd())

# Test the skill (triggered by "encrypt" keyword)
# The skill provides instructions and a script for ROT13 encryption
print("\nSending message with 'encrypt' keyword to trigger skill...")
conversation.send_message("Encrypt the message 'hello world'.")
conversation.run()

print(f"\nTotal cost: ${llm.metrics.accumulated_cost:.4f}")
print(f"EXAMPLE_COST: {llm.metrics.accumulated_cost:.4f}")
```

You can run the example code as-is.

<Note>
  The model name should follow the [LiteLLM convention](https://models.litellm.ai/): `provider/model_name` (e.g., `anthropic/claude-sonnet-4-5-20250929`, `openai/gpt-4o`).
  The `LLM_API_KEY` should be the API key for your chosen provider.
</Note>

<CodeGroup>
  <CodeBlock language="bash" filename="Bring-your-own provider key" icon="terminal" wrap>
    {`export LLM_API_KEY="your-api-key"\nexport LLM_MODEL="anthropic/claude-sonnet-4-5-20250929"  # or openai/gpt-4o, etc.\ncd software-agent-sdk\nuv run python ${path_to_script_3}`}
  </CodeBlock>

  <CodeBlock language="bash" filename="OpenHands Cloud" icon="terminal" wrap>
    {`# https://app.all-hands.dev/settings/api-keys\nexport LLM_API_KEY="your-openhands-api-key"\nexport LLM_MODEL="openhands/claude-sonnet-4-5-20250929"\ncd software-agent-sdk\nuv run python ${path_to_script_3}`}
  </CodeBlock>
</CodeGroup>

<Tip>
  **ChatGPT Plus/Pro subscribers**: You can use `LLM.subscription_login()` to authenticate with your ChatGPT account and access Codex models without consuming API credits. See the [LLM Subscriptions guide](/sdk/guides/llm-subscriptions) for details.
</Tip>

### Key Functions

#### `load_skills_from_dir()`

Loads all skills from a directory, returning three dictionaries:

```python icon="python" focus={3} theme={null}
from openhands.sdk.context.skills import load_skills_from_dir

repo_skills, knowledge_skills, agent_skills = load_skills_from_dir(skills_dir)
```

| Return Value          | Source Files                                      | Injection Behavior                                                                                   |
| --------------------- | ------------------------------------------------- | ---------------------------------------------------------------------------------------------------- |
| **repo\_skills**      | `repo.md`, `AGENTS.md`, `.cursorrules`            | Full content in `<REPO_CONTEXT>` in the initial system prompt; included in LLM context for each turn |
| **knowledge\_skills** | `knowledge/` subdirectories, `*.md` with triggers | Listed in `<available_skills>`, auto-inject on trigger                                               |
| **agent\_skills**     | `SKILL.md` files (AgentSkills standard)           | Listed in `<available_skills>`, agent calls `invoke_skill()`                                         |

<Tip>
  When passing to `AgentContext(skills=...)`, all three types are accepted. The injection behavior depends on the skill's `is_agentskills_format` flag and `trigger` field — see [Skill Injection Behavior](#skill-injection-behavior).
</Tip>

#### `discover_skill_resources()`

Discovers resource files in a skill directory:

```python icon="python" focus={3} theme={null}
from openhands.sdk.context.skills import discover_skill_resources

resources = discover_skill_resources(skill_dir)
print(resources.scripts)     # List of script files
print(resources.references)  # List of reference files
print(resources.assets)      # List of asset files
print(resources.skill_root)  # Path to skill directory
```

### Skill Location in Prompts

The `<location>` element in `<available_skills>` follows the AgentSkills standard, allowing agents to read the full skill content on demand. When a triggered skill is activated, the content is injected with the location path:

```
<EXTRA_INFO>
The following information has been included based on a keyword match for "encrypt".

Skill location: /path/to/rot13-encryption
(Use this path to resolve relative file references in the skill content below)

[skill content from SKILL.md]
</EXTRA_INFO>
```

This enables skills to reference their own scripts and resources using relative paths like `./scripts/encrypt.sh`.

### Example Skill: ROT13 Encryption

Here's a skill with triggers (OpenHands extension):

**SKILL.md:**

```markdown icon="markdown" theme={null}
---
name: rot13-encryption
description: >
  This skill helps encrypt and decrypt messages using ROT13 cipher.
triggers:
  - encrypt
  - decrypt
  - cipher
---

# ROT13 Encryption Skill

Run the [encrypt.sh](scripts/encrypt.sh) script with your message:

\`\`\`bash
./scripts/encrypt.sh "your message"
\`\`\`
```

**scripts/encrypt.sh:**

```bash icon="sh" theme={null}
#!/bin/bash
echo "$1" | tr 'A-Za-z' 'N-ZA-Mn-za-m'
```

When the user says "encrypt", the skill is triggered and the agent can use the provided script.

## Loading Public Skills

OpenHands maintains a [public skills repository](https://github.com/OpenHands/extensions) with community-contributed skills. You can automatically load these skills without waiting for SDK updates.

### Automatic Loading via AgentContext

Enable public skills loading in your `AgentContext`:

```python icon="python" focus={2} theme={null}
agent_context = AgentContext(
    load_public_skills=True,  # Auto-load from public registry
    skills=[
        # Your custom skills here
    ]
)
```

When enabled, the SDK will:

1. Clone or update the public skills repository to `~/.openhands/cache/skills/` on first run
2. Load all available skills from the repository
3. Merge them with your explicitly defined skills

### Skill Naming and Triggers

**Skill Precedence by Name**: If a skill name conflicts, your explicitly defined skills take precedence over public skills. For example, if you define a skill named `code-review`, the public `code-review` skill will be skipped entirely.

**Multiple Skills with Same Trigger**: Skills with different names but the same trigger can coexist and will ALL be activated when the trigger matches. To add project-specific guidelines alongside public skills, use a unique name (e.g., `custom-codereview-guide` instead of `code-review`). Both skills will be triggered together.

```python icon="python" theme={null}
# Both skills will be triggered by "/codereview"
agent_context = AgentContext(
    load_public_skills=True,  # Loads public "code-review" skill
    skills=[
        Skill(
            name="custom-codereview-guide",  # Different name = coexists
            content="Project-specific guidelines...",
            trigger=KeywordTrigger(keywords=["/codereview"]),
        ),
    ]
)
```

<Tip>
  **Skill Activation Behavior**: When multiple skills share a trigger, all matching skills are loaded. Content is concatenated into the agent's context with public skills first, then explicitly defined skills. There is no smart merging—if guidelines conflict, the agent sees both.
</Tip>

### Programmatic Loading

You can also load public skills manually and have more control:

```python icon="python" theme={null}
from openhands.sdk.context.skills import load_public_skills

# Load all public skills
public_skills = load_public_skills()

# Use with AgentContext
agent_context = AgentContext(skills=public_skills)

# Or combine with custom skills
my_skills = [
    Skill(name="custom", content="Custom instructions", trigger=None)
]
agent_context = AgentContext(skills=my_skills + public_skills)
```

### Custom Skills Repository

You can load skills from your own repository:

```python icon="python" focus={3-7} theme={null}
from openhands.sdk.context.skills import load_public_skills

# Load from a custom repository
custom_skills = load_public_skills(
    repo_url="https://github.com/my-org/my-skills",
    branch="main"
)
```

### How It Works

The `load_public_skills()` function uses git-based caching for efficiency:

* **First run**: Clones the skills repository to `~/.openhands/cache/skills/public-skills/`
* **Subsequent runs**: Pulls the latest changes to keep skills up-to-date
* **Offline mode**: Uses the cached version if network is unavailable

This approach is more efficient than fetching individual skill files via HTTP and ensures you always have access to the latest community skills.

<Note>
  Explore available public skills at [github.com/OpenHands/extensions](https://github.com/OpenHands/extensions). These skills cover various domains like GitHub integration, Python development, debugging, and more.
</Note>

## Customizing Agent Context

### Message Suffixes

Append custom instructions to the system prompt or user messages via `AgentContext`:

```python icon="python" theme={null}
agent_context = AgentContext(
    system_message_suffix="""
<REPOSITORY_INFO>
Repository: my-project
Branch: feature/new-api
</REPOSITORY_INFO>
    """.strip(),
    user_message_suffix="Remember to explain your reasoning."
)
```

* **`system_message_suffix`**: Appended to system prompt (always active, combined with repo skills)
* **`user_message_suffix`**: Appended to each user message

### Replacing the Entire System Prompt

For complete control, provide a custom Jinja2 template via the `Agent` class:

```python icon="python" focus={6} theme={null}
from openhands.sdk import Agent

agent = Agent(
    llm=llm,
    tools=tools,
    system_prompt_filename="/path/to/custom_system_prompt.j2",  # Absolute path
    system_prompt_kwargs={"cli_mode": True, "repo_name": "my-project"}
)
```

**Custom template example** (`custom_system_prompt.j2`):

```jinja2 theme={null}
You are a helpful coding assistant for {{ repo_name }}.

{% if cli_mode %}
You are running in CLI mode. Keep responses concise.
{% endif %}

Follow these guidelines:
- Write clean, well-documented code
- Consider edge cases and error handling
- Suggest tests when appropriate
```

**Key points:**

* Use relative filenames (e.g., `"system_prompt.j2"`) to load from the agent's prompts directory
* Use absolute paths (e.g., `"/path/to/prompt.j2"`) to load from any location
* Pass variables to the template via `system_prompt_kwargs`
* The `system_message_suffix` from `AgentContext` is automatically appended after your custom prompt

## Dynamic Command Execution

Skills support inline shell command execution for injecting dynamic context at render time. This is useful for including repository state, environment information, or computed values in skill content.

<Warning>
  **Security**: Commands execute with full shell privileges. Only use this feature with trusted skill sources. User-provided content should never be passed to command execution.
</Warning>

### Basic Syntax

Use `` !`command` `` to execute a shell command and replace it with stdout:

```markdown icon="markdown" theme={null}
---
name: repo-context
description: Injects current repository state
triggers:
  - git
  - commit
---

# Repository Context

Current branch: !`git branch --show-current`
Last commit: !`git log -1 --oneline`
```

When triggered, the skill content becomes:

```markdown icon="markdown" theme={null}
# Repository Context

Current branch: main
Last commit: a1b2c3d Fix authentication bug
```

### Safety Rules

**Code blocks are never executed.** Both fenced and inline code blocks are preserved:

````markdown icon="markdown" theme={null}
# Safe Examples

Regular inline code: `git status` → preserved as-is
Fenced block: → preserved as-is
```bash
!`echo "not executed"`
```

Dynamic command: !`echo "executed"` → replaced with "executed"
````

**Unclosed fenced blocks protect trailing content.** If a fenced block isn't closed (odd number of \`\`\` delimiters), everything after it is treated as inside the fence:

````markdown icon="markdown" theme={null}
```bash
!`echo "inside fence - not executed"`
```

!`echo "between fences - executed"`

```bash
!`echo "unclosed fence - not executed"`
````

### Escape Syntax

Use `` \!`cmd` `` to output the literal text `` !`cmd` `` without execution:

```markdown icon="markdown" theme={null}
# Documenting the Syntax

To execute a command, use \!`command` syntax.
For example: \!`git status` shows the current git state.
```

Output:

```markdown theme={null}
# Documenting the Syntax

To execute a command, use !`command` syntax.
For example: !`git status` shows the current git state.
```

### Error Handling

Failed commands return inline error markers:

| Scenario             | Output                                                     |
| -------------------- | ---------------------------------------------------------- |
| Command fails        | `[Error: Command `xyz` exited with code 1: error message]` |
| Command times out    | `[Error: Command `xyz` timed out after 10s]`               |
| Large output (>50KB) | Output truncated with `... [output truncated]`             |

### Programmatic Rendering

When using skills programmatically, call `render_content()` to execute commands:

```python icon="python" focus={6-7} theme={null}
from openhands.sdk.context import Skill

skill = Skill.load("/path/to/skill/SKILL.md")

# Render with command execution
rendered = skill.render_content(working_dir="/path/to/repo")
print(rendered)  # Commands replaced with output
```

The `working_dir` parameter sets the current directory for command execution, enabling workspace-relative commands like `git status`.

## Migrating from Legacy to AgentSkills Format

If you have legacy inline skills consuming many tokens, convert them to AgentSkills format for progressive disclosure:

### Before (Legacy Format)

```python icon="python" theme={null}
# Legacy: Full content in <REPO_CONTEXT> in the initial system prompt
Skill(
    name="api-guidelines",
    content="""
    # API Guidelines
    ... 2000 lines of detailed documentation ...
    """,
    trigger=None,  # Always-on context - affects token usage on each turn!
)
```

### After (AgentSkills Format)

Create a directory `api-guidelines/SKILL.md`:

```markdown icon="markdown" theme={null}
---
name: api-guidelines
description: Comprehensive API design guidelines for the project. Invoke when designing or reviewing API endpoints.
---

# API Guidelines

... 2000 lines of detailed documentation ...
```

Then load it:

```python icon="python" theme={null}
from openhands.sdk.skills import load_skills_from_dir

# AgentSkills: Only description in prompt, agent reads full content on demand
_, _, skills = load_skills_from_dir("/path/to/skills")
agent_context = AgentContext(skills=list(skills.values()))
```

### Benefits

| Aspect        | Legacy `trigger=None`                                                | AgentSkills `SKILL.md`          |
| ------------- | -------------------------------------------------------------------- | ------------------------------- |
| Token usage   | Full content in system prompt; included in LLM context for each turn | Description only (\~100 chars)  |
| Model control | None — always present                                                | Agent decides when to read      |
| Scalability   | Limited by context window                                            | Many skills without token bloat |

## Next Steps

* **[Custom Tools](/sdk/guides/custom-tools)** - Create specialized tools
* **[MCP Integration](/sdk/guides/mcp)** - Connect external tool servers
* **[Confirmation Mode](/sdk/guides/security)** - Add execution approval