Skill

Data Structures for Skills.

SkillScope

Bases: str, Enum

Skill scope enum.

Source code in src/llm_agents_from_scratch/data_structures/skill.py

class SkillScope(str, Enum):
    """Skill scope enum."""

    PROJECT = "project"
    USER = "user"

SkillFrontmatter

Bases: BaseModel

Parsed frontmatter metadata from a skill's SKILL.md file.

Conforms to the Agent Skills open standard frontmatter specification.

Attributes:

Name	Type	Description
name	str	Name of the skill.
description	str	Description of what the skill does and when to use it.
license	str | None	License name or reference to a bundled license file.
compatibility	str | None	Environment requirements for the skill.
metadata	dict[str, str] | None	Arbitrary key-value pairs for additional metadata.
allowed_tools	str | None	Space-delimited list of pre-approved tools the skill may use.

Source code in src/llm_agents_from_scratch/data_structures/skill.py

class SkillFrontmatter(BaseModel):
    """Parsed frontmatter metadata from a skill's SKILL.md file.

    Conforms to the Agent Skills open standard frontmatter specification.

    Attributes:
        name: Name of the skill.
        description: Description of what the skill does and when to use it.
        license: License name or reference to a bundled license file.
        compatibility: Environment requirements for the skill.
        metadata: Arbitrary key-value pairs for additional metadata.
        allowed_tools: Space-delimited list of pre-approved tools the skill
            may use.
    """

    model_config = ConfigDict(populate_by_name=True)

    name: str
    description: str
    license: str | None = None
    compatibility: str | None = None
    metadata: dict[str, str] | None = None
    allowed_tools: str | None = Field(default=None, alias="allowed-tools")

    @field_validator("name", "description")
    @classmethod
    def must_be_non_empty(cls, v: str) -> str:
        """Validate that name and description are non-empty strings.

        Args:
            v: The field value to validate.

        Returns:
            The validated field value.

        Raises:
            ValueError: If the field value is empty or whitespace-only.
        """
        if not v or not v.strip():
            raise ValueError("must be a non-empty string")
        return v

must_be_non_empty classmethod

must_be_non_empty(v)

Validate that name and description are non-empty strings.

Parameters:

Name	Type	Description	Default
v	str	The field value to validate.	required

Returns:

Type	Description
str	The validated field value.

Raises:

Type	Description
ValueError	If the field value is empty or whitespace-only.

Source code in src/llm_agents_from_scratch/data_structures/skill.py

@field_validator("name", "description")
@classmethod
def must_be_non_empty(cls, v: str) -> str:
    """Validate that name and description are non-empty strings.

    Args:
        v: The field value to validate.

    Returns:
        The validated field value.

    Raises:
        ValueError: If the field value is empty or whitespace-only.
    """
    if not v or not v.strip():
        raise ValueError("must be a non-empty string")
    return v