"""Load skill tool — allows the LLM to load skill instructions on demand."""

from __future__ import annotations

from pathlib import Path
from typing import Any, ClassVar

from pydantic import BaseModel, Field

from app.models.config import AppConfig
from app.models.tool_call import ToolResult, ToolResultStatus
from app.services.skills import SkillsManager
from app.tools.base import BaseTool


class LoadSkillParams(BaseModel):
    """Parameters for the load_skill tool."""

    name: str = Field(description="Name of the skill to load")


class LoadSkillTool(BaseTool):
    """Load a skill's full instructions by name.

    Use when a skill is relevant to the current task.
    """

    name: ClassVar[str] = "load_skill"
    description: ClassVar[str] = (
        "Load a skill's full instructions by name. "
        "Use when a skill is relevant to the current task."
    )
    params_model: ClassVar[type[BaseModel]] = LoadSkillParams

    def __init__(
        self,
        workspace_root: Path,
        config: AppConfig,
        skills_manager: SkillsManager,
    ) -> None:
        super().__init__(workspace_root, config)
        self._skills = skills_manager

    def execute(self, *, tool_call_id: str, **kwargs: Any) -> ToolResult:
        skill_name: str = kwargs["name"]
        content = self._skills.load_skill(skill_name)
        if content is None:
            available = [s.name for s in self._skills.list_skills()]
            return ToolResult(
                tool_call_id=tool_call_id,
                tool_name=self.name,
                status=ToolResultStatus.ERROR,
                error=f"Unknown skill '{skill_name}'. Available: {available}",
            )
        return ToolResult(
            tool_call_id=tool_call_id,
            tool_name=self.name,
            status=ToolResultStatus.SUCCESS,
            output=content,
        )