"""Skill Prompt Optimizer framework for tuning SKILL.md instruction prompts."""

import logging
from typing import Any, Dict, List
from eval.metrics import evaluate_case_run

logger = logging.getLogger(__name__)


class SkillOptimizer:
    """Analyzes benchmark evaluation feedback and recommends skill prompt adjustments."""

    def generate_tuning_recommendations(self, eval_summary: Dict[str, Any]) -> List[Dict[str, Any]]:
        """Generate prompt tuning recommendations based on evaluation failures."""
        recommendations = []
        results = eval_summary.get("results", [])

        for res in results:
            if not res.get("passed"):
                feedback_items = res.get("feedback", [])
                for feedback in feedback_items:
                    rec = self._map_feedback_to_skill_tuning(res.get("case_id"), feedback)
                    if rec:
                        recommendations.append(rec)

        return recommendations

    def _map_feedback_to_skill_tuning(self, case_id: str, feedback: str) -> Dict[str, Any] | None:
        """Maps specific feedback strings to target SKILL.md prompt enhancements."""
        if "deferred" in feedback.lower():
            return {
                "target_skill": "requirements_discovery",
                "phase": "discover",
                "issue": feedback,
                "recommendation": "Emphasize product selection deferral rule in app/skills/requirements_discovery/SKILL.md frontmatter and guidelines.",
            }
        elif "mermaid" in feedback.lower():
            return {
                "target_skill": "architecture_design",
                "phase": "design",
                "issue": feedback,
                "recommendation": "Add strict Mermaid diagram syntax validation guidelines to app/skills/architecture_design/SKILL.md.",
            }
        elif "terraform" in feedback.lower():
            return {
                "target_skill": "architecture_design",
                "phase": "design",
                "issue": feedback,
                "recommendation": "Ensure Terraform provider and Google Cloud resource block patterns are explicit in app/skills/architecture_design/SKILL.md.",
            }
        elif "section" in feedback.lower():
            return {
                "target_skill": "packaging_guide",
                "phase": "package",
                "issue": feedback,
                "recommendation": "Include explicit section headers checklist in app/skills/packaging_guide/SKILL.md.",
            }
        return None