"""Schachstellen-Erkennung für unified Slot-Review."""
from planning_exercise_path_builder import (
    _problematic_slots_from_path_qa,
    _slot_suggestion_accepted,
)
from planning_progression_roadmap import StageSpecArtifact


def _spec(midx: int) -> StageSpecArtifact:
    return StageSpecArtifact(
        major_step_index=midx,
        learning_goal=f"Lernziel Slot {midx + 1}",
        load_profile=[],
        exercise_type="",
        success_criteria=[],
        anti_patterns=[],
    )


def test_problematic_slots_from_optimization_hints():
    qa = {
        "optimization_hints": [
            {
                "action": "rematch_slot",
                "step_index": 1,
                "issue": "stage_mismatch",
                "reason": "Übung passt nicht zur Stufe",
            }
        ],
        "off_topic_steps": [],
    }
    steps = [
        {"roadmap_major_step_index": 0, "exercise_id": 1, "title": "A"},
        {"roadmap_major_step_index": 1, "exercise_id": 2, "title": "B"},
    ]
    specs = [_spec(0), _spec(1)]
    problems = _problematic_slots_from_path_qa(qa, steps, specs)
    assert 1 in problems
    assert any("Stufe" in r or "passt" in r for r in problems[1])


def test_slot_suggestion_accepted_for_problem_slot():
    diff = {"baseline_exercise_id": 10, "proposed_exercise_id": 99}
    assert _slot_suggestion_accepted(
        baseline_qa={"optimization_hints": [{"action": "rematch_slot", "roadmap_major_step_index": 1}]},
        projected_qa={"optimization_hints": []},
        baseline_score=0.7,
        projected_score=0.7,
        diff=diff,
        off_topic=False,
        major_idx=1,
        slot_problem=True,
    )