"""Stage 7: Reviewer — LLM review of generated skill."""
import json
from pipeline.extractor import call_llm

def review_skill(generator_output, config):
    """
    Review a generated skill. Generation and review are separated.
    The reviewer never modifies — only approves or rejects with feedback.
    """
    if generator_output.get("status") != "GENERATED":
        return {
            "status": "BLOCKED",
            "reason": "Generation failed",
        }

    files = generator_output.get("files", {})
    skill_md = files.get("SKILL.md", "")

    prompt = f"""You are reviewing an AI Agent Skill that was automatically extracted from a GitHub repository.

Would an experienced engineer install this Skill without editing it?

Answer with ONLY valid JSON in this format:
{{
  "decision": "YES" or "NO",
  "confidence": 0.0-1.0,
  "reason": "One paragraph explaining your decision",
  "missing_assumptions": ["List any unclear steps or assumptions"],
  "minimum_changes": ["If NO, list the minimum changes for approval"]
}}

Skill to review:

{skill_md}

Remember:
- The skill must be clearly documented
- It must be reusable outside the original repository
- Steps must be specific enough to execute
- Inputs and outputs must be well-defined
- Failure modes should be documented

Return ONLY valid JSON. No markdown."""

    result_text = call_llm(prompt, config)

    try:
        cleaned = result_text.strip()
        if cleaned.startswith("```"):
            cleaned = cleaned.split("```")[1]
            if cleaned.startswith("json"):
                cleaned = cleaned[4:]
            cleaned = cleaned.rstrip("```")
        cleaned = cleaned.strip()

        review = json.loads(cleaned)

        decision = review.get("decision", "NO").upper()
        confidence = review.get("confidence", 0)
        min_confidence = config.get("reviewer", {}).get("confidence_min", 0.80)

        if decision == "YES" and confidence >= min_confidence:
            status = "APPROVED"
        elif decision == "YES" and confidence < min_confidence:
            status = "LOW_CONFIDENCE"
        else:
            status = "REJECTED"

        return {
            "status": status,
            "decision": decision,
            "confidence": confidence,
            "reason": review.get("reason", ""),
            "missing_assumptions": review.get("missing_assumptions", []),
            "minimum_changes": review.get("minimum_changes", []),
            "generator_output": generator_output,
        }

    except json.JSONDecodeError:
        return {
            "status": "REVIEW_ERROR",
            "raw": result_text[:500],
            "generator_output": generator_output,
        }