reviewer/report.py

import json
import uuid
from datetime import datetime, timezone
from pathlib import Path
from config import settings
from reviewer.scorer import score_session, get_all_spooled_entries
from reviewer.pattern_detector import detect_failure_patterns
from reviewer.skill_analyzer import analyze_skill_coverage


def _group_by_session(rows: list[dict]) -> dict[str, list[dict]]:
    grouped = {}
    for row in rows:
        grouped.setdefault(row["session_id"], []).append(row)
    return grouped


def generate_report(since: str | None = None) -> dict:
    from spooler.store import get_conn

    conn = get_conn()
    rows = get_all_spooled_entries(conn, since)
    conn.close()

    # Group and score
    grouped = _group_by_session(rows)
    session_scores = []
    for session_id, sess_rows in grouped.items():
        agent_id = sess_rows[0].get("agent_id", "unknown")
        scored = score_session(sess_rows)
        scored["session_id"] = session_id
        scored["agent_id"] = agent_id
        session_scores.append(scored)

    # Detect patterns
    patterns = detect_failure_patterns(session_scores, rows)

    # Skill coverage
    skill_coverage = analyze_skill_coverage()

    # Optimization recommendations (stub — deterministic only)
    recommendations = []
    for mcp in skill_coverage.get("mcps_missing_skill_surface", []):
        recommendations.append({
            "type": "skill_surface_missing",
            "description": f"MCP '{mcp}' is registered but has no skill surface",
            "target": mcp,
            "confidence": 0.8,
        })

    # Unused skills (skills dir exists, no tool_name match in spool)
    skill_names = set(skill_coverage.get("mcps_with_skill_surface", []))
    used_tools = {r.get("tool_name") for r in rows if r.get("tool_name")}
    unused_skills = [s for s in skill_names if s not in used_tools and s not in skill_coverage.get("mcps_missing_skill_surface", [])]
    for skill in unused_skills:
        recommendations.append({
            "type": "skill_never_used",
            "description": f"Skill '{skill}' exists but was not used in this period",
            "target": skill,
            "confidence": 0.7,
        })

    # Filter by confidence threshold
    recommendations = [r for r in recommendations if r["confidence"] >= settings.review_confidence_threshold]

    # Drift signals (stub — compare to previous report if available)
    drift_signals = []

    report = {
        "review_id": str(uuid.uuid4()),
        "generated_at": datetime.now(timezone.utc).isoformat(),
        "period": {
            "from": since or "all",
            "to": datetime.now(timezone.utc).isoformat(),
        },
        "sessions_reviewed": len(session_scores),
        "session_quality_scores": session_scores,
        "failure_patterns": patterns,
        "unused_tools": [
            {"tool": mcp, "registered": True, "used_this_week": False}
            for mcp in skill_coverage.get("mcps_missing_skill_surface", [])
        ],
        "optimization_recommendations": recommendations,
        "drift_signals": drift_signals,
        "skill_coverage": skill_coverage,
    }

    # Persist to DB
    _persist_report(report)

    return report


def generate_skills_report() -> dict:
    coverage = analyze_skill_coverage()
    report = {
        "generated_at": datetime.now(timezone.utc).isoformat(),
        "period": "weekly",
        **coverage,
    }
    _write_json_artifact("skills-latest.json", report)
    return report


def _persist_report(report: dict):
    from spooler.store import get_conn

    conn = get_conn()
    conn.execute(
        """
        INSERT OR REPLACE INTO review_reports
        (review_id, generated_at, period_from, period_to, report_json)
        VALUES (?, ?, ?, ?, ?)
        """,
        (
            report["review_id"],
            report["generated_at"],
            report["period"]["from"],
            report["period"]["to"],
            json.dumps(report),
        ),
    )
    conn.commit()
    conn.close()
    _write_json_artifact("review-latest.json", report)
    _write_json_artifact(f"history/review-{report['generated_at'].replace(':', '').replace('+00:00', 'Z')}.json", report)


def _write_json_artifact(relative_path: str, payload: dict):
    base = settings.openclaw_state_dir / "session_amplifier"
    target = base / relative_path
    target.parent.mkdir(parents=True, exist_ok=True)
    target.write_text(json.dumps(payload, indent=2, sort_keys=True))