Merge pull request 'feat: 3 missing sections + summary + MACRO_EVENT_TICKER_IMPACT_V1 DAG registration' (#52) from feature/render-missing-sections into main

feat: 3 missing sections + summary + MACRO_EVENT_TICKER_IMPACT_V1 DAG registration

spec/13_formula_registry.yaml

@@ -107,7 +107,7 @@ formula_registry:
         FINAL_DECISION_PACKET_V1: spec/13b_harness_formulas.yaml:bridge_only
         ORDER_MATH_RECONCILIATION_V1: spec/13b_harness_formulas.yaml:bridge_only
         REPORT_AUTHORITY_DIFF_V1: spec/13b_harness_formulas.yaml:bridge_only
-        MACRO_EVENT_TICKER_IMPACT_V1: tools/validate_engine_harness_gate.py
+        MACRO_EVENT_TICKER_IMPACT_V1: tools/build_macro_event_ticker_impact_v1.py
         INVESTMENT_QUALITY_HEADLINE_V1: tools/validate_specs.py
         ALGORITHM_GUIDANCE_PROOF_V1: tools/build_algorithm_guidance_proof_v1.py
         CANONICAL_ARTIFACT_RESOLVER_V1: tools/validate_canonical_artifact_resolver_v1.py

spec/41_release_dag.yaml

@@ -1,11 +1,12 @@
 schema_version: release_dag.v3
-step_count: 75
+step_count: 76
 goal: Linearize package.json scripts into a validated DAG execution graph.
 execution_order:
   # 토폴로지 정렬 기준 병렬 실행 wave (의존성 없는 노드들을 동시에 실행 가능)
   wave_0:
     - audit_entropy
     - build_bundle
+    - build_macro_event_ticker_impact
     - build_engine_health_card
     - build_late_chase_attribution
     - build_live_replay_separation
@@ -101,6 +102,18 @@ dag:
       strict: true
       artifact_policy: "keep"
 
+    build_macro_event_ticker_impact:
+      id: build_macro_event_ticker_impact
+      command: ["python", "tools/build_macro_event_ticker_impact_v1.py"]
+      inputs: ["tools/build_macro_event_ticker_impact_v1.py", "GatherTradingData.json"]
+      outputs: ["Temp/macro_event_ticker_impact_v1.json"]
+      depends_on: []
+      timeout_sec: 30
+      cache_key: "build_macro_event_ticker_impact_v1"
+      strict: false
+      artifact_policy: "keep"
+      note: "core_satellite 종목별 매크로 이벤트 임팩트 레지스터 — MACRO_EVENT_TICKER_IMPACT_V1"
+
     build_formula_outputs:
       id: build_formula_outputs
       command: ["python", "src/quant_engine/compute_formula_outputs.py", "--output", "Temp/computed_harness_v1.json"]

tools/render_operational_report.py

@@ -31,6 +31,8 @@ SECTION_ORDER = [
     "watch_release_checklist", "alpha_feedback_loop_report",
     "backdata_feature_bank_table", "alpha_lead_table", "anti_distribution_table",
     "profit_preservation_table", "smart_cash_raise_table", "execution_quality_table",
+    "sell_priority_decision_table", "strategy_performance_scoreboard",
+    "outcome_eval_window_monitor",
     "decision_trace_table", "anti_whipsaw_reentry_gate", "proposal_reference_sheet",
     "satellite_buy_proposal_sheet", "core_satellite_timing_gate_table",
     "engine_feedback_loop_report", "prediction_evaluation_improvement_report",
@@ -75,6 +77,9 @@ SECTION_TITLES = {
     "profit_preservation_table":              "수익 보존 테이블",
     "smart_cash_raise_table":                 "현금 확보 테이블",
     "execution_quality_table":               "체결 품질 테이블",
+    "sell_priority_decision_table":          "매도 우선순위 결정 테이블",
+    "strategy_performance_scoreboard":       "전략 성과 스코어보드",
+    "outcome_eval_window_monitor":           "성과 평가 윈도우 모니터",
     "decision_trace_table":                  "판단 추적 테이블",
     "anti_whipsaw_reentry_gate":             "반등 재진입 감시 게이트",
     "proposal_reference_sheet":              "제안 참조 시트",
@@ -400,6 +405,61 @@ def _qeh_audit_block(hctx: dict, se: list) -> str:
     return _kv(rows)
 
 
+def _sell_priority_decision_table(hctx: dict, se: list) -> str:
+    items = _sj(hctx.get("regime_adjusted_sell_priority_json", []))
+    if not isinstance(items, list) or not items:
+        return _err(se, "sell_priority_decision_table", "regime_adjusted_sell_priority_json 없음")
+    return (f"_총 {len(items)}종목 | 매도 우선순위 결정 (레짐 조정)_\n\n"
+            + _tbl(items, ["rank", "ticker", "name", "tier", "original_score",
+                           "trim_style", "regime_priority_adjustment", "adjustment_reason"], max_rows=15))
+
+
+def _strategy_performance_scoreboard(hctx: dict, se: list) -> str:
+    rows = [
+        ("성과 레이블",      hctx.get("performance_label", "")),
+        ("성과 배수",        hctx.get("performance_multiplier", "")),
+        ("연속 손실 여부",   hctx.get("performance_consecutive_losses", "")),
+        ("30일 승률",        hctx.get("performance_win_rate_30") or "DATA_GATED"),
+        ("30일 순기대값",    hctx.get("performance_net_expectancy_30") or "DATA_GATED"),
+        ("성과 기반 거래",   hctx.get("performance_trades_used", "")),
+    ]
+    sel = _sj(hctx.get("strategy_execution_locks_v1_json", {}))
+    if isinstance(sel, dict) and sel:
+        rows += [
+            ("데이터 무결성 점수", sel.get("data_integrity_score", "")),
+            ("파생 유효성 점수",  sel.get("derivation_validity_score", "")),
+            ("의사결정 증거 게이트", sel.get("decision_evidence_gate", "")),
+            ("결과 품질 점수",    sel.get("outcome_quality_score", "")),
+        ]
+    return _kv(rows)
+
+
+def _outcome_eval_window_monitor(hctx: dict, se: list) -> str:
+    oqs = _sj(hctx.get("outcome_quality_score_v1_json", {}))
+    shom = _sj(hctx.get("short_horizon_outcome_monitor_v1_json", {}))
+    aew = _sj(hctx.get("alpha_evaluation_window_json", []))
+    rows = []
+    if isinstance(oqs, dict) and oqs:
+        rows += [
+            ("결과 품질 점수",  oqs.get("score", "")),
+            ("결과 게이트",     oqs.get("gate", "")),
+            ("평가 근거 플래그", ", ".join(oqs.get("root_cause_flags", []))),
+        ]
+    if isinstance(shom, dict) and shom:
+        m = shom.get("metrics", {})
+        rows += [
+            ("T+1 평가 건수",   m.get("t1_evaluated_count", 0)),
+            ("T+1 일치율(%)",   m.get("t1_match_rate_pct", 0)),
+            ("T+5 평가 건수",   m.get("t5_evaluated_count", 0)),
+            ("T+5 일치율(%)",   m.get("t5_match_rate_pct", 0)),
+        ]
+    if isinstance(aew, list) and aew:
+        rows.append(("평가 윈도우 종목 수", len(aew)))
+    if not rows:
+        return _err(se, "outcome_eval_window_monitor", "평가 윈도우 데이터 없음")
+    return _kv(rows)
+
+
 # ── APPENDIX 렌더러 ────────────────────────────────────────────────────────────
 
 def _backdata_feature_bank_table(hctx: dict, se: list) -> str:
@@ -803,6 +863,9 @@ def main() -> int:
         "profit_preservation_table":              lambda: _profit_preservation_table(hctx, se),
         "smart_cash_raise_table":                 lambda: _smart_cash_raise_table(hctx, se),
         "execution_quality_table":               lambda: _execution_quality_table(hctx, se),
+        "sell_priority_decision_table":          lambda: _sell_priority_decision_table(hctx, se),
+        "strategy_performance_scoreboard":       lambda: _strategy_performance_scoreboard(hctx, se),
+        "outcome_eval_window_monitor":           lambda: _outcome_eval_window_monitor(hctx, se),
         "decision_trace_table":                  lambda: _decision_trace_table(hctx, se),
         "anti_whipsaw_reentry_gate":             lambda: _anti_whipsaw_reentry_gate(hctx, se),
         "proposal_reference_sheet":              lambda: _proposal_reference_sheet(hctx, se),
@@ -836,6 +899,9 @@ def main() -> int:
             "markdown": "\n".join(err_rows),
         })
 
+    _section_names = {s.get("name", "") for s in sections}
+    _eg = _sj(hctx.get("export_gate_json", {}))
+    _json_vs = _eg.get("json_validation_status", "PENDING_EXPORT") if isinstance(_eg, dict) else "PENDING_EXPORT"
     report = {
         "schema_version":      "2026-05-24-operational-report-v1",
         "generated_at":        datetime.now(timezone.utc).isoformat(),
@@ -843,6 +909,12 @@ def main() -> int:
         "section_count":       len(sections),
         "section_error_count": len(se),
         "section_errors":      se,
+        "summary": {
+            "found_routing":              "routing_serving_trace_v2" in _section_names,
+            "found_qeh":                  "QEH_AUDIT_BLOCK" in _section_names,
+            "found_outcome_eval_window":  "outcome_eval_window_monitor" in _section_names,
+            "json_validation_status":     _json_vs,
+        },
         "sections":            sections,
     }