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首席架構師 2026-04-19 Review (92/100 Grade A) 指出 P1 優化:
1. LLM JSON 3-path parse 邏輯在 4 scanner 重複 (~80 行 × 4 = 320 行)
2. coverage red>=20 觸發閾值偏低,生產 bootstrap 必觸發浪費 token
P1.1+1.2 新增 services/llm_json_parser.py (~90 行):
parse_llm_json_response(text, required_key, logger_context)
3-path fallback:
Path 1: 剝 markdown fence + 直接 JSON 含 required_key
Path 2: NemoTron wrapper (description/action_title/reasoning 內嵌 JSON)
Path 3: 所有失敗 return None + logger.warning
失敗永不 raise,呼叫者決定 fallback.
4 個 LLM scanner 改用 helper:
- hermes_rule_quality_job: required_key='recommended_actions'
- capacity_forecaster_job: required_key='priority_actions'
- compliance_scanner_job: required_key='posture_grade'
- coverage_evaluator_job: required_key='worst_dimension'
每個減少約 20 行重複.
P1.3 coverage 觸發條件改雙條件:
原: total_red >= 20 (bootstrap 必觸發)
新: red_ratio > 30% AND total_scanned >= 50
_fetch_red_summary 加 total_scanned 回傳供計算.
5/5 單元測試 parse_llm_json_response:
✅ direct / markdown fence / NemoTron wrapper / invalid / missing key
P1.4 capacity_scanner + rule_catalog_sync: 檢查後已有完整作者註解 (Review 誤判).
其他 P1 (Prom HTTP helper / first_delay 錯開 / LLM budget guard) 留下 session.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>