朱子纯 / xlyNewAi

…i_op_queue staging cols + ai_skill registry

- proposeCreate tool -> ai_op_queue draft(payload) -> confirm executes addBusinessData
- ai_op_queue: add sPayload/sSourceRef/bAutoExecute/sResultBillId/sErrorMsg/tExecutedDate/tExpireAt (create/examine/auto-flow ready)
- ai_skill registry table + seed playbooks (Skills §6)
- QueryTool: self-repair retry (feed SQL error back to model, up to 3x)
- TracingChatModelListener: per-call LLM latency/token/error trace (Langfuse hook point)

- FormResolverService: shared KG resolution (entity->master table excl. viw_*, field 中文->column, name field, labels)
- ErpReadTool.lookupRecord(entity, record): reliably resolves the master table + returns a single record's full labelled fields — fixes the 'specific field of a specific record' case (e.g. 必胜客的销售员 -> 马艺祖)
- AuditService + ai_audit_log: immutable audit of propose/confirm/cancel/query (who/when/action/target/result)
- QueryTool.queryData(question): read-only SQL escape hatch — coder-model NL2SQL grounded on 字段字典, jsqlparser single-SELECT guard, blocks OUTFILE/LOAD_FILE/information_schema/SLEEP, forced LIMIT, audited. SAFE by construction; NL2SQL table/join accuracy for complex questions is limited (architecture-flagged, deferred).

Verified: lookupRecord works; audit rows written; Query guards + LIMIT + audit work (NL2SQL grounding still mis-picks entity master on multi-table questions).