在准备环境前提交次全部更改。

docs/audit/prompt_logs/prompt_log_20260217_040144.md

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+- [P20260217-040144] 2026-02-17 04:01:44 +0800
+  - summary: CONTEXT TRANSFER: We are continuing a conversation that had gotten too long. Here is a summary: --- ## TASK 1: Execute D…
+  - prompt:
+```text
+CONTEXT TRANSFER: We are continuing a conversation that had gotten too long. Here is a summary:
+
+---
+## TASK 1: Execute Dataflow Structure Analysis (数据流结构分析)
+
+**STATUS**: done
+
+**USER QUERIES**: User query 1 ("执行数据流结构分析，按以下步骤完成")
+
+**DETAILS**:
+The user requested a two-phase dataflow structure analysis for the feiqiu (飞球) connector:
+
+**Phase 1 - Data Collection**: Ran `analyze_dataflow.py` to collect API JSON samples, DB schemas, field mappings, and BD descriptions for all 23 ODS tables.
+
+**Phase 2 - Report Generation**: Ran `gen_dataflow_report.py` to generate a comprehensive Markdown report with enhanced content (field diffs, coverage stats, business descriptions, sample values, cross-layer anchor links).
+
+**Key challenge**: The shell's cwd was stuck at `C:\NeoZQYY\apps\etl\pipelines\feiqiu` and couldn't be changed (cd is forbidden). Both scripts require running from project root `C:\NeoZQYY` because they use relative paths for `.env` files and `TABLE_MAP` source parsing.
+
+**Solution**: Created wrapper scripts (`scripts/ops/_run_dataflow.py` and `scripts/ops/_run_report.py`) that use `os.chdir(root)` to set the correct working directory before importing and calling the main functions.
+
+**Results**:
+- Phase 1: 23 tables all successful, 3405 total records collected
+- Phase 2: Report generated at `export/dataflow_analysis/dataflow_2026-02-17_040043.md` (576.6 KB)
+- All intermediate data landed in `export/dataflow_analysis/` subdirectories: `json_trees/`, `db_schemas/`, `field_mappings/`, `bd_descriptions/`, `collection_manifest.json`
+
+**FILEPATHS**:
+- `scripts/ops/analyze_dataflow.py` — CLI entry point for data collection
+- `scripts/ops/dataflow_analyzer.py` — Core collection module (flatten_json_tree, collect_all_tables, dump_collection_results, build_field_mappings, parse_table_map, parse_fact_mappings)
+- `scripts/ops/gen_dataflow_report.py` — Markdown report generator
+- `scripts/ops/_run_dataflow.py` — Wrapper script for Phase 1 (created to solve cwd issue)
+- `scripts/ops/_run_report.py` — Wrapper script for Phase 2 (created to solve cwd issue)
+- `export/dataflow_analysis/dataflow_2026-02-17_040043.md` — Latest generated report
+- `export/dataflow_analysis/collection_manifest.json` — Collection manifest
+
+**NOTE**: The task is complete. The two temporary wrapper scripts (`_run_dataflow.py`, `_run_report.py`) were created as utility helpers and remain in the repo. No high-risk paths were modified, so no audit is required.
+
+## CONTEXT: ODS Dedup Standardize Spec (Background)
+
+**STATUS**: not directly relevant to current task, but provides important context
+
+**DETAILS**: The workspace has an existing spec at `.kiro/specs/ods-dedup-standardize/` with tasks mostly completed (tasks 1-7 done, task 8 in-progress at subtasks 8.4-8.5, task 9 queued). This spec covers ODS dedup and soft-delete standardization. The dataflow analysis task was independent of this spec work.
+
+**USER CORRECTIONS AND INSTRUCTIONS**:
+- Shell cwd is `C:\NeoZQYY\apps\etl\pipelines\feiqiu` — cannot use `cd` command, must use absolute paths or wrapper scripts
+- Scripts that need project root context should use `os.chdir()` in a wrapper
+- Follow `tech.md` script execution rules: prefer Python scripts over complex PowerShell
+- All output in simplified Chinese per `language-zh.md`
+- This was a read-only analysis task (no code changes to high-risk paths), so no `/audit` needed
+
+## Files to read
+- `scripts/ops/_run_dataflow.py`
+- `scripts/ops/_run_report.py`
+- `scripts/ops/analyze_dataflow.py`
+- `scripts/ops/gen_dataflow_report.py`
+- `export/dataflow_analysis/collection_manifest.json`
+
+USER QUERIES(most recent first):
+1. <source-event>
+    The user manually invoked this action
+    The user is focued on the following file: No file focused
+    The user has the following paths open: \apps\etl\pipelines\feiqiu\config\env_parser.py, \apps\etl\pipelines\feiqiu\config\env_parser.py
+</source-event>
+
+执行数据流结构分析，按以下步骤完成：
+
+第一阶段：数据采集
+1. 运行 `python scripts/ops/analyze_dataflow.py` 完成数据采集
+2. 确认采集结果已落盘，包括：
+   - json_trees/（含 samples 多示例值）
+   - db_schemas/
+   - field_mappings/（三层映射 + 锚点）
+   - bd_descriptions/（BD_manual 业务描述）
+   - collection_manifest.json（含 json_field_count）
+
+第二阶段：报告生成
+3. 运行 `python scripts/ops/gen_dataflow_report.py` 生成 Markdown 报告
+4. 报告包含以下增强内容：
+   - 总览表含 API JSON 字段数列
+   - 1.1 API↔ODS↔DWD 字段对比差异报告
+   - 2.3 覆盖率表含业务描述列
+   - API 源字段表含业务描述列 + 多示例值（枚举值解释）
+   - ODS 表结构含业务描述列 + 上下游双向映射锚点链接
+   - DWD 表结构含业务描述列 + ODS 来源锚点链接
+5. 输出文件路径和关键统计摘要
+
+注意：当前仅分析飞球（feiqiu）连接器。未来新增连接器时，应自动发现并纳入分析范围。
+2. <implicit-rules>## Implicit Rules
+You are working on the implementation plan. 
+Ensure each task is actionable, references specific requirements, and focuses only on coding activities. 
+Once approved, inform the user that the spec is complete and they can begin implementing the tasks by opening the tasks.md file.</implicit-rules>
+---
+
+METADATA:
+The previous conversation had 2 messages.
+
+INSTRUCTIONS:
+Continue working until the user query has been fully addressed. Do not ask for clarification - proceed with the work based on the context provided.
+IMPORTANT: you need to read from the files to Read section
+```