audit-case-rag
This skill packages a local-only workflow to build a searchable evidence index for a single audit/investigation case and query it with page-level citations.
Workflow
0) Prepare a case folder (事件驱动)
Create a case directory named:
<项目问题编号>__<标题>
Inside, use stage folders (stage is inferred from folder name):
01_policy_basis/(basis) — 制度/流程/授权02_process/(process) — 招采/定标/过程证据03_contract/(contract) — 合同/补充协议04_settlement_payment/(payment) — 结算/付款/发票/验收05_comm/(comm) — 邮件/会议纪要/IM06_interviews/(interview) — 访谈/笔录/询证07_workpapers/(workpaper) — 底稿/抽样/复核表09_rectification/(rectification) — 整改/闭环
Full template: references/case-folder-template.md
1) Install dependencies (local)
From the skill folder (or copy the script into your repo):
python3 -m venv .venv
source .venv/bin/activate
pip install -r scripts/requirements.txt
LibreOffice is recommended for Office→PDF page citations:
sofficemust be available (PATH) or pass--soffice /path/to/soffice.
2) Index the case
./scripts/audit_case_rag.py index \
--case-dir "/path/to/<项目问题编号>__<标题>" \
--out-dir "/path/to/audit_rag_db"
Outputs:
manifest.jsonlwritten into the case directoryaudit_rag_db/<case_id>.joblib(persistent local index)
3) Query with event filters
./scripts/audit_case_rag.py query \
--case "<项目问题编号>" \
--stage payment \
"付款节点是否倒挂?请给出处页码"
Notes:
- Evidence lines include clickable
file://...#page=Ncitations when possible. - Retrieval is hybrid: embedding recall + TF‑IDF rerank (alpha configurable).
Safety/Privacy
- No cloud APIs. Everything runs locally.
- Do not commit outputs (indices, converted PDFs) to git.