dao-zang-skill
godners-code/dao-zang-skill
道藏知识库离线检索与原文提取:对 28.5 万段经文进行关键词或语义检索,精确提取原文(带行号与命中标记),可从 Godners/DaoZang 数据集一键搭建工作区。
安装
dsh plugin --profile web add github:godners-code/dao-zang-skillREADME
dao-zang-skill
DaoZang offline retrieval & original-text extraction skill for DeepSeek Harness (DSH).
Search 285,117 scripture chunks of the Daoist Canon (《中华道藏》《正统道藏》) by keyword or semantics, and extract exact original text from the source Markdown with line numbers and hit markers. Fully offline — no embedding API, no network needed for retrieval.
Install
dsh plugin --profile web add dao-zang-skill
Or from source:
dsh plugin --profile web add https://github.com/Godners-Code/dao-zang-skill
After install, restart dsh web; type / in the chat input and select
dao-zang, or ask the assistant to "use the dao-zang skill".
What you get
- text engine (default, zero deps): ChromaDB full-text filter + TF/IDF ranking
- semantic engine (optional): local bge-m3 ONNX model, same 1024-dim cosine vectors as the database
- launcher (
daozang.cmd): auto-locates Python and the workspace - self-check (
check_env.py --selftest): environment + smoke query - original-text extraction (
--original): locates the hit in the raw.mdwith⟦...⟧markers and line numbers - file filter (
--source): restrict search to files whose name contains a keyword - one-click workspace setup:
setup_workspace.pydownloads data from the Godners/DaoZang dataset (3,152 markdown files + 6 parquet shards with bge-m3 embeddings) and rebuilds the local ChromaDB offline
Data
The workspace needs ChromaDB/ (285,117 chunks) and Markdowns/ (3,152 files).
Prepare it with:
python assets/dao-zang/scripts/setup_workspace.py --dir <workspace>
See USAGE.md for details.
Distribution packages
Three ready-made installers are available under
dao-zang-plugin releases:
| Version | Install | Package contents |
|---|---|---|
| v1-full | direct copy, no network | skill + ChromaDB + Markdowns |
| v2-hf | download + offline rebuild | skill + Markdowns + HF links for the RAG DB |
| v3-git | clone + download + cleanup | install script + GitHub clone link + HF links |
License
MIT