Daoist Canon (DaoZang) retrieval skill: keyword or semantic search over 285,117 scripture chunks with exact original-text extraction (line numbers, hit markers), and one-command workspace setup from the Godners/DaoZang dataset.
Install
# from npm (prebuilt)
dsh plugin --profile web add dao-zang-skill
# from GitHub (first run asks for allowBuilds approval — follow the hint, retry)
dsh plugin --profile web add github:Godners-Code/dao-zang-skill
Any plugin you install runs third-party code with your own permissions — it can read your files, use your credentials, and reach the network, and tool approvals don’t sandbox it. GitHub-sourced plugins also run build scripts at install time — pnpm blocks those until you allow them, so an install can stop with ERR_PNPM_GIT_DEP_PREPARE_NOT_ALLOWED or ERR_PNPM_IGNORED_BUILDS; dsh prints the exact key to add under allowBuilds in your profile’s pnpm-workspace.yaml, and the install works on the next run. Allowing a build is a trust decision: only install sources you trust, and pin a commit (github:owner/repo#sha).
README
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
Links
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