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Dao Zang Skill — DSH Plugin for DeepSeek Harness
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dao-zang-skill

Dao Zang Skill

Installable bundle contributing the DaoZang offline retrieval & original-text extraction skill to DeepSeek Harness (v2.0: launcher + self-check + workspace setup)

The plugin will be installed here. Keep web if you are unsure.

npx -y @deepseek-ai/dsh plugin --profile web add github:Godners-Code/dao-zang-skill#bc4387ba06be27e817ebb37ca5d63f4b3c9173fb
READMECompatibilityVersions

Compatibility and provenance

Dao Zang Skill is published as dao-zang-skill and currently resolves to version 2.0.0. The Hub verifies its manifest and preserves the exact installation source for reproducible installs.

DSH compatibility
*
Runtime surfaces
any
Release source
github
Registry updated
8/26/2026

Versions

2.0.0stable
8/26/2026
0.1.0stable
8/24/2026

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Latest
2.0.0
DSH
*
HMR
Process restart
Tree shaking
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Unpacked size
Unavailable
Files
Unavailable
Surface
any
License
MIT
Source
github
GitHub
★ 1
Weekly downloads
0
Last push
8/28/2026
View source ↗
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README

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 .md with ⟦...⟧ markers and line numbers
  • file filter (--source): restrict search to files whose name contains a keyword
  • one-click workspace setup: setup_workspace.py downloads 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:

VersionInstallPackage contents
v1-fulldirect copy, no networkskill + ChromaDB + Markdowns
v2-hfdownload + offline rebuildskill + Markdowns + HF links for the RAG DB
v3-gitclone + download + cleanupinstall script + GitHub clone link + HF links

License

MIT