原生 DSH 外掛，把 DeepSeek Harness 變成對話式資料分析師：連上資料庫，用自然語言提問，得到基於 SQL 的結論與 HTML 報告。支援 9+ 種資料庫引擎，帶唯讀保護。透過 `dsh plugin --profile web add @yejiming/dsh-data-agent` 安裝。
DSH 整合
原生執行環境
作者聲明
安全稽核
未稽核
最後核實
2026-08-23
授權條款
MIT
01它能幫你完成什麼？
Analyze data by conversation: connect a database and ask business questions in plain language
DSH views the schema, writes and runs SQL against real data, iterates, and returns clear data conclusions and business insights; analysis reports save as offline HTML
Analysts and engineers who run DeepSeek Harness and want to query MySQL/PostgreSQL/SQLite/Oracle/ClickHouse/SQL Server etc. by talking to the agent
02如何將外掛接入 DeepSeek Harness？
先決條件
- DeepSeek Harness with the `dsh plugin` command
- Database client installed for your engine (mysql/psql/sqlcmd etc.) and network access to the target DB
安裝步驟
- 01
Run `dsh plugin --profile web add @yejiming/dsh-data-agent` (or from GitHub: `dsh plugin --profile web add github:omdsh-dev/dsh-data-agent`)
$ dsh plugin --profile web add @yejiming/dsh-data-agent
- 02
Start the web UI with `dsh --profile web`, create a session, pick the '数据模式' (Data Mode) preset, then connect a database in the workbench
$ dsh --profile web
驗證整合成功
作者未說明
復原
- Uninstall with `dsh plugin --profile web remove @yejiming/dsh-data-agent` (also `remove` for desktop and dsh-tui profiles); clear the preset with `rm -rf "$DSH_HOME/.agent-presets/data-agent"` if needed.
03DSH 整合程度與能力邊界
Native DSH plugin that connects databases and lets DeepSeek Harness analyze data by conversation (auto SQL, business insights, HTML reports, read-only protection).
Conversational data analysis
Natural-language business questions→DSH writes and executes SQL, iterates on real results, returns conclusions and business insights
When not in read-only mode the agent can run update/management statements at your requestAI data governance (catalog)
Database schema, columns, comments, relations→AI-proposed business meanings per table/column, confirmed by the user; later queries read them via catalog-search/catalog-get/metric-get
Catalog persists only desensitized source summaries, metadata, versions and human curated meanings — no passwords, credentials, query results or sample rowsHTML analysis reports (render-analysis)
Analysis results→Versioned offline HTML reports (metric/line/bar/pie/scatter/table) saved under analysis-reports/ in the working dir
Reports are atomically saved to the session working dir; the full dashboard is self-contained (inline data/styles/SVG) and opens offline18-tool data protocol
Same 8-tool protocol across web/desktop/dsh-tui/headless→sql-query, sql-write, sql-cmd, render-analysis, catalog-search, catalog-get, metric-get plus str_replace_editor for files
Host/community tools like describe_image and ssh_* do not enter Data Mode
04適合誰？何時不該用？
適合
- Analysts and engineers who run DeepSeek Harness and want to query MySQL/PostgreSQL/SQLite/Oracle/ClickHouse/SQL Server etc. by talking to the agent
不適合
- The plugin and its ecosystem adapters run in-process inside DSH — not an OS, process or realm sandbox. Ecosystem permission only negotiates admission; it does not replace DB account privileges, network isolation or host security policy.
- For production databases, use a read-only DB account and enable read-only mode in the connection form; otherwise the agent can run update/management statements.
- Each engine needs its own CLI client (mysql/psql/sqlcmd/clickhouse HTTP); SQL Server needs Microsoft ODBC sqlcmd 18.x and only supports SQL Login (no Windows/Entra/DSN/named instances).
05相容性、維護與安全提醒
- The plugin and its ecosystem adapters run in-process inside DSH — not an OS, process or realm sandbox. Ecosystem permission only negotiates admission; it does not replace DB account privileges, network isolation or host security policy.
- For production databases, use a read-only DB account and enable read-only mode in the connection form; otherwise the agent can run update/management statements.
- Each engine needs its own CLI client (mysql/psql/sqlcmd/clickhouse HTTP); SQL Server needs Microsoft ODBC sqlcmd 18.x and only supports SQL Login (no Windows/Entra/DSN/named instances).
MIT · 由 facts pack 抓取（README 分支 main）
06常見問題
怎麼安裝 dsh-data-agent？
執行 `dsh plugin --profile web add @yejiming/dsh-data-agent`（或 `github:omdsh-dev/dsh-data-agent`），然後 `dsh --profile web`。新建工作階段選擇「資料模式」預設，並在工作台連接資料庫。
支援哪些資料庫？
MySQL、PostgreSQL、SQLite、Oracle、Hive、Impala、ClickHouse、Apache Doris 與 SQL Server。各引擎需各自的 CLI 用戶端；SQL Server 需要 Microsoft ODBC sqlcmd 18.x，且僅支援 SQL Login。
我的資料庫安全嗎？
外掛在 DSH 程序內執行（非沙箱）。生產環境建議使用唯讀資料庫帳號，並在連線表單開啟唯讀模式；否則智慧體會依你的要求執行更新陳述式。
分析報告長什麼樣？
render-analysis 工具會把帶版本號的、自包含的 HTML 報告（metric/line/bar/pie/scatter/table）寫入工作階段工作目錄的 analysis-reports/，可離線開啟並隨工作階段日誌持久化。
07相關的 DSH 工作流程
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08資料與來源
dsh-data-agent是DeepSeek Harness（DSH）的数据分析插件。
dsh plugin --profile web add @yejiming/dsh-data-agent
此頁面根據專案公開文件、儲存庫中繼資料與 DSH Plugins 的結構化解析所產生；最後核實於 2026-08-23。發現錯誤？提交更正。
最佳 DeepSeek Harness 外掛
從全目錄挑出的 12 個值得優先安裝的外掛，涵蓋各個分類。