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dsh-yingnao

Yingnao

Yingnao (硬脑) DeepSeek Harness 插件:让你的代理管理本地磁盘——查看仍未被发现的内容、搜索内容、查找相关内容,并分派可逆且考虑成本的治理任务

插件会安装到这里;不确定时保持 web。

npx -y @deepseek-ai/dsh plugin --profile web add github:qiuyiwu1989-star/dsh-yingnao#ea173bc90a0fa985f101fd89e569e24841ca2ca9
README兼容性版本

兼容性与来源证明

Yingnao 以 dsh-yingnao 发布,当前版本为 0.1.0。Plugin Hub 会校验它的 manifest,并保存精确安装来源,便于复现安装结果。

DSH 兼容范围
*
运行环境
any
发布来源
github
Registry 更新时间
2026/9/7

版本

0.1.0stable
2026/9/7

相关插件

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最新版
0.1.0
DSH
*
HMR
重启进程
Tree shaking
未声明可安全裁剪
解包体积
未提供
文件数
未提供
Surface
any
许可证
MIT
发布源
github
GitHub
★ 1
周下载
0
最近提交
2026/9/22
查看源码 ↗
README Badge

点击下方 Badge 复制 Markdown,粘贴到 README 即可。

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README

dsh-yingnao

Bring Yingnao (硬脑) into DeepSeek Harness.

Yingnao indexes a local disk: your files never move, only the index goes into a database. With this plugin your DSH agent can see how much of that disk is still dark, search it, follow semantic neighbours to material you'd never think to search for, and dispatch governance jobs — instead of only reading dashboards.

Requires Yingnao running locally. https://github.com/qiuyiwu1989-star/yingnao No API key: it manages your own machine. The UI and returned content are in Chinese.

Install

npx -p @deepseek-ai/dsh dsh plugin --profile web add github:qiuyiwu1989-star/dsh-yingnao

Build output ships in the repository, so no dependency build scripts need to be allowed. Restart the profile afterwards.

Start Yingnao's index service (the desktop client does this for you, or run python3 app.py). The plugin talks to http://127.0.0.1:5050 by default.

Six tools

Yingnao's HTTP surface has a dozen-odd endpoints. This plugin registers 6 — a client's job is not to mirror the server, it is to present the right shape. Hand a model a long list of endpoint names and its default strategy becomes "call whichever returns the most", which blows up its own context before it can think about which tool it should have used.

ToolWhen to use it
yingnao_overviewFirst step, before governing anything. How much of the disk is still dark, and how much of what's "processed" is actually usable
yingnao_searchFind files. Degrades rather than fails — files with no extractable text still match on name and path, and say so
yingnao_relatedTake one file, find what's semantically near it. Measurably the most reliable capability here
yingnao_inspectOne file's metadata, body text and quality verdict. Check this before quoting anything
yingnao_governDispatch a governance job, or check progress. This is the hand — and it has a boundary
yingnao_callEscape hatch, not the main road

Why related beats search here

Measured on a real 76k-file archive:

file → file   0.819   two decks genuinely on one thread
query → file  0.639   a good hit
query → file  0.609   a clear miss (matched someone else's memoir)

File-to-file scores run high because both sides are whole documents; a one-sentence query carries far less signal. So the same 0.639 is a good result in search and a weak one in related — the plugin uses two separate vocabularies rather than one shared threshold, because sharing one would mislead both the model and the user.

The practical upshot for an agent: when gathering material, search for one anchor document, then related outward. That surfaces the drafts and earlier versions you would never have thought to query for.

The boundary on yingnao_govern

Two classes of governance action are not the agent's to decide:

  • ones that cost money (OCR re-extraction, LLM labelling)
  • ones that move the user's real files (inbox archiving)

Yingnao marks these needs_confirm. Dispatching one only queues it — it will not run until the user confirms in the desktop client. The tool says so plainly rather than reporting success.

Everything else (quality checks, codepoint normalisation) runs immediately and is reversible: those jobs write a full backup manifest before touching anything.

If you don't want the agent able to dispatch anything at all, set allowGovern: false and yingnao_govern degrades to read-only.

Configuration

- insert:
    - id: yingnao
      name: 'dsh-yingnao'
      config:
        endpoint: 'http://127.0.0.1:5050'   # Yingnao's local index service
        timeoutMs: 60000                    # queries cross an SSH tunnel; can be slow
        passthrough: true                   # false = don't register yingnao_call
        allowGovern: true                   # false = yingnao_govern becomes read-only

YINGNAO_ENDPOINT overrides the endpoint if you'd rather not put it in config.

Errors are classified so the model can act on them

Not a stack trace — a sentence the model can change its behaviour on:

KindWhat the model should do
offlineYingnao isn't running. Retrying won't help — tell the user to open it
tunnelService is up but can't reach the database. May recover; retry once later
notfoundChange the argument, don't retry as-is
serverRetry once; if it keeps failing, tell the user

Pairs with dsh-deepbrain

Install both and one agent holds two complementary layers: judgments with evidence chains from DeepBrain, and the raw material those judgments came from, sitting on your own disk.

"Write me a piece on creativity education" → pull what you've said on it across meetings from DeepBrain → pull the source decks and drafts from Yingnao → write from both.

License

MIT