Plugin directory / Developer / dsh-habit
dsh-habit
Unverified Max-Null
What it does
Self-learning habit engine for the DeepSeek Harness - correction signals, threshold judgment, two-level human gate
Unverified — not yet verified
Self-learning habit engine for the DeepSeek Harness - correction signals, threshold judgment, two-level human gate Not yet verified — install and test it yourself.
“Unverified” means our automated CI has not yet installed this plugin. Feature descriptions and version compatibility are the author’s claims. This is not a security audit and not an endorsement of third-party code.
README
@max-null/dsh-habit
本插件属于 @max-null/* 插件系列——这一系列共同构成 SSID(思灵 · Seek Soul in Darkness) 桌面体验。SSID 是整合它们的盒:dsh-capture · dsh-chat-rail · dsh-chinese-thinking · dsh-draft-polish · dsh-guardian · dsh-habit · dsh-header-unify · dsh-memory · dsh-node-appearance · dsh-plugin-center · dsh-skill-mcp-center · dsh-ssid-panels · dsh-ssid-zh-ui。
This plugin belongs to the @max-null/* family — a set of plugins that together form the SSID (思灵 · Seek Soul in Darkness) desktop experience.
Self-learning habit engine for the DeepSeek Harness — observes user-correction
signals from session events, judges habits with a low-cost model on threshold,
and settles candidates behind a two-level human gate. No new agent role: the
judgment is an event-driven plugin, immune to context decay.
The loop
① observe session/event → correction-signal detection (deterministic, zero-token)
② judge >=3 signals in one session → one flash call (evidence slices + existing habits)
③ settle candidate zone → user confirms → dsh-memory remember() (suggested)
→ user confirms again → auto → recall injection
Compose
- id: habit
name: '@max-null/dsh-habit'
Requires storage and llm in the host composition (dsh-base ships both).
Installs as a bundle: dsh plugin --profile <name> add @max-null/dsh-habit.
Service
ctx.habit— the engine:snapshot()→ candidates (newest first)confirm(id)/discard(id)→ first-level human gate- (the second gate is dsh-memory's own suggested→auto confirmation)
Config
| Field | Default | Meaning |
|---|---|---|
signalThreshold |
3 |
Correction signals before one judgment call |
provider |
deepseek-official |
Judgment model provider |
model |
deepseek-v4-flash |
Judgment model (cheap, deterministic) |
storageRoot |
$DSH_HOME/storages/habit |
JSON storage root |
Design notes
- Deterministic observation, LLM on demand: correction detection is a
fixed phrase list + length cap (task descriptions are not corrections);
the LLM only runs when a session accumulates enough signals. - Two-level human gate: candidates must be confirmed in the UI AND then
pass dsh-memory's own suggested→auto gate. The model can never promote its
own habits. - Narrow input for quality: the judgment call gets at most 5 evidence
texts plus the existing habit list — judgment quality comes from precise
context, not volume.
Develop
npm install --legacy-peer-deps
npm test
npm run typecheck
npm run build
SSID 系列
Install
Install the catalog once, then DeepSeek Harness can find and install any plugin from this site automatically:
dsh plugin add dshbase-catalog Then say "install dsh-habit for me" — your agent finds it in the directory and installs it. Docs: dshbase-catalog · verified packs.
This plugin is GitHub source (not published to npm) — install it straight from the repo:
Web profile:
dsh plugin --profile web add github:Max-Null/dsh-habit Headless (CLI) profile:
dsh plugin --profile headless add github:Max-Null/dsh-habit Test report
Not yet L3-verified — see failure note below if we already ran it.