DeepSeek Harness plugin

dsh-habit

Self-learning habit engine for the DeepSeek Harness — detects user-correction signals, judges habits with a low-cost model on threshold, settles candidates behind a two-level human gate

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Source facts

Repository
Max-Null/dsh-habit
Latest update
Aug 21, 2026
Category
Security & Permissions
GitHub stars
1
Format
plugin
Catalog evidence
Upstream dsh.bundle evidence
Evidence path
package.json#dsh.bundle
Checked against
0.1.0-rc.8
Upstream check date
2026-08-20

This evidence comes from the upstream catalog. This site has not installed, run, or security-reviewed the plugin.

Install

Start with a prompt that asks an agent to review the GitHub repository and source. Switch to the command if you want to install it yourself.

Copy this prompt into DSH, Codex, or another agent and ask it to review the GitHub repository and source first.

Do not install or run any commands yet. Read this plugin's GitHub repository, README, and relevant source code. Then answer the questions below clearly and directly so I can decide whether it fits my needs:

1. What is this plugin, and what problem does it solve?
2. Who is it for, and what are its typical use cases?
3. How is it used after installation? Include one minimal example.
4. What known limitations or privacy, security, compatibility, or maintenance risks does it have?
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GitHub: https://github.com/Max-Null/dsh-habit
Plugin: dsh-habit
Author: Max-Null

Check the source files

Read the README and other files from this plugin directory before installing.

File explorer2 files
README.mdSource · read only

@max-null/dsh-habit

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

FieldDefaultMeaning
signalThreshold3Correction signals before one judgment call
providerdeepseek-officialJudgment model provider
modeldeepseek-v4-flashJudgment model (cheap, deterministic)
storageRoot$DSH_HOME/storages/habitJSON 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

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-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.