dsh-plugin-j-space
J-Space Cognition Suite V3.6 - Inference-time cognitive control and deep reasoning plugin for DeepSeek Harness (DSH)
- Stars
- 1
- Language
- Python
- Created
- Aug 18, 2026
- Updated
- Aug 18, 2026
Introduction
@custom/dsh-plugin-j-space
J-Space Cognition Suite (V3.6) is an inference-time cognitive control plugin designed for DeepSeek Harness (DSH). It enhances the reasoning fidelity, context persistence, and verification discipline of LLMs (especially DeepSeek-V4-Pro / Flash and Kimi models) during complex, long-horizon tasks.
🌟 Why J-Space?
During long multi-step reasoning, coding, and autonomous workflows, large language models frequently suffer from four major inference-time losses:
- Working-Set Overload: Too many active constraints dilute attention.
- Representation Drift: Global invariants, architectural definitions, or goals gradually mutate across steps.
- Uncontrolled Retry: Repeating failed routes without carrying diagnostic hypotheses.
- Premature Completion: Mistaking fluent conversational output for verified execution.
J-Space turns the model's accessible working memory into a structured, actively managed internal workspace without changing model weights or requiring fine-tuning.
⚙️ 6 Core Cognitive Mechanisms
| Module | Mechanism | Impact |
|---|---|---|
| Broadcast Hub | Shared constraints derived once and broadcast | Prevents cross-file & cross-step representation drift |
| Dense Track | ✓ / ? / ✗ symbol registers with lossless plain-text expansion | Enforces stepwise falsification & rigorous self-verification |
| Directed Focus | Workspace limited to 1-2 active concepts | Eliminates working-set cognitive overload |
| Bridge Reasoning | Mandates intermediate bridging before conclusion | Eliminates conclusion-first rationalization |
| Self-Monitoring | Autonomously detects reasoning degeneration | Triggers rollback with explicit diagnosis |
| Workspace Ledger | Persistent state externalization (jspace.py) | Maintains durable memory across task seams & subagents |
🚀 Installation
Compatible with all operating systems (macOS, Linux, Windows).
Method 1: DSH CLI (Recommended for Local & Server)
Inside your DSH profile or project workspace, run:
# Install directly from GitHub
dsh plugin add github:kolawong/dsh-plugin-j-space
# Or link from a local folder
dsh plugin add ./dsh-plugin-j-space
Method 2: Manual Setup (Local / Server / Container)
If you are cloning manually into your user directory (~/.dsh):
macOS / Linux:
# 1. Clone into your DSH plugins directory
mkdir -p ~/.dsh/plugins ~/.dsh/skills
git clone https://github.com/kolawong/dsh-plugin-j-space.git ~/.dsh/plugins/dsh-plugin-j-space
# 2. Symlink skill to the global skill directory
ln -sfn ~/.dsh/plugins/dsh-plugin-j-space/skills/j-space ~/.dsh/skills/j-space
# 3. Restart DSH
# On local desktop/CLI: restart your 'dsh web' or app process
# On systemd server: systemctl restart deepseek-harness
Windows (PowerShell):
# 1. Clone into your user profile DSH plugins directory
New-Item -ItemType Directory -Force -Path "$HOME\.dsh\plugins", "$HOME\.dsh\skills"
git clone https://github.com/kolawong/dsh-plugin-j-space.git "$HOME\.dsh\plugins\dsh-plugin-j-space"
# 2. Create directory junction for skill
New-Item -ItemType Junction -Path "$HOME\.dsh\skills\j-space" -Target "$HOME\.dsh\plugins\dsh-plugin-j-space\skills\j-space"
# 3. Restart your DSH process
🎛️ 4 Runtime Modes & Activation Policy
You can switch the operating mode in the DSH Web UI (Settings ➔ Plugins ➔ J-Space) or in ~/.dsh/settings.yaml:
j-space:
mode: on-demand # Options: on-demand | always-on | auto | off
- 🎯 On Demand (
on-demand) [Default]: Automatically activated upon explicit user prompts or during complex multi-step reasoning. - ⚡ Always On (
always-on): Global cognitive workspace injected into every turn context. - 🤖 Auto (
auto): Autonomously triggered based on task complexity and code depth. - ⛔ Off (
off): Completely disables the cognitive framework.
💬 Usage Examples
In DSH conversations or Taskboard AI drawer:
- Implicit activation: In
on-demandmode, the model automatically loadsj-spacewhen you ask for architecture refactoring, bug tracing, or theorem proving. - Explicit trigger:
"Use the J-Space cognitive framework to plan and verify this database migration." "Activate J-Space Dense Track to audit cross-file consistency for the auth module."
🌐 Internationalization (i18n)
The plugin UI card (client.js) features built-in automatic language detection (English / 中文), adapting automatically to your DSH locale and browser language without any configuration needed.
🔬 Scientific Background & Original Attribution
This project is built upon empirical research on language-model internal representations and packages the original open-source J-Space Cognition Suite V3.6 by Tiger3807861189 as a standard DeepSeek Harness plugin.
Scientific Foundation
- Gurnee et al., Anthropic (2026) — Research on privileged internal representational workspace ("poised-to-say" representations).
Citation
@software{j_space_cognition_suite_2026,
author = {Tiger3807861189},
title = {J-Space Cognition Suite: Model-Agnostic Inference-Time Control Suite},
year = {2026},
version = {3.6.0},
url = {https://github.com/Tiger3807861189/J-Space-Cognition-Suite-V3.6}
}
📄 License & Open Source Compliance
Licensed under the Apache License, Version 2.0 (the "License").
- You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0.
- Includes upstream work from
J-Space Cognition Suite V3.6(c) 2026 Tiger3807861189. - See the LICENSE and NOTICE files for complete attribution details.