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asher-2000/dsh-expert-mode

DSH (DeepSeek Harness) 專家模式 agent preset — 首席協調官 + 11 位領域專家子代理 Expert-mode preset for DeepSeek Harness

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MIT

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2026-08-15

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2026-08-19

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README

DSH Expert Mode

🧠 DSH Expert Mode

One agent preset that turns DSH into a "1 Coordinator + 11 Experts" multi-agent team

dsh-plugin Featured in Awesome DSH Plugin License: MIT Stars

中文 · English


✨ What it does

Install this preset and DSH automatically becomes a "Chief Coordinator" mode:

Scenario Behavior
Receives task Identifies domain → delegates to the best expert
Complex tasks Dispatches multiple experts in parallel
Simple tasks Coordinator handles directly — no forced delegation
Task complete Experts stay online for follow-up modifications

No custom prompts to write. No multi-config to maintain. Just install and use.


🖼️ Demo

DSH Expert Mode main interface
Select the "Expert Mode" preset in DSH workspace to use

Expert Mode running
5 expert subagents working in parallel, with real-time token usage and timing


🧩 11 Experts

Expert Tool Domain
📊 Data Analyst expert_data_analyst Data cleaning, statistics, visualization
✍️ Copywriter expert_copywriter Marketing copy, content creation, rewriting
⚖️ Legal Review expert_legal_review Contract review, legal risk assessment
📋 Product Manager expert_product_manager Requirements analysis, PRD writing, competitor research
🖥️ Frontend Dev expert_frontend_dev Web frontend implementation, component development
🎨 UI/UX Design expert_uiux_design Interface design, interaction patterns, design systems
🏗️ Architect expert_architect System design, tech selection, architecture review
📱 Social Media expert_social_media Multi-platform content distribution, account management
🚀 Growth Hacker expert_growth Growth strategy, conversion funnels, A/B testing
💹 Quant Finance expert_quant_finance Quantitative models, financial analysis, risk control
💰 Finance expert_finance Financial analysis, report interpretation, budget planning

🔧 Core Mechanisms

🚀 Quick Path

The Coordinator answers directly without delegating for:

  • Single file read/write/edit
  • Simple Q&A (no domain expertise needed)
  • Casual chat / greetings
  • User says "do it yourself" or "no delegation needed"
  • Task completable with a single command

⚡ Fault Recovery

  • Expert call timeout/failure → auto-retry once
  • 2 consecutive failures → inform user, suggest alternative
  • Expert output clearly off-topic → recall and re-guide

📋 Progressive Disclosure

The Coordinator holds a complete expert methodology index and injects on-demand — not dumping all expert personas into context at startup.

Metric Before After Improvement
Expert persona tokens 3850 chars 533 chars -86%
Total prompt tokens ~2205 ~1582 -28%

🎯 Anchored Non-degradation

Solves the "trajectory flip" problem caused by system prompt mutations:

Anchor Purpose
Style Lock Maintain default reasoning style regardless of context changes
Evidence Priority Every conclusion backed by data/logic
Step-by-step Complex tasks decomposed into single steps
Consistency Check Verify reasoning style matches previous turn
Anti-drift Proactively save state before context window fills

🏗️ Five Anchor Constraints

The Coordinator self-checks five anchor points every turn:

Anchor Purpose
Review One-sentence recap of current subtask
Convergence Confirm this step advanced the goal
Anti-drift 2 turns with no progress → force strategy switch
Collaboration Check Before delegation, verify routing is correct
Resource Awareness Monitor token usage; auto-simplify if >70%

🎯 Near-distance Guidance

During delegation, the Coordinator fills in the structured guidance template:

┌─ Near-distance Guidance ─┐
Identity: You are [expert role]
Task: {specific task description}
Input: {input data}
Output format: [extracted from methodology index]
Completion criteria: {clear delivery standard}
└──────────────────────────┘

Subagents start with clear "who I am, what to do, how to deliver."

🔗 Expert Communication Protocol

When cross-expert collaboration is needed:

[FROM:expert_data_analyst → TO:expert_frontend_dev]
Task: Design frontend data display based on analysis
Data: {Expert A's conclusion summary}

🔍 Cross Review

High-risk tasks (architecture selection, contract review, financial analysis) trigger multi-expert independent review. The Coordinator synthesizes conclusions.

💾 Experience Pool

After completing important tasks, experts extract lessons to .expert-mode/experts/{name}/lessons.md, automatically injected for similar future tasks.

🧠 Expert Persistence

Experts stay online after task completion. The Coordinator can wake them up for follow-up modifications with full context preserved.


📦 Installation

dsh plugin --profile web add github:Asher-2000/dsh-expert-mode

Method 2: git clone

mkdir -p ~/.dsh/.agent-presets
git clone https://github.com/Asher-2000/dsh-expert-mode.git ~/.dsh/.agent-presets/expert-mode

Want English? The repo includes an expert-mode-en/ preset:

cp -r ~/.dsh/.agent-presets/expert-mode/expert-mode-en ~/.dsh/.agent-presets/expert-mode-en

Method 3: Manual download

Download from Releases and place preset.yml + agent.cordis.yml into ~/.dsh/.agent-presets/expert-mode/.


🚀 Usage

After installation, select the Expert Mode preset when creating a new session in DSH Web GUI.


❓ FAQ

Q: Does Expert Mode consume extra model quota? A: Delegating to expert subagents triggers subagent model calls (DSH subagent mechanism), same as the official subagent feature. Simple tasks are handled directly by the Coordinator with no extra calls.

Q: Can I add my own experts? A: Yes. Copy any expert entry in agent.cordis.yml, modify the tool name and persona.

Q: How does it relate to the official standard preset? A: Built on top of the official standard preset combination, preserving the full toolset and only adding the expert delegation layer.


📁 File Structure

.
├── preset.yml              # Preset metadata (name + description)
├── agent.cordis.yml        # Coordinator persona + methodology index + expert tools
├── expert-mode-en/         # English preset
│   ├── preset.yml
│   └── agent.cordis.yml
├── .expert-mode/           # Expert experience pool
│   └── experts/            # Each expert's lessons.md
├── assets/                 # Screenshots
├── README.md               # English
├── README.zh.md            # 中文
└── LICENSE

📝 Changelog

Version Changes
v0.6.0 Quick Path + Fault Recovery + bilingual parity
v0.5.0 Progressive disclosure + anchored non-degradation (tokens -28%)
v0.4.0 Five anchors + near-distance guidance + cross review + experience pool
v0.3.0 Expert persistence + communication protocol
v0.2.0 Basic multi-expert delegation

🏆 Community


🏷️ Tags

dsh deepseek-harness agent-preset expert-mode multi-agent subagent ai-agent dsh-plugin


📄 License

MIT License — see LICENSE.

DSH Plugins 是獨立的 DeepSeek Harness 外掛市集,與 DeepSeek 官方無關,也不代表官方背書。第三方外掛未經安全稽核,安裝前請審查原始碼。

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