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SKILL.md

name deepseek-reasoning
description DeepSeek special model reasoning bridge - Advanced multi-step reasoning via MCP, bridging devuser to deepseek-user for complex problem-solving with structured Chain-of-Thought outputs.
version 1.0.0
author turbo-flow-claude
mcp_server true
protocol mcp-sdk
entry_point mcp-server/server.js
dependencies deepseek-api

DeepSeek Reasoning Skill

Access DeepSeek's special reasoning model endpoint directly from Claude Code with MCP bridge to isolated deepseek-user.

Overview

This skill provides:

  • Advanced reasoning via DeepSeek special model endpoint
  • User isolation - Bridges devuser (Claude Code) to deepseek-user
  • Structured outputs with reasoning traces
  • Multi-step problem solving for complex queries
  • Hybrid AI workflow - Claude as executor, DeepSeek as reasoning planner

Architecture

Claude Code (devuser)
    ↓ MCP Protocol
DeepSeek MCP Server
    ↓ User bridge (sudo -u deepseek-user)
DeepSeek API Client
    ↓ HTTPS
api.deepseek.com/v3.2_speciale_expires_on_20251215

MCP Server

The skill includes an MCP server that exposes DeepSeek reasoning tools:

Tools

  1. deepseek_reason - Complex reasoning with thinking mode

    • Multi-step logical analysis
    • Structured chain-of-thought output
    • Problem decomposition
  2. deepseek_analyze - Code/system analysis with reasoning

    • Bug detection and root cause analysis
    • Architecture evaluation
    • Performance bottleneck identification
  3. deepseek_plan - Task planning with reasoning steps

    • Break down complex tasks
    • Generate execution strategies
    • Identify dependencies and prerequisites

Usage from Claude Code

# Complex reasoning
deepseek_reason "Explain why quicksort is O(n log n) average case but O(n²) worst case"

# Code analysis with reasoning
deepseek_analyze --code "$(cat buggy_code.py)" \
  --issue "Memory leak on repeated calls"

# Task planning
deepseek_plan --goal "Implement distributed cache" \
  --constraints "Must handle 10k req/s, 5 nodes max"

Configuration

API credentials configured via deepseek-user environment:

DEEPSEEK_API_KEY=sk-[your deepseek api key]
DEEPSEEK_SPECIAL_ENDPOINT=https://api.deepseek.com/v3.2_speciale_expires_on_20251215
DEEPSEEK_MODEL=deepseek-chat  # Special model

Set in /home/deepseek-user/.config/deepseek/config.json

Special Model Features

The special endpoint model provides:

  • Required thinking mode - Must explicitly engage reasoning
  • Extended context - Handles complex multi-step problems
  • Structured output - Clear reasoning + conclusion format
  • Metacognitive traces - Shows how the model thinks

Integration with Claude Flow

Hybrid Workflow

Pattern: DeepSeek as Planner, Claude as Executor

  1. Claude receives complex query
  2. Forwards to DeepSeek via MCP for reasoning
  3. DeepSeek returns structured plan with chain-of-thought
  4. Claude executes plan with polished code/responses

Example Flow

Query: "Build a distributed rate limiter"
  ↓
DeepSeek Reasoning:
  - Algorithm: Token bucket vs sliding window
  - Data structure: Redis sorted sets
  - Synchronization: Lua scripts for atomicity
  - Fallback: Local cache on Redis failure
  ↓
Claude Execution:
  - Generates Redis Lua scripts
  - Implements client library
  - Adds error handling and monitoring
  - Writes comprehensive tests

Tools Reference

deepseek_reason

Purpose: Complex multi-step reasoning

Parameters:

  • query (required) - Question requiring reasoning
  • context (optional) - Background information
  • max_steps (optional) - Max reasoning steps (default: 10)
  • format (optional) - Output format: prose|structured|steps (default: structured)

Returns:

{
  "reasoning": {
    "steps": [
      { "step": 1, "thought": "...", "conclusion": "..." },
      { "step": 2, "thought": "...", "conclusion": "..." }
    ],
    "final_answer": "...",
    "confidence": 0.95
  },
  "usage": { "total_tokens": 450 }
}

deepseek_analyze

Purpose: Code/system analysis with root cause reasoning

Parameters:

  • code (required) - Code to analyze
  • issue (required) - Problem description
  • language (optional) - Programming language
  • depth (optional) - Analysis depth: quick|normal|deep (default: normal)

Returns:

{
  "analysis": {
    "root_cause": "...",
    "reasoning_trace": ["...", "...", "..."],
    "recommendations": [{ "priority": "high", "action": "...", "rationale": "..." }]
  },
  "code_issues": [{ "line": 42, "severity": "error", "message": "..." }]
}

deepseek_plan

Purpose: Task planning with dependency analysis

Parameters:

  • goal (required) - What to achieve
  • constraints (optional) - Limitations or requirements
  • context (optional) - Existing system context
  • granularity (optional) - Task size: coarse|medium|fine (default: medium)

Returns:

{
  "plan": {
    "phases": [
      {
        "name": "Phase 1: Setup",
        "tasks": [{ "id": "T1", "description": "...", "dependencies": [], "reasoning": "..." }],
        "reasoning": "Why this phase is needed"
      }
    ],
    "critical_path": ["T1", "T3", "T7"],
    "estimated_complexity": "high"
  }
}

User Isolation

Security: DeepSeek credentials isolated to deepseek-user (UID 1004)

  • MCP server runs as devuser
  • API calls execute as deepseek-user via sudo bridge
  • Credentials never exposed to devuser environment
  • Separate workspace: /home/deepseek-user/workspace

Workflow Examples

Debugging Complex Issue

// Claude Code detects tricky bug
const bug = await readFile("app.js");

// Send to DeepSeek for deep reasoning
const analysis = await deepseek_analyze({
  code: bug,
  issue: "Race condition causing data corruption",
  depth: "deep",
});

// Claude uses reasoning to fix
console.log("Root cause:", analysis.root_cause);
// Implement fix based on recommendations

Algorithm Design

// Complex algorithm design task
const plan = await deepseek_plan({
  goal: "Design consistent hashing for distributed cache",
  constraints: "Min rebalancing on node add/remove, uniform distribution",
});

// Claude implements based on plan
plan.phases.forEach((phase) => {
  phase.tasks.forEach((task) => {
    console.log(`Implementing: ${task.description}`);
    console.log(`Reasoning: ${task.reasoning}`);
    // Generate code here
  });
});

Multi-Step Problem Solving

// Complex reasoning required
const reasoning = await deepseek_reason({
  query: "Why does my ML model overfit on validation but not training data?",
  context: "Using 80/20 split, early stopping, L2 regularization",
  format: "steps",
});

// Claude synthesizes solution
reasoning.steps.forEach((step, i) => {
  console.log(`Step ${i + 1}: ${step.thought}`);
});
console.log("Solution:", reasoning.final_answer);

Performance

  • Response time: 2-5s for typical reasoning queries
  • Token usage: Higher than standard (includes reasoning tokens)
  • Quality: Superior for multi-step logic, debugging, planning
  • Cost: Special endpoint pricing (check DeepSeek docs)

Limitations

  • Requires thinking mode (cannot disable)
  • Special endpoint has expiration (v3.2_speciale_expires_on_20251215)
  • Higher latency than standard deepseek-chat
  • Reasoning tokens count toward usage

Integration Notes

Claude Code Skills

Automatically available when MCP server is running:

  • Tools appear in Claude Code tool list
  • Invoke directly from prompts
  • Streaming support for long reasoning chains

Supervisord Configuration

Add to supervisord.unified.conf:

[program:deepseek-reasoning-mcp]
command=/usr/local/bin/node /home/devuser/.claude/skills/deepseek-reasoning/mcp-server/server.js
directory=/home/devuser/.claude/skills/deepseek-reasoning/mcp-server
user=devuser
environment=HOME="/home/devuser",DEEPSEEK_USER="deepseek-user"
autostart=true
autorestart=true
priority=530
stdout_logfile=/var/log/deepseek-reasoning-mcp.log
stderr_logfile=/var/log/deepseek-reasoning-mcp.error.log

Best Practices

  1. Use for complex reasoning only - Simple queries use Claude directly
  2. Provide context - More background = better reasoning
  3. Check reasoning traces - Understand AI's logic before executing
  4. Hybrid approach - DeepSeek plans, Claude executes
  5. Monitor costs - Reasoning tokens add up quickly

Comparison: DeepSeek vs Claude Reasoning

Aspect DeepSeek Special Claude Sonnet 4.5
Multi-step logic Excellent Very Good
Code generation Good Excellent
Reasoning transparency Explicit traces Implicit
Speed Medium (2-5s) Fast (<1s)
Cost Lower Higher
Best for Planning, analysis Execution, polish

Recommendation: Use both in hybrid workflow for optimal results.

Troubleshooting

"invalid_request_error: non-thinking mode"

  • Special endpoint requires reasoning mode (automatic in this skill)

"Permission denied" errors

  • Check deepseek-user exists (UID 1004)
  • Verify sudo access: devuser ALL=(deepseek-user) NOPASSWD: ALL

Slow responses

  • Normal for reasoning model (includes thinking time)
  • Reduce max_steps if too slow
  • Use format: quick for faster responses

API key errors

  • Verify config: /home/deepseek-user/.config/deepseek/config.json
  • Check API key is valid
  • Ensure special endpoint URL is correct

Advanced Usage

Custom Reasoning Strategies

// Force specific reasoning approach
const result = await deepseek_reason({
  query: "Design database schema for social network",
  context: "Must support 1M users, complex friend relationships",
  strategy: "first_principles", // vs incremental, analogical
  max_steps: 15,
});

Chaining Reasoning

// Multi-stage reasoning
const stage1 = await deepseek_plan({ goal: "Build payment system" });
const stage2 = await deepseek_analyze({
  code: "existing_payment_code.js",
  issue: "Identify integration points",
});

// Claude synthesizes both
const implementation = synthesize(stage1, stage2);

See Also