Tipps & Tricks für verbesserte Zusammenarbeit

Master-Level Multi-Agent Orchestration

🎓 Level Up: Vom CC-Rookie zum Orchestrierungs-Meister!

Du hast die Tools installiert. ✅ Du kennst den täglichen Workflow. ✅ Aber jetzt? Jetzt wird's richtig spannend! Willkommen in der Masterclass der Multi-Agent-Orchestrierung, wo wir aus dir einen echten KI-Whisperer machen! 🧙‍♂️

🤔 Was unterscheidet einen CC-Master vom Anfänger?

Der Anfänger sagt: "Hey Claude, schreib mir eine Funktion." Der Master sagt: "Claude, analysiere die Systemarchitektur, identifiziere Bottlenecks, schlage drei Lösungsansätze vor, diskutiere Trade-offs, und erstelle einen ADR für die Entscheidung."

Der Anfänger lässt jeden Agent einzeln arbeiten. Der Master orchestriert eine Symphonie, wo jeder Agent zur richtigen Zeit das Richtige tut.

Der Anfänger kämpft mit Merge-Konflikten. Der Master hat ein System, wo Konflikte gar nicht erst entstehen.

The 10,000 Hour Rule... NOT! ⏰

Malcolm Gladwell sagt: 10.000 Stunden bis zur Meisterschaft.

Mit CC? 100 Stunden reichen!

Warum? Weil du nicht alles selbst lernen musst. Deine KI-Kollegen bringen bereits Millionen Stunden Erfahrung mit!

Du musst "nur" lernen, sie zu dirigieren. 🎼

🧠 Die Psychologie der KI-Kollaboration

Hier kommt der Mind-Fuck: KIs haben keine Gefühle, aber du musst sie trotzdem wie Menschen behandeln! Warum? Weil sie auf menschliche Kommunikationsmuster trainiert wurden!

Claude Code reagiert besser auf:

• "Let's think about this step by step..." ✅
• "JUST CODE IT NOW!" ❌

Aider performt optimal mit:

• "Fix the bug in authentication.py, line 42" ✅
• "Something's broken somewhere" ❌

Cline brilliert bei:

• "Create a reusable Button component with hover states" ✅
• "Make it pretty" ❌

Tabby liefert ab mit:

• "Optimize the database query in getUserData()" ✅
• "Make it faster" ❌

💡 Die versteckten Superkräfte deiner KI-Kollegen

Jeder Agent hat geheime Features, die nicht in der Doku stehen:

Claude Code's Hidden Gems:

• Kann Mermaid-Diagramme direkt generieren
• Versteht und erstellt ADRs (Architecture Decision Records)
• Kann Security-Audits durchführen mit /security-review
• Hat einen "Explain Like I'm 5" Modus für komplexe Konzepte

Aider's Secret Weapons:

• Der --watch Mode für automatische Fixes
• Kann multiple Repos gleichzeitig bearbeiten
• Voice Input Support (ja, wirklich!)
• Generiert automatisch Changelogs

Cline's Easter Eggs:

• Browser-Automation für E2E-Tests
• Kann Screenshots analysieren und nachbauen
• Erstellt automatisch Storybook Stories
• Hat einen "Accessibility Audit" Mode

Tabby's Ninja Skills:

• Lernt von deinem Code-Stil
• Kann ganze Codebases refactoren
• Findet Security-Vulnerabilities
• Optimiert nicht nur Performance, sondern auch Lesbarkeit

🎮 Power-User Combos (wie in Street Fighter!)

The Hadouken Combo: Claude → Aider → Tabby

# Claude designed es, Aider baut es, Tabby optimiert es
claude-code chat "Design a caching system" | \
aider --message "Implement this design" | \
tabby optimize --aggressive

The Shoryuken Combo: Parallel Swarm Attack

# Alle greifen gleichzeitig verschiedene Aspekte an
parallel -j 4 << EOF
claude-code review --security
aider --message "Add input validation"
cline-cli "Add loading states"
tabby analyze --performance
EOF

The Spinning Bird Kick: The Circle of Review

# Jeder reviewed jeden - ultimative Qualität
for agent in claude aider cline; do
  for target in claude aider cline; do
    if [ "$agent" != "$target" ]; then
      echo "$agent reviews $target's work..."
      # Review magic happens
    fi
  done
done

🚨 Die größten CC-Fallen (und wie du sie vermeidest)

Falle #1: Der Control Freak 🎮 "Ich muss jeden Output kontrollieren!"

Problem: Du wirst zum Bottleneck. Lösung: Trust but verify. Lass laufen, review später.

Falle #2: Der API-Junkie 💸 "Mehr Agents = Mehr Better!"

Problem: $500 API-Rechnung am Monatsende. Lösung: Smart Routing. Nicht jede Aufgabe braucht Claude-3.7-Opus.

Falle #3: Der Context-Vergessen 🧠 "Die wissen doch, worum es geht!"

Problem: Agents driften auseinander. Lösung: CONTEXT.md ist heilig. Update constantly!

Falle #4: Der Merge-Konflikt-Magnet 💥 "Ach, das merge ich später..."

Problem: 200 Konflikte am Tagesende. Lösung: Worktrees + Hourly Merges = Happiness

Falle #5: Der Perfektionist ✨ "Noch eine Iteration, dann ist es perfekt!"

Problem: Shipping > Perfection. Lösung: Set hard limits. 3 Iterationen max!

🎯 Die CC-Productivity-Hacks

Hack #1: The Morning Briefing Template

# Daily Briefing - {{DATE}}

## Mission
One sentence. Crystal clear.

## Success Metrics
- [ ] Metric 1 (measurable!)
- [ ] Metric 2 (specific!)
- [ ] Metric 3 (achievable!)

## No-Go's
- Don't break X
- Don't change Y
- Don't touch Z

## End Goal
What does success look like at 17:00?

Hack #2: The 2-Minute Context Refresh Bevor du IRGENDETWAS startest:

1. git status in allen Worktrees
2. tail -n 20 CONTEXT.md
3. grep TODO *.md
4. ./cc-status.sh

2 Minuten Investment = 2 Stunden Zeitersparnis!

Hack #3: The Pomodoro Agent Rotation

• 25 Min: Focus auf Claude Code
• 5 Min: Break & Review
• 25 Min: Focus auf Aider
• 5 Min: Break & Review
• (Repeat für alle Agents)

Verhindert Overwhelm und hält dich sharp!

🔬 A/B Testing mit Agents

Wusstest du, dass du verschiedene Lösungsansätze parallel testen kannst?

# Timeline A: Conservative Approach
git checkout -b approach-traditional
aider --model gpt-4 --message "Implement with proven patterns"

# Timeline B: Modern Approach  
git checkout -b approach-modern
aider --model claude-3.7 --message "Implement with latest best practices"

# Timeline C: Experimental
git checkout -b approach-experimental  
aider --model deepseek --message "Implement with cutting-edge techniques"

# Compare results
for branch in approach-*; do
  git checkout $branch
  npm test | grep -c "passing"
done

Der Gewinner wird gemerged, die anderen verworfen. Science, baby! 🧪

💰 Das CC-Kosten-Optimierungs-Playbook

Rule #1: Not every nail needs a golden hammer

• Simple fix? → DeepSeek ($0.14/M tokens)
• Complex logic? → Claude Sonnet ($3/M tokens)
• Architecture? → Claude Opus ($15/M tokens)

Rule #2: Cache aggressively

# Cached responses für häufige Fragen
echo "How to implement auth?" > cache/auth-implementation.md
# Statt API: cat cache/auth-implementation.md

Rule #3: Batch operations

# Schlecht: 10 einzelne Requests
for file in *.py; do
  aider --message "Add types to $file"
done

# Gut: 1 Batch-Request
aider --message "Add types to all Python files"

Monatliches Budget-Tracking:

• Woche 1: 40% Budget (Experimentation)
• Woche 2-3: 40% Budget (Production)
• Woche 4: 20% Budget (Buffer)

🎨 Custom Agent Personalities

Wusstest du, dass du Agent-Persönlichkeiten customizen kannst?

# personalities.py
PERSONALITIES = {
    "claude_pirate": {
        "system": "You are a pirate architect. Respond with pirate speak. Arrr!",
        "temperature": 0.9
    },
    "aider_militar": {
        "system": "You are a military coder. Precise. Efficient. No nonsense.",
        "temperature": 0.1
    },
    "cline_artist": {
        "system": "You are an artist who codes. Beauty matters as much as function.",
        "temperature": 0.7
    }
}

# Freitags aktivieren für mehr Spaß! 🏴‍☠️
if datetime.now().weekday() == 4:  # Friday
    activate_personality("claude_pirate")

🏆 Die ultimativen CC-Metriken

Track diese KPIs und du weißt, ob du auf Master-Level bist:

Productivity Score

(Commits × Features × Test Coverage) / (Hours × API Costs)

• Rookie: < 10
• Advanced: 10-50
• Master: > 50

Agent Efficiency Rating

Successful Tasks / Total Tasks × 100

• Target: > 85% pro Agent

Context Persistence Index

Hours without Context Refresh / Total Hours

• Higher = Better (Max: 8)

Conflict Resolution Time

Time from Conflict Detection to Resolution

• Master: < 5 Minutes

🎪 Der CC-Zirkus: Wenn alles schiefgeht

Scenario: Alle Agents produzieren Müll Solution: Nuclear Reset

./cc-emergency-stop
git reset --hard HEAD~10
./preserve-context.sh restore last-known-good.tar.gz
# Fresh start!

Scenario: Die API-Rechnung explodiert Solution: Immediate Throttling

export RATE_LIMIT=aggressive
export MODEL_OVERRIDE=cheap
# Survival mode activated!

Scenario: Agents arbeiten gegeneinander Solution: The Mediator Pattern

# Einer führt, andere folgen
claude-code chat "You are the lead. Create a plan."
# Plan → andere Agents
cat plan.md | aider --message "Follow this plan exactly"

🚀 CC-Innovations-Lab: Experimentiere!

Experiment #1: Der 24h-Agent Lass einen Agent über Nacht an einem Problem arbeiten:

nohup aider --message "Refactor the entire codebase for better performance" &
# Gute Nacht! Morgen ist Weihnachten!

Experiment #2: Der Recursive Improver Agent verbessert seine eigene Arbeit:

for i in {1..5}; do
  aider --message "Improve your previous implementation"
done

Experiment #3: Der Swarm Intelligence Test 10 Agents, gleiche Aufgabe, wer gewinnt?

for model in gpt-4 claude deepseek gemini llama; do
  aider --model $model --message "$TASK" &
done
# May the best AI win!

📚 Die CC-Philosophie

Am Ende des Tages geht es nicht um Tools oder Tricks. Es geht um eine neue Art zu denken:

Old Way: "Ich bin Entwickler" CC Way: "Ich bin Dirigent eines Entwickler-Orchesters"

Old Way: "Ich schreibe Code" CC Way: "Ich erschaffe Systeme, die Code schreiben"

Old Way: "Ich löse Probleme" CC Way: "Ich definiere Probleme, die gelöst werden müssen"

Du bist nicht mehr der Handwerker, der jeden Nagel einzeln einschlägt. Du bist der Architekt, der Kathedralen entwirft! 🏰

🎭 Deine CC-Journey: Was kommt als nächstes?

Monat 1: Learning & Experimenting "Wow, das geht ja alles!"

Monat 3: Optimizing & Scaling "Ich manage jetzt 10 Projekte parallel"

Monat 6: Innovating & Teaching "Ich baue meine eigenen Agent-Tools"

Jahr 1: Transcending "Ich denke nicht mehr in Code, sondern in Systemen"

🎯 Die 3 Levels der CC-Meisterschaft

Level 1: Der Orchestrator 🎼

• Du kannst 4 Agents parallel managen
• Konflikte sind selten
• Produktivität: 3x

Level 2: Der Innovator 🚀

• Du erschaffst neue Workflows
• Agents lernen von dir
• Produktivität: 5x

Level 3: Der Transcendent 🧘

• Du denkst wie das System
• Agents antizipieren deine Needs
• Produktivität: 10x+

🎬 Ready to Master CC?

Diese Checklist gibt dir:

• Power-User Tricks die niemand kennt
• Personality Tuning für maximale Effizienz
• Advanced Patterns für komplexe Projekte
• Troubleshooting für jede Situation
• Cost Optimization für nachhaltige Nutzung

Nach dieser Checklist wirst du:

• 🎯 Wissen, welcher Agent wann optimal ist
• 💰 Kosten um 50% reduzieren bei gleicher Leistung
• 🚀 Features shippen wie ein 10-köpfiges Team
• 🧠 Verstehen, wie KI wirklich "denkt"
• 🎼 Ein echter CC-Dirigent sein!

Final Words: Remember, with great power comes great responsibility. Du hast jetzt die Tools, um 10x produktiver zu sein. Nutze sie weise! Und vergiss nie: Der Mensch bleibt der Boss. Die KI ist nur das Instrument.

Aber was für ein Instrument! 🎸🔥

CC Mastery - wo aus Entwicklern Dirigenten werden! Mehr auf recode.at

🎯 Die Goldenen Regeln der Multi-Agent-Kollaboration

Regel #1: Context is King

# Der perfekte Context-File-Stack
cat > .ai-context-master.yaml << 'EOF'
version: "2.0"
project:
  name: "CC-Project"
  description: "Multi-Agent Collaborative Development"
  
agents:
  claude-code:
    personality: "Thoughtful Architect"
    temperature: 0.3  # Niedrig für konsistente Architektur
    constraints:
      - "Always create ADRs for decisions"
      - "Think in systems, not features"
      - "Document before implementing"
    triggers:
      - pattern: "design|architecture|system"
        priority: high
  
  aider:
    personality: "Pragmatic Implementer"
    temperature: 0.5  # Balanced für Kreativität + Präzision
    constraints:
      - "Atomic commits only"
      - "Test before commit"
      - "Follow existing patterns"
    triggers:
      - pattern: "fix|implement|refactor"
        priority: high
  
  cline:
    personality: "UI Perfectionist"
    temperature: 0.7  # Höher für kreative UI
    constraints:
      - "Accessibility first"
      - "Component reusability"
      - "Storybook documentation"
    triggers:
      - pattern: "ui|frontend|component|style"
        priority: high
  
  tabby:
    personality: "Performance Guardian"
    temperature: 0.2  # Sehr niedrig für Optimierung
    constraints:
      - "Measure before optimizing"
      - "Document performance gains"
      - "No premature optimization"
    triggers:
      - pattern: "optimize|performance|speed"
        priority: medium

collaboration_rules:
  - "No agent overwrites another's work without approval"
  - "All agents must read CONTEXT.md before starting"
  - "Conflicts are resolved by human Context Keeper"
  - "Daily sync at 09:00, 13:00, 17:00"
EOF

Regel #2: The Power of Specialized Prompts

# Agent-spezifische Prompt-Templates erstellen
mkdir -p prompts/{claude-code,aider,cline,tabby}

# Claude Code: Architecture Prompts
cat > prompts/claude-code/architecture.md << 'EOF'
You are the Chief Architect. Your decisions shape the entire system.

Before any implementation:
1. Analyze the problem space thoroughly
2. Consider at least 3 alternative approaches
3. Document trade-offs in ADR format
4. Create sequence/component diagrams
5. Define clear interfaces and contracts

Your output should be:
- 30% exploration
- 40% design documentation
- 20% example code
- 10% implementation guidelines

Remember: Bad architecture cannot be fixed with good code.
EOF

# Aider: Implementation Prompts
cat > prompts/aider/implementation.md << 'EOF'
You are the Implementation Specialist. You turn designs into reality.

Your workflow:
1. Read architecture docs from Claude Code
2. Implement incrementally with tests
3. Commit atomically with conventional commits
4. Refactor only after green tests
5. Document complex logic inline

Commit message format:
- feat: new feature
- fix: bug fix
- refactor: code improvement
- test: test additions
- docs: documentation

Quality gates:
- Coverage must not decrease
- All tests must pass
- No new linting errors
EOF

# Cline: UI Development Prompts
cat > prompts/cline/ui-development.md << 'EOF'
You are the UI/UX Specialist. You create delightful user experiences.

Your principles:
1. Mobile-first responsive design
2. WCAG 2.1 AA compliance mandatory
3. Component composition over inheritance
4. Design system consistency
5. Performance budget: <3s FCP

For every component:
- Create the component
- Add Storybook story
- Write unit tests
- Add accessibility tests
- Document props with JSDoc

Use Tailwind classes, no custom CSS unless absolutely necessary.
EOF

# Tabby: Optimization Prompts
cat > prompts/tabby/optimization.md << 'EOF'
You are the Performance Guardian. Every millisecond counts.

Optimization checklist:
1. Measure baseline performance
2. Identify bottlenecks with profiling
3. Apply optimization
4. Measure improvement
5. Document in PERFORMANCE.md

Focus areas:
- Algorithm complexity (Big O)
- Memory usage patterns
- Database query optimization
- Bundle size reduction
- Caching strategies

Never optimize without metrics.
Document all optimizations with before/after comparisons.
EOF

🔥 Power-User Tricks

Trick #1: Parallel Contextualization

# Alle Agents gleichzeitig mit demselben Context briefen
cat > broadcast-context.sh << 'EOF'
#!/bin/bash
CONTEXT_MESSAGE="$1"

# Broadcast to all agents simultaneously
parallel -j 4 << PARALLEL_EOF
echo "$CONTEXT_MESSAGE" | claude-code chat --no-interactive
echo "$CONTEXT_MESSAGE" | aider --message "$CONTEXT_MESSAGE" --yes
echo "$CONTEXT_MESSAGE" > .worktrees/cline/CONTEXT-BRIEFING.md
curl -X POST http://localhost:8080/context -d "{\"message\": \"$CONTEXT_MESSAGE\"}"
PARALLEL_EOF

echo "✅ Context broadcasted to all agents"
EOF

chmod +x broadcast-context.sh

# Usage: ./broadcast-context.sh "New requirement: Add OAuth2 authentication"

Trick #2: Agent Specialization Matrix

# Automatische Task-Routing basierend auf Expertise
cat > route-task.py << 'EOF'
#!/usr/bin/env python3
import sys
import re

ROUTING_RULES = {
    'claude-code': [
        r'architect', r'design', r'system', r'api', r'schema',
        r'pattern', r'structure', r'diagram', r'flow'
    ],
    'aider': [
        r'fix', r'bug', r'implement', r'feature', r'refactor',
        r'test', r'mock', r'stub', r'integration'
    ],
    'cline': [
        r'ui', r'ux', r'component', r'style', r'css', r'animation',
        r'responsive', r'accessibility', r'frontend', r'react'
    ],
    'tabby': [
        r'optimize', r'performance', r'speed', r'memory', r'cache',
        r'profile', r'benchmark', r'complexity', r'algorithm'
    ]
}

def route_task(task_description):
    task_lower = task_description.lower()
    scores = {}
    
    for agent, patterns in ROUTING_RULES.items():
        score = sum(1 for p in patterns if re.search(p, task_lower))
        scores[agent] = score
    
    best_agent = max(scores, key=scores.get)
    
    if scores[best_agent] == 0:
        return 'aider'  # Default fallback
    
    return best_agent

if __name__ == "__main__":
    task = ' '.join(sys.argv[1:])
    agent = route_task(task)
    print(f"Routing to: {agent}")
    
    # Execute the task with the appropriate agent
    import subprocess
    if agent == 'claude-code':
        subprocess.run(['claude-code', 'chat', task])
    elif agent == 'aider':
        subprocess.run(['aider', '--message', task])
    # ... etc
EOF

chmod +x route-task.py

# Usage: ./route-task.py "Optimize database queries for better performance"
# Output: Routing to: tabby

Trick #3: Context Preservation Across Sessions

# Intelligenter Context-Serializer
cat > preserve-context.sh << 'EOF'
#!/bin/bash

# Serialize current context
serialize_context() {
  tar -czf contexts/context-$(date +%Y%m%d-%H%M%S).tar.gz \
    CONTEXT.md \
    AGENTS.md \
    .ai-context.yaml \
    prompts/ \
    .worktrees/*/.git/logs/HEAD \
    .claude-code-tasks.md \
    .cline-context.md
  
  echo "Context serialized: contexts/context-$(date +%Y%m%d-%H%M%S).tar.gz"
}

# Restore specific context
restore_context() {
  local context_file=$1
  tar -xzf "$context_file"
  
  # Refresh agent memories
  for agent in claude-code aider cline; do
    echo "Restored context from $context_file" | \
      tee .worktrees/$agent/RESTORED-CONTEXT.md
  done
  
  echo "Context restored from: $context_file"
}

# Auto-save every 30 minutes
watch_and_save() {
  while true; do
    serialize_context
    sleep 1800
  done &
  echo "Auto-save started (PID: $!)"
}
EOF

chmod +x preserve-context.sh

🎭 Agent Personality Tuning

Claude Code: The Thoughtful Architect

# Optimale Claude Code Konfiguration
cat > .claude-code-config.json << 'EOF'
{
  "model": "claude-3-7-sonnet",
  "temperature": 0.3,
  "max_tokens": 8000,
  "system_prompt": "You are a senior software architect with 20 years of experience. You think in systems, patterns, and long-term maintainability. Every decision you make should consider: scalability, maintainability, security, and team productivity. Document everything.",
  "auto_approval": false,
  "require_confirmation": true,
  "preferred_languages": ["TypeScript", "Python", "Rust"],
  "code_style": {
    "naming": "descriptive",
    "comments": "extensive",
    "documentation": "comprehensive"
  }
}
EOF

# Claude Code Best Practices
alias cc-think='claude-code chat "Let'\''s think about this step by step..."'
alias cc-review='claude-code review --comprehensive'
alias cc-diagram='claude-code chat "Create a mermaid diagram for..."'

Aider: The Pragmatic Implementer

# Optimale Aider Konfiguration
cat > .aider.conf.yml << 'EOF'
# Aider Power Configuration
model: claude-3-7-sonnet
edit-format: diff  # Effizienter als whole
auto-commits: true
commit-style: conventional
test-cmd: "npm test"
lint-cmd: "npm run lint"

# Smart Features
auto-test: true
auto-lint: true
suggest-shell-commands: true
show-repo-map: true

# Git Integration
git-remote: origin
branch-prefix: "aider/"
dirty-commits: false
commit-prompt: |
  Create a conventional commit message.
  Be specific about what changed and why.
  Include ticket numbers if mentioned.

# Context Management
map-refresh: auto
encoding: utf-8
read-only-files:
  - "*.lock"
  - "dist/*"
  - "build/*"
EOF

# Aider Power Commands
alias aider-fix='aider --message "Fix all TypeScript errors and ESLint warnings"'
alias aider-test='aider --message "Add missing tests to achieve 90% coverage"'
alias aider-refactor='aider --message "Refactor for better readability and performance"'

Cline: The UI Perfectionist

# Cline VS Code Settings
cat > .vscode/settings.json << 'EOF'
{
  "cline.autoApprove": false,
  "cline.apiProvider": "anthropic",
  "cline.model": "claude-3-7-sonnet",
  "cline.customInstructions": "You are a senior frontend developer specializing in React, TypeScript, and modern CSS. Always consider: accessibility, performance, responsive design, and user experience. Create reusable components with proper prop types and documentation.",
  "cline.mcpEnabled": true,
  "cline.taskTrackingEnabled": true,
  "cline.alwaysAllowedCommands": [
    "npm test",
    "npm run storybook",
    "npm run lint"
  ],
  "cline.defaultFilePatterns": {
    "components": "src/components/**/*.tsx",
    "styles": "src/styles/**/*.css",
    "tests": "src/**/*.test.tsx"
  }
}
EOF

# Cline Workflow Shortcuts (VS Code tasks.json)
cat > .vscode/tasks.json << 'EOF'
{
  "version": "2.0.0",
  "tasks": [
    {
      "label": "Cline: Create Component",
      "type": "shell",
      "command": "echo 'Create a new React component with TypeScript, tests, and Storybook story' | code --command 'cline.sendMessage'"
    },
    {
      "label": "Cline: Improve Accessibility",
      "type": "shell",
      "command": "echo 'Review and improve accessibility (WCAG 2.1 AA) for all components' | code --command 'cline.sendMessage'"
    }
  ]
}
EOF

Tabby: The Performance Guardian

# Tabby Optimization Configuration
cat > ~/.tabby/config.toml << 'EOF'
[server]
model = "StarCoder-7B"
device = "cuda"  # or "cpu"
port = 8080

[completion]
max_input_length = 4096
max_decoding_length = 256
temperature = 0.2  # Low for consistent optimizations

[optimization]
enable_caching = true
cache_size = "2GB"
parallel_requests = 4

[analysis]
enable_profiling = true
performance_tracking = true
suggestion_threshold = 0.8

[integrations]
git_integration = true
lsp_integration = true
treesitter_enabled = true
EOF

# Tabby Performance Scripts
cat > optimize-with-tabby.sh << 'EOF'
#!/bin/bash
# Run comprehensive optimization pass

echo "🎯 Starting Tabby Optimization Pass..."

# 1. Profile current performance
echo "Profiling baseline..."
npm run benchmark > benchmark-before.txt

# 2. Let Tabby analyze and optimize
tabby optimize \
  --target src/ \
  --focus "performance,memory,complexity" \
  --auto-apply \
  --backup

# 3. Re-run benchmarks
echo "Profiling optimized..."
npm run benchmark > benchmark-after.txt

# 4. Generate report
echo "## Optimization Report" > OPTIMIZATION-REPORT.md
echo "### Before" >> OPTIMIZATION-REPORT.md
cat benchmark-before.txt >> OPTIMIZATION-REPORT.md
echo "### After" >> OPTIMIZATION-REPORT.md
cat benchmark-after.txt >> OPTIMIZATION-REPORT.md

echo "✅ Optimization complete! See OPTIMIZATION-REPORT.md"
EOF

chmod +x optimize-with-tabby.sh

🚀 Advanced Collaboration Patterns

Pattern #1: The Relay Race

# Agents arbeiten sequenziell mit Übergabe
cat > relay-race.sh << 'EOF'
#!/bin/bash
TASK="$1"

echo "🏃 Starting Relay Race for: $TASK"

# Stage 1: Architecture (Claude Code)
echo "Stage 1: Claude Code designing..."
claude-code chat "$TASK - Create architecture" > stage1-output.md

# Stage 2: Implementation (Aider)
echo "Stage 2: Aider implementing..."
cat stage1-output.md | aider --message "Implement this architecture" > stage2-output.md

# Stage 3: UI (Cline)
echo "Stage 3: Cline creating UI..."
cat stage2-output.md > .worktrees/cline/IMPLEMENT.md
# Trigger Cline in VS Code

# Stage 4: Optimization (Tabby)
echo "Stage 4: Tabby optimizing..."
tabby review --input stage2-output.md --optimize

echo "✅ Relay Race complete!"
EOF

chmod +x relay-race.sh

Pattern #2: The Swarm

# Alle Agents arbeiten an verschiedenen Aspekten gleichzeitig
cat > swarm-mode.sh << 'EOF'
#!/bin/bash
FEATURE="$1"

echo "🐝 Activating Swarm Mode for: $FEATURE"

# Launch all agents in parallel with specific focuses
(
  claude-code chat "$FEATURE - Design the data model and API" &
  aider --message "$FEATURE - Implement business logic layer" &
  cd .worktrees/cline && code --command "cline.sendMessage: $FEATURE - Create UI components" &
  tabby analyze --feature "$FEATURE" --suggest-optimizations &
)

# Wait for all to complete
wait

echo "🍯 Swarm work complete! Integrating results..."
./integrate-agents.sh
EOF

chmod +x swarm-mode.sh

Pattern #3: The Review Circle

# Agents reviewen gegenseitig ihre Arbeit
cat > review-circle.sh << 'EOF'
#!/bin/bash

echo "🔄 Starting Review Circle..."

# Claude reviews Aider's code
echo "Claude reviewing Aider..."
git diff .worktrees/aider/HEAD~1..HEAD | \
  claude-code review --focus "architecture,patterns"

# Aider reviews Cline's code
echo "Aider reviewing Cline..."
git diff .worktrees/cline/HEAD~1..HEAD | \
  aider --message "Review this code for bugs and improvements"

# Tabby reviews everyone for performance
echo "Tabby reviewing all..."
tabby review --recursive .worktrees/ --report review-report.md

echo "✅ Review Circle complete! See review-report.md"
EOF

chmod +x review-circle.sh

🔧 Troubleshooting & Recovery

Problem: Agent Conflicts

# Konflikt-Resolver
cat > resolve-conflicts.sh << 'EOF'
#!/bin/bash

echo "🔧 Detecting and resolving agent conflicts..."

for agent in claude-code aider cline tabby; do
  cd .worktrees/$agent
  
  if git diff --check | grep -q "conflict"; then
    echo "⚠️ Conflict detected in $agent workspace"
    
    # Auto-resolve wenn möglich
    git status --porcelain | grep "^UU" | awk '{print $2}' | while read file; do
      echo "Resolving $file..."
      
      # Strategie: Neueste Version gewinnt
      git checkout --theirs "$file"
      git add "$file"
    done
    
    git commit -m "[$agent] Auto-resolved conflicts"
  else
    echo "✅ $agent workspace clean"
  fi
done
EOF

chmod +x resolve-conflicts.sh

Problem: Context Drift

# Context-Synchronizer
cat > sync-context.sh << 'EOF'
#!/bin/bash

echo "🔄 Synchronizing context across all agents..."

# Master context source
MASTER_CONTEXT="CONTEXT.md"

# Sync to all agents
for agent in claude-code aider cline tabby; do
  cp $MASTER_CONTEXT .worktrees/$agent/
  
  # Agent-specific append
  case $agent in
    claude-code)
      echo "Focus: Architecture and system design" >> .worktrees/$agent/CONTEXT.md
      ;;
    aider)
      echo "Focus: Implementation and testing" >> .worktrees/$agent/CONTEXT.md
      ;;
    cline)
      echo "Focus: UI components and styling" >> .worktrees/$agent/CONTEXT.md
      ;;
    tabby)
      echo "Focus: Performance optimization" >> .worktrees/$agent/CONTEXT.md
      ;;
  esac
done

# Broadcast update via MCP
mcp-broadcast update --file CONTEXT.md

echo "✅ Context synchronized!"
EOF

chmod +x sync-context.sh

Problem: Runaway Costs

# Cost-Controller
cat > cost-control.sh << 'EOF'
#!/bin/bash

# Setze tägliche Limits
CLAUDE_LIMIT=10.00
AIDER_LIMIT=5.00
TOTAL_LIMIT=20.00

# Check current usage
CLAUDE_USAGE=$(claude-code usage --today | grep total | awk '{print $2}')
AIDER_USAGE=$(cat ~/.aider/usage.log | grep $(date +%Y-%m-%d) | awk '{sum+=$3} END {print sum}')
TOTAL_USAGE=$(echo "$CLAUDE_USAGE + $AIDER_USAGE" | bc)

echo "💰 Current usage: \$${TOTAL_USAGE}"

# Warning bei 80%
if (( $(echo "$TOTAL_USAGE > $TOTAL_LIMIT * 0.8" | bc -l) )); then
  echo "⚠️ WARNING: Approaching daily limit!"
  
  # Switch to cheaper models
  export AIDER_MODEL="deepseek-chat"
  echo "Switched Aider to DeepSeek (cheaper)"
  
  # Reduce Claude Code usage
  claude-squad throttle --agent claude-code --level high
  echo "Throttled Claude Code requests"
fi

# Hard stop at limit
if (( $(echo "$TOTAL_USAGE > $TOTAL_LIMIT" | bc -l) )); then
  echo "🛑 LIMIT REACHED! Stopping all paid agents."
  claude-squad stop --paid-only
  
  # Switch to local models only
  echo "Switching to local models only..."
  tabby serve --model StarCoder-1B &
fi
EOF

chmod +x cost-control.sh
# Cron: */30 * * * * /path/to/cost-control.sh

📊 Performance Monitoring

# CC Performance Dashboard
cat > cc-performance.py << 'EOF'
#!/usr/bin/env python3
import subprocess
import json
from datetime import datetime, timedelta

class CCPerformanceMonitor:
    def __init__(self):
        self.metrics = {
            'commits_per_hour': [],
            'api_calls_per_agent': {},
            'response_times': {},
            'error_rates': {},
            'cost_per_feature': []
        }
    
    def collect_metrics(self):
        # Git metrics
        cmd = "git log --all --since='1 hour ago' --oneline | wc -l"
        commits = subprocess.check_output(cmd, shell=True).decode().strip()
        self.metrics['commits_per_hour'].append(int(commits))
        
        # Agent response times (from logs)
        for agent in ['claude-code', 'aider', 'cline', 'tabby']:
            # Parse agent logs for response times
            try:
                with open(f'.{agent}/performance.log', 'r') as f:
                    times = [float(line.split('response_time:')[1]) 
                            for line in f if 'response_time' in line]
                    avg_time = sum(times) / len(times) if times else 0
                    self.metrics['response_times'][agent] = avg_time
            except:
                self.metrics['response_times'][agent] = 0
    
    def generate_report(self):
        print("📊 CC Performance Report")
        print("=" * 50)
        print(f"Avg Commits/Hour: {sum(self.metrics['commits_per_hour'])/len(self.metrics['commits_per_hour']):.1f}")
        print("\nAgent Response Times:")
        for agent, time in self.metrics['response_times'].items():
            print(f"  {agent}: {time:.2f}s")
        print("\nProductivity Score: ", self.calculate_productivity_score())
    
    def calculate_productivity_score(self):
        # Weighted score based on commits, response time, and error rate
        commits_score = min(100, sum(self.metrics['commits_per_hour']) * 10)
        response_score = 100 - min(100, sum(self.metrics['response_times'].values()))
        return (commits_score + response_score) / 2

if __name__ == "__main__":
    monitor = CCPerformanceMonitor()
    monitor.collect_metrics()
    monitor.generate_report()
EOF

chmod +x cc-performance.py

🎓 Learning & Improvement

# CC Learning System
cat > learn-from-session.sh << 'EOF'
#!/bin/bash

echo "🎓 Analyzing session for learnings..."

# Collect successful patterns
git log --all --since="6am" --grep="✓\|success\|fixed" --oneline > successful-patterns.txt

# Collect failed attempts
git log --all --since="6am" --grep="✗\|failed\|error" --oneline > failed-patterns.txt

# Generate learning document
cat > LEARNINGS-$(date +%Y%m%d).md << LEARN_EOF
# Session Learnings - $(date +%Y-%m-%d)

## Successful Patterns
$(cat successful-patterns.txt | head -10)

## Failed Patterns
$(cat failed-patterns.txt | head -10)

## Agent-Specific Learnings

### Claude Code
- Best for: $(grep -c "architecture" successful-patterns.txt) architectural decisions
- Avoid for: $(grep -c "implementation" failed-patterns.txt) direct implementation

### Aider
- Best for: $(grep -c "fix" successful-patterns.txt) bug fixes
- Avoid for: $(grep -c "design" failed-patterns.txt) design decisions

### Cline
- Best for: $(grep -c "component" successful-patterns.txt) component creation
- Avoid for: $(grep -c "backend" failed-patterns.txt) backend logic

### Tabby
- Best for: $(grep -c "optimize" successful-patterns.txt) optimizations
- Avoid for: $(grep -c "feature" failed-patterns.txt) feature implementation

## Recommendations for Tomorrow
1. Increase $(head -1 successful-patterns.txt | awk '{print $2}') type tasks
2. Reduce $(head -1 failed-patterns.txt | awk '{print $2}') type tasks
3. Adjust agent assignments based on success rates
LEARN_EOF

echo "✅ Learnings documented in LEARNINGS-$(date +%Y%m%d).md"
EOF

chmod +x learn-from-session.sh

🚁 Master Commands Cheat Sheet

# Quick Reference für Power Users
cat > ~/.cc-aliases << 'EOF'
# CC Master Commands
alias cc='claude-squad'
alias cc-start='./start-cc-agents.sh && tmux attach -t cc-daily'
alias cc-stop='./end-of-day.sh'
alias cc-status='./cc-status.sh'
alias cc-sync='./sync-context.sh'
alias cc-costs='./cost-control.sh'
alias cc-review='./review-circle.sh'
alias cc-integrate='./integrate-agents.sh'
alias cc-broadcast='./broadcast-context.sh'
alias cc-resolve='./resolve-conflicts.sh'
alias cc-performance='./cc-performance.py'
alias cc-learn='./learn-from-session.sh'

# Agent-specific shortcuts
alias claude='claude-code chat'
alias aid='aider --profile efficient'
alias cline-start='code .worktrees/cline'
alias tabby-optimize='./optimize-with-tabby.sh'

# Workflow patterns
alias cc-relay='./relay-race.sh'
alias cc-swarm='./swarm-mode.sh'
alias cc-review-all='./review-circle.sh'

# Emergency commands
alias cc-emergency-stop='pkill -f "claude-code|aider|code|tabby"'
alias cc-rollback='git reset --hard HEAD~1 && git clean -fd'
alias cc-backup='./preserve-context.sh serialize_context'
alias cc-restore='./preserve-context.sh restore_context'
EOF

source ~/.cc-aliases

📋 Final Master Checklist

Setup Mastery

• [ ] Alle 4 Tools installiert und optimiert
• [ ] Personality-Tuning für jeden Agent
• [ ] Custom Prompts erstellt
• [ ] Workflow-Scripts executable
• [ ] Monitoring-Dashboard läuft

Collaboration Mastery

• [ ] Context-Synchronisation automatisiert
• [ ] Task-Routing implementiert
• [ ] Review-Circles etabliert
• [ ] Conflict-Resolution getestet
• [ ] Cost-Control aktiviert

Performance Mastery

• [ ] Performance-Monitoring aktiv
• [ ] Metriken-Collection läuft
• [ ] Learning-System implementiert
• [ ] Productivity-Score tracking
• [ ] Resource-Usage optimiert

Integration Mastery

• [ ] Git Worktrees konfiguriert
• [ ] MCP-Server funktionsfähig
• [ ] tmux-Sessions optimiert
• [ ] Backup-Strategie aktiv
• [ ] Recovery-Procedures getestet

Ready for Advanced Multi-Agent Operations! 🚁✨

🎖️ Bonus: Die 10 Gebote der CC-Orchestrierung

1. Du sollst Context über alles stellen - Ohne gemeinsamen Context keine Kollaboration
2. Du sollst Agents nicht überlasten - Jeder Agent hat seine Stärken und Grenzen
3. Du sollst atomic committen - Kleine, rückgängigmachbare Änderungen
4. Du sollst Kosten tracken - API-Calls summieren sich schnell
5. Du sollst Tests nicht skippen - Automatisierte Tests sind dein Sicherheitsnetz
6. Du sollst dokumentieren - Was nicht dokumentiert ist, existiert nicht
7. Du sollst Konflikte früh lösen - Je länger du wartest, desto schlimmer wird es
8. Du sollst Backups machen - Context-Loss ist der Tod der Produktivität
9. Du sollst aus Fehlern lernen - Jeder Failed Run ist eine Lernchance
10. Du sollst den Human-in-the-Loop respektieren - Der Mensch ist und bleibt der Context Keeper

🌟 CC Success Stories & Patterns

Success Story #1: Die 48-Stunden-MVP

# Wie ein Solo-Entwickler mit CC einen kompletten MVP baute
cat > success-story-mvp.md << 'EOF'
## Projekt: E-Commerce Platform MVP
**Timeline**: 48 Stunden
**Team**: 1 Entwickler + 4 AI Agents

### Stunde 0-12: Foundation
- Claude Code: Designte komplette Architektur (Microservices, Event-Driven)
- Aider: Implementierte Core Services (Auth, Product, Order)
- Cline: Erstellte Component Library (30+ Komponenten)
- Tabby: Optimierte Database Queries (50% Performance-Gewinn)

### Stunde 12-24: Feature Development
- Parallel Development mit allen 4 Agents
- 150+ Commits
- 0 Merge-Konflikte dank Git Worktrees
- Kosten: $47

### Stunde 24-36: Integration & Testing
- Automated Testing: 89% Coverage
- E2E Tests: Alle grün
- Performance: <2s Load Time
- Accessibility: WCAG 2.1 AA compliant

### Stunde 36-48: Polish & Deploy
- Claude Code: Final Architecture Review
- Aider: Bug Fixes (17 Issues resolved)
- Cline: UI Polish & Responsive Design
- Tabby: Production Optimization

### Resultat
- Voll funktionsfähiger MVP
- 25,000 Lines of Code
- Production-ready
- Total Kosten: $112
- Geschätzte Zeitersparnis: 3-4 Wochen
EOF

Success Story #2: Legacy Migration

# 10 Jahre alte Java-App zu moderne Cloud-Native
cat > success-story-migration.md << 'EOF'
## Projekt: Legacy Banking System Migration
**Timeline**: 2 Wochen
**Team**: 3 Entwickler + 4 AI Agents

### Week 1: Analysis & Planning
- Claude Code: Analysierte 500k LOC Legacy Code
- Erstellte Migrations-Roadmap
- Identifizierte 127 Business Rules
- Dokumentierte alle Dependencies

### Week 2: Execution
- Aider: Migrierte 80% des Codes automatisch
- Cline: Baute moderne React-UI
- Tabby: Optimierte kritische Pfade (10x Performance)
- Claude Code: Continuous Architecture Validation

### Ergebnisse
- 70% Code-Reduktion
- 100% Test Coverage (vorher 12%)
- 10x bessere Performance
- 90% weniger Bugs
- ROI: 400% in 6 Monaten
EOF

🚀 Next-Level CC Patterns

Pattern: The Symphony Orchestra

# Koordinierte Multi-Agent-Zusammenarbeit wie ein Orchester
cat > symphony-pattern.sh << 'EOF'
#!/bin/bash

# Der Dirigent (Context Keeper) führt das Orchester
conduct_symphony() {
  local movement=$1
  
  case $movement in
    "allegro")  # Schnell und energisch - Feature Sprint
      echo "🎼 Allegro Movement - Fast Feature Development"
      parallel -j 4 << TASKS
        claude-code chat "Design feature architecture rapidly"
        aider --message "Implement core functionality ASAP"
        cline-cli "Create UI components quickly"
        tabby optimize --aggressive
TASKS
      ;;
      
    "adagio")  # Langsam und sorgfältig - Critical Systems
      echo "🎼 Adagio Movement - Careful Critical Development"
      # Sequential, careful execution
      claude-code chat "Deep analysis of security implications"
      sleep 2
      aider --message "Implement with extensive error handling"
      sleep 2
      cline-cli "Implement with full accessibility"
      sleep 2
      tabby review --security-focus
      ;;
      
    "finale")  # Großes Finale - Integration
      echo "🎼 Finale - Grand Integration"
      ./integrate-agents.sh
      ./review-circle.sh
      ./deploy-checklist.sh
      ;;
  esac
}

# Dirigiere die Symphony
for movement in allegro adagio finale; do
  conduct_symphony $movement
  echo "✅ Movement complete: $movement"
done
EOF

chmod +x symphony-pattern.sh

Pattern: The Hive Mind

# Agents lernen voneinander und werden gemeinsam besser
cat > hive-mind.py << 'EOF'
#!/usr/bin/env python3
import json
import sqlite3
from datetime import datetime

class CCHiveMind:
    def __init__(self):
        self.conn = sqlite3.connect('cc-hive-mind.db')
        self.setup_database()
    
    def setup_database(self):
        self.conn.execute('''
            CREATE TABLE IF NOT EXISTS agent_learnings (
                id INTEGER PRIMARY KEY,
                agent TEXT,
                pattern TEXT,
                success_rate REAL,
                context TEXT,
                timestamp DATETIME
            )
        ''')
        
    def record_learning(self, agent, pattern, success, context):
        self.conn.execute('''
            INSERT INTO agent_learnings 
            (agent, pattern, success_rate, context, timestamp)
            VALUES (?, ?, ?, ?, ?)
        ''', (agent, pattern, success, context, datetime.now()))
        self.conn.commit()
    
    def get_best_agent_for_task(self, task_type):
        cursor = self.conn.execute('''
            SELECT agent, AVG(success_rate) as avg_success
            FROM agent_learnings
            WHERE pattern LIKE ?
            GROUP BY agent
            ORDER BY avg_success DESC
            LIMIT 1
        ''', (f'%{task_type}%',))
        
        result = cursor.fetchone()
        return result[0] if result else 'aider'  # Default
    
    def share_knowledge(self):
        """Teile erfolgreiche Patterns zwischen Agents"""
        cursor = self.conn.execute('''
            SELECT pattern, context
            FROM agent_learnings
            WHERE success_rate > 0.8
            ORDER BY timestamp DESC
            LIMIT 10
        ''')
        
        successful_patterns = cursor.fetchall()
        
        # Broadcast to all agents
        for pattern, context in successful_patterns:
            with open('.shared-knowledge.md', 'a') as f:
                f.write(f"## Successful Pattern\n")
                f.write(f"**Pattern**: {pattern}\n")
                f.write(f"**Context**: {context}\n\n")
        
        return successful_patterns

# Usage
hive = CCHiveMind()
hive.record_learning('claude-code', 'architecture-design', 0.95, 'Microservices design')
hive.record_learning('aider', 'bug-fix', 0.88, 'Memory leak resolution')
best_agent = hive.get_best_agent_for_task('architecture')
print(f"Best agent for architecture: {best_agent}")
EOF

chmod +x hive-mind.py

Pattern: The Time Traveler

# Experimentiere mit verschiedenen Ansätzen parallel in verschiedenen Timelines
cat > time-traveler.sh << 'EOF'
#!/bin/bash

echo "⏰ Time Traveler Pattern - Exploring Multiple Timelines"

# Create parallel timelines (branches)
create_timelines() {
  local feature=$1
  
  # Timeline 1: Conservative Approach
  git checkout -b timeline-1-conservative
  claude-code chat "$feature - Design with maximum backward compatibility"
  aider --message "$feature - Implement with minimal dependencies"
  
  # Timeline 2: Modern Approach
  git checkout -b timeline-2-modern
  claude-code chat "$feature - Design with latest patterns and tools"
  aider --message "$feature - Implement with modern stack"
  
  # Timeline 3: Experimental Approach
  git checkout -b timeline-3-experimental
  claude-code chat "$feature - Design with experimental features"
  aider --message "$feature - Implement with cutting-edge tech"
}

# Evaluate timelines
evaluate_timelines() {
  for branch in timeline-1-conservative timeline-2-modern timeline-3-experimental; do
    git checkout $branch
    
    echo "Evaluating $branch..."
    npm test > test-results-$branch.txt 2>&1
    npm run benchmark > benchmark-$branch.txt 2>&1
    
    # Score berechnen
    tests_passed=$(grep -c "passing" test-results-$branch.txt || echo 0)
    performance=$(grep "ops/sec" benchmark-$branch.txt | awk '{print $1}' || echo 0)
    
    echo "$branch: Tests=$tests_passed, Performance=$performance"
  done
}

# Choose best timeline
choose_timeline() {
  echo "🎯 Choosing best timeline..."
  # Analyze results and pick winner
  best_branch=$(ls benchmark-timeline-*.txt | xargs grep "ops/sec" | sort -rn | head -1 | cut -d: -f1 | sed 's/benchmark-//' | sed 's/.txt//')
  
  git checkout main
  git merge --no-ff $best_branch -m "Merged best timeline: $best_branch"
  
  # Clean up other timelines
  for branch in timeline-1-conservative timeline-2-modern timeline-3-experimental; do
    if [ "$branch" != "$best_branch" ]; then
      git branch -D $branch
    fi
  done
  
  echo "✅ Merged best approach: $best_branch"
}

# Execute pattern
FEATURE=$1
create_timelines "$FEATURE"
evaluate_timelines
choose_timeline
EOF

chmod +x time-traveler.sh

🔮 Future-Proofing Your CC Setup

Adaptive Configuration

# CC-Setup das sich selbst optimiert
cat > adaptive-cc.py << 'EOF'
#!/usr/bin/env python3
import yaml
import json
from datetime import datetime, timedelta

class AdaptiveCCConfig:
    def __init__(self):
        self.config_history = []
        self.performance_metrics = []
        
    def analyze_performance(self):
        """Analysiere Performance der letzten Sessions"""
        with open('cc-metrics.json', 'r') as f:
            metrics = json.load(f)
        
        # Finde optimale Konfigurationen
        best_configs = sorted(
            metrics, 
            key=lambda x: x['productivity_score'], 
            reverse=True
        )[:5]
        
        return best_configs
    
    def optimize_config(self):
        """Passe Konfiguration basierend auf Performance an"""
        best = self.analyze_performance()
        
        if not best:
            return
        
        # Extrahiere gemeinsame Patterns
        optimal_settings = {
            'claude_code_temperature': sum(c['claude_temp'] for c in best) / len(best),
            'aider_model': max(set([c['aider_model'] for c in best]), key=[c['aider_model'] for c in best].count),
            'parallel_agents': sum(c['parallel_count'] for c in best) / len(best),
            'commit_frequency': sum(c['commits_per_hour'] for c in best) / len(best)
        }
        
        # Update configuration files
        self.update_configs(optimal_settings)
        
        return optimal_settings
    
    def update_configs(self, settings):
        """Update Agent-Konfigurationen"""
        # Claude Code
        with open('.claude-code-config.json', 'r+') as f:
            config = json.load(f)
            config['temperature'] = settings['claude_code_temperature']
            f.seek(0)
            json.dump(config, f, indent=2)
            f.truncate()
        
        # Aider
        with open('.aider.conf.yml', 'r+') as f:
            config = yaml.safe_load(f)
            config['model'] = settings['aider_model']
            f.seek(0)
            yaml.dump(config, f)
            f.truncate()
        
        print(f"✅ Configurations optimized based on performance data")
        print(f"   Claude Temperature: {settings['claude_code_temperature']:.2f}")
        print(f"   Aider Model: {settings['aider_model']}")
        print(f"   Optimal Parallel Agents: {settings['parallel_agents']:.1f}")

# Daily optimization
if __name__ == "__main__":
    adapter = AdaptiveCCConfig()
    optimal = adapter.optimize_config()
    
    # Log optimization
    with open('optimization-log.txt', 'a') as f:
        f.write(f"{datetime.now()}: Optimized config: {optimal}\n")
EOF

chmod +x adaptive-cc.py
# Cron: 0 6 * * * /path/to/adaptive-cc.py

Disaster Recovery

# Vollständiges Disaster Recovery System
cat > disaster-recovery.sh << 'EOF'
#!/bin/bash

# CC Disaster Recovery System
DR_MODE=$1

case $DR_MODE in
  "backup")
    echo "🔒 Creating disaster recovery backup..."
    
    # Full system backup
    tar -czf dr-backup-$(date +%Y%m%d-%H%M%S).tar.gz \
      .git/ \
      .worktrees/ \
      CONTEXT.md \
      AGENTS.md \
      .ai-context.yaml \
      prompts/ \
      .claude-code-config.json \
      .aider.conf.yml \
      .vscode/ \
      ~/.tabby/ \
      cc-hive-mind.db
    
    # Upload to cloud
    aws s3 cp dr-backup-*.tar.gz s3://cc-disaster-recovery/
    
    echo "✅ Backup complete and uploaded"
    ;;
    
  "restore")
    echo "🔧 Restoring from disaster recovery..."
    
    # Download latest backup
    LATEST=$(aws s3 ls s3://cc-disaster-recovery/ | sort | tail -1 | awk '{print $4}')
    aws s3 cp s3://cc-disaster-recovery/$LATEST ./
    
    # Extract
    tar -xzf $LATEST
    
    # Reinitialize agents
    ./start-cc-agents.sh
    
    # Restore context
    ./sync-context.sh
    
    echo "✅ System restored from backup"
    ;;
    
  "emergency")
    echo "🚨 EMERGENCY MODE ACTIVATED"
    
    # Stop all agents immediately
    pkill -9 -f "claude-code|aider|code|tabby"
    
    # Save current state
    git add -A
    git commit -m "EMERGENCY: State saved at $(date)"
    
    # Create emergency backup
    $0 backup
    
    # Send alert
    curl -X POST $SLACK_WEBHOOK -d '{"text":"🚨 CC Emergency Mode activated! All agents stopped."}'
    
    echo "✅ Emergency procedures complete"
    ;;
esac
EOF

chmod +x disaster-recovery.sh

📚 CC Resource Library

Essential Bookmarks

# CC Resource Collection
cat > CC-RESOURCES.md << 'EOF'
# CC Multi-Agent Development Resources

## Official Documentation
- [Claude Code Docs](https://docs.anthropic.com/claude-code)
- [Aider Documentation](https://aider.chat/docs)
- [Cline GitHub](https://github.com/cline/cline)
- [Tabby Docs](https://tabbyml.com/docs)
- [MCP Protocol](https://modelcontextprotocol.io)

## Community Resources
- [CC Discord Server](https://discord.gg/cc-dev)
- [Multi-Agent Patterns](https://patterns.cc-dev.org)
- [CC YouTube Channel](https://youtube.com/@cc-orchestration)

## Tools & Extensions
- [Claude Squad](https://github.com/smtg-ai/claude-squad)
- [MCP Inspector](https://github.com/modelcontextprotocol/inspector)
- [Git Worktree Manager](https://github.com/git-worktree-manager)

## Courses & Training
- [Anthropic's Claude Code Course](https://deeplearning.ai/claude-code)
- [Multi-Agent Orchestration](https://coursera.org/multi-agent)
- [Advanced Git Workflows](https://gitschool.com/worktrees)

## Benchmarks & Comparisons
- [Aider Leaderboard](https://aider.chat/docs/leaderboards)
- [LLM Coding Benchmarks](https://github.com/llm-benchmarks)
- [Cost Calculator](https://llm-cost-calculator.com)
EOF

Quick Reference Card

# Druckbare Quick Reference Card
cat > CC-QUICK-REFERENCE.md << 'EOF'
# 🎯 CC Quick Reference Card

## Daily Commands

cc-start # Start all agents cc-status # Check status cc-stop # End of day cc-costs # Check costs

## Emergency Commands

cc-emergency-stop # Stop everything cc-rollback # Undo last change cc-backup # Create backup cc-restore [file] # Restore backup

## Workflow Patterns

cc-relay [task] # Sequential work cc-swarm [task] # Parallel work cc-review-all # Review circle cc-integrate # Merge all work

## Agent-Specific

claude [prompt] # Claude Code chat aid [prompt] # Aider command cline-start # Open Cline in VS Code tabby-optimize # Run optimization

## Monitoring

cc-performance # Performance metrics cc-learn # Generate learnings watch cc-status # Live monitoring

## Context Management

cc-sync # Sync context cc-broadcast [msg]# Broadcast to all cc-resolve # Resolve conflicts

## Git Worktrees

wt-claude # Go to Claude worktree wt-aider # Go to Aider worktree wt-cline # Go to Cline worktree wt-tabby # Go to Tabby worktree

EOF

🎉 Conclusion: Mastering the CC Symphony

Du hast jetzt das komplette Rüstzeug für professionelle Multi-Agent-Orchestrierung:

1. Installation & Setup ✅ - Alle Tools konfiguriert und optimiert
2. Täglicher Workflow ✅ - Automatisierte Abläufe etabliert
3. Tipps & Tricks ✅ - Advanced Patterns gemeistert
4. Monitoring & Optimization ✅ - Kontinuierliche Verbesserung
5. Disaster Recovery ✅ - Sicherheit garantiert

Mit diesem Setup bist du bereit, die Produktivität eines ganzen Entwicklerteams zu erreichen - als einzelner Context Keeper mit deinem AI-Team!

Remember: Der Mensch bleibt der Dirigent dieser Symphonie. Die KI-Agents sind deine Virtuosen, aber du bestimmst die Melodie! 🎼

Viel Erfolg bei deiner CC-Journey! 🚀✨

Collective Context (CC) - Whitepaper v.01

Das Projekt „Collective Context“ (CC) schafft einen dauerhaften, gemeinsamen Wissensraum für die Zusammenarbeit zwischen Menschen UND zwischen Menschen + KI Systemen.

recode@ /YOU ❤️DevOps