JJJ - Junior Developer CLI Wrapper

Purpose

Smart multi-agent task execution with automatic routing and cost optimization. Routes tasks to appropriate agents (Junior/Claude) based on complexity.

When to Use

• User explicitly types jjj
• Writing unit tests
• Adding comments/docstrings
• Simple refactoring
• Generating boilerplate code
• Any routine coding task

Cost Comparison

Claude-Only Workflow:
  - Every task: $0.075
  - 10 tasks: $0.75

Multi-Agent Workflow:
  - Simple (40%): $0.0021 per task
  - Moderate (30%): $0.0231 per task
  - Complex (30%): $0.0231 per task
  - 10 tasks: $0.147
  - SAVINGS: 80%+ 🎉

Three Execution Modes

Mode 1: Smart Mode (Default) - Automatic Routing

Best for: Most use cases, maximum cost optimization

Usage:

./scripts/jjj.sh

Interactive prompts:

1. Task description?
2. File path? (optional)
3. Include file content? (y/n)

System automatically:

• Analyzes complexity
• Routes to Junior/Junior+Review/Claude
• Shows agent status in real-time
• Displays cost savings

Agent Status Display:

🔍 Analyzing task complexity...
✅ Complexity: simple

🤖 Routing Decision:
   Agent: Junior Developer
   Model: Gemini Flash
   Estimated Cost: $0.0021

⚙️  Junior Developer [ACTIVE]
   Status: Generating code...

✅ Task completed!
   Generated: 245 lines
   Savings: $0.0525 (96.2%)

Mode 2: Manual Mode - Force Junior Developer

Best for: Testing, specific scenarios, full control

Usage:

./scripts/jjj.sh --manual

Full control:

• Select task type (test/comment/refactor/boilerplate/general)
• Choose model (auto/flash/local)
• Provide context code
• Junior executes directly (no routing)

Mode 3: Quick Mode - One-liner

Best for: Fast, one-off tasks

Usage:

./scripts/jjj.sh "Add docstring" utils.py
./scripts/jjj.sh "Write tests" auth.ts
./scripts/jjj.sh "Refactor function" --mode local

Steps

1. Check Prerequisites

# Check script exists
test -f scripts/jjj.sh && echo "✅ Found" || echo "❌ Missing: scripts/jjj.sh"

# Check dependencies
which jq > /dev/null && echo "✅ jq installed" || echo "❌ Need: brew install jq"

# Check Python modules
python -c "import agent_coordinator" 2>/dev/null && echo "✅ Python ready" || echo "❌ Missing Python modules"

2. Determine Mode

Ask user:

Which mode would you like to use?

1. Smart Mode (recommended) - Automatic routing
2. Manual Mode - Direct Junior Developer
3. Quick Mode - One-liner

Or just tell me the task and I'll use Smart Mode.

3. Execute Based on Mode

Smart Mode:

./scripts/jjj.sh

# Then provide when prompted:
# - Task description
# - File path (if applicable)
# - Whether to include file content

Manual Mode:

./scripts/jjj.sh --manual

# Then follow prompts:
# - Select task type
# - Choose model
# - Provide context

Quick Mode:

./scripts/jjj.sh "[task]" [file] [--mode MODE]

4. Monitor Execution

The script will show:

• 🔍 Analyzing task complexity...
• 🤖 Routing decision (agent/model/cost)
• ⚙️ Agent status (active/generating)
• ✅ Completion (result/savings)

5. Review Output

Junior Developer output includes:

• Generated code
• Quality score (if reviewed)
• Cost comparison
• Savings percentage

Present to user:

✅ Task Complete!

**Agent Used**: Junior Developer (Gemini Flash)
**Generated**: [lines] lines of code
**Cost**: $0.0021
**Savings**: $0.0525 (96.2%) vs Claude-only

**Output:**
[Show generated code]

**Quality**: 8/10 (Claude reviewed)

Ready to apply this code?

6. Apply or Iterate

If quality good (score ≥ 8):

• Apply the code directly
• Commit with appropriate message

If quality needs improvement:

• Ask user if they want to iterate
• Re-run with different parameters
• Or escalate to Claude for complex handling

Options & Flags

CLI Options

--manual          # Force Manual Mode (Junior only)
--mode MODE       # LLM mode: auto/flash/local
--type TYPE       # Task type: test/comment/refactor/boilerplate/general
--help            # Show detailed help

Task Types

• test: Writing unit tests
• comment: Adding comments/docstrings
• refactor: Simple refactoring
• boilerplate: Generating boilerplate code
• general: General coding task

LLM Modes

• auto: Try Gemini Flash → fallback to Local LLM
• flash: Force Gemini Flash (best quality)
• local: Force Local LLM (offline/privacy)

Environment Variables

# Gemini Flash API for Junior Developer
export GEMINI_API_KEY="your-key-here"

# Local LLM (optional, fallback)
export LOCAL_LLM_URL="http://192.168.1.202:8088/v1/chat/completions"

Important Notes

When to Use Smart Mode

• Maximum cost optimization (80%+)
• Automatic complexity analysis
• Real-time agent status
• Best user experience

When to Use Manual Mode

• Testing Junior Developer
• Specific task types
• Override routing decision
• Learning/experimentation

When to Use Quick Mode

• Fast, one-off tasks
• Scripting/automation
• When you know exactly what you want

Offline Mode

Works offline with Local LLM:

./scripts/jjj.sh --mode local

Error Handling

"jjj.sh not found":

# Check if script exists
ls -la scripts/jjj.sh

# If missing:
"❌ Junior Developer script not found at scripts/jjj.sh"

"jq not installed":

# Install jq
brew install jq  # macOS
sudo apt install jq  # Linux

# Or inform user:
"❌ jq required. Install: brew install jq"

"Python modules missing":

# Check what's missing
python -c "import agent_coordinator; import task_router; import junior_developer"

# Inform user which modules are missing

"Agent routing failed":

# Fall back to Claude
"⚠️ Routing failed. Using Claude for this task."

Success Criteria

• ✅ Script executed successfully
• ✅ Agent selected appropriately
• ✅ Code generated with quality score
• ✅ Cost savings calculated and shown
• ✅ User provided with clear output
• ✅ Ready to apply or iterate

Performance Tips

• Use Smart Mode for best results (80%+ savings)
• Manual Mode useful for testing specific scenarios
• Quick Mode for automation and scripting
• Review Junior output before applying
• Iterate if quality score < 8
• See scripts/README.md for detailed docs

Related Skills

• ggg - Use Gatekeeper before jjj for large files
• nnn - Plan complex tasks before using jjj
• gogogo - Execute plans, using jjj for simple sub-tasks