# ConnectOnion Features Roadmap

*Features designed for agent developers who want their agents to collaborate*

## Phase 1: Core Features (MVP)

### 1. Share Your Functions
```python
from connectonion import share

# Any function can be shared
def translate(text: str, to_lang: str = "en") -> str:
    """I translate text to any language"""
    return my_translation_logic(text, to_lang)

# One line to share
share(translate)
# That's it! Others can now find it with: need("translate text")
```

### 2. Find What You Need
```python
from connectonion import need

# Just describe what you need in natural language
def process_foreign_text(text: str):
    translator = need("translate text to english")
    english = translator(text)
    return process(english)

# Any natural description works
analyzer = need("figure out if this review is positive")
summarizer = need("make this text shorter")
calculator = need("solve math problems")
```

### 3. Test Before Trust
```python
def get_reliable_translator():
    translators = need.all("translate text")
    
    for t in translators:
        result = t.test("Hello", expected="Hola")
        if result:
            return t  # This one works!
```

### 4. Automatic Network Discovery
```python
# Your shared functions are automatically discovered
# No configuration needed - just works!

# If someone else shared a translator:
translator = need("translate to spanish")
result = translator("Hello")  # "Hola"

# If someone shared an analyzer:
analyzer = need("is this text positive or negative?")
sentiment = analyzer("I love this!")  # "positive"
```

## Phase 2: Essential Features

### 5. Natural Language Works Everywhere
```python
# Works in any language
summarizer = need("make text shorter")
analyzer = need("entender los sentimientos del cliente")  # Spanish
calculator = need("解决数学问题")  # Chinese

# All these find the same capability
translator = need("translate text")
translator = need("convert to another language") 
translator = need("I don't understand this foreign text")
```

### 6. Track Your Experience
```python
translator = need("translate text")

# After using it
print(translator.my_experience)
# Output: Used 45 times, 98% success, avg 43ms

# Auto-prefer reliable agents
best_translator = need("translate text", prefer_reliable=True)
```

### 7. Handle Failures Naturally
```python
def reliable_service(data):
    # Try primary, fallback with regular Python
    try:
        analyzer = need("premium data analysis")
        return analyzer(data)
    except:
        # Try backup
        try:
            basic = need("basic data analysis")
            return basic(data)
        except:
            return "Analysis temporarily unavailable"

# Use it directly
result = reliable_service(my_data)
```

## Phase 3: Power Features

### 8. See Your Agent's Impact
```python
from connectonion import my_agent

my_agent.dashboard()
"""
Agent: translator
Status: Active ✓
Health: 99.2%

Today:
- Calls: 1,234
- Unique users: 67
- Avg response: 45ms
- Errors: 3
- Earnings: $12.34

Top users:
- research_assistant (234 calls)
- news_analyzer (187 calls)
- chatbot (134 calls)
"""
```

## Phase 4: Advanced Features

### 9. Visual Network Explorer
```python
from connectonion import visualize

# See the living network
visualize.network()
# Opens browser showing:
# - Active agents (nodes)
# - Current calls (animated edges)
# - Your agents highlighted
# - Performance metrics overlaid
```

### 10. Agent Versioning
```python
# Pin specific versions
translator = discover("translate", version="stable")

# Or use latest
translator = discover("translate", version="latest")

# See version history
discover.history("translate")
"""
v3.2 (current): Added Arabic support
v3.1: Performance improvements 
v3.0: Major refactor
"""
```

## Phase 5: Ecosystem Features

### 11. Agent Marketplace
```python
# Publish your agent
$ connectonion publish ./my_agent.py
# Publishing sentiment_analyzer...
# Set price (optional): $0.001/call
# Published! Install with: pip install agents/sentiment_analyzer

# Browse available agents
$ connectonion browse
# Featured agents:
# - gpt4_wrapper: Direct GPT-4 access ($0.01/call)
# - image_analyzer: Computer vision (free)
# - sql_generator: Text to SQL ($0.001/call)
```

### 12. Enterprise Features
```python
# Private network for company
$ connectonion serve --network company.local

# Access controls (simplified - no decorator needed)
def proprietary_analyzer(data):
    # Access control happens at network level
    return analyze_with_secret_sauce(data)

# Audit logs
discover.audit_log()
"""
2024-01-10 10:23:01 marketing_agent called analyzer
2024-01-10 10:24:15 sales_agent called translator
"""
```

## Developer Experience Goals

**Onboarding**: 
- Install → First agent working: < 2 minutes
- First agent composition: < 5 minutes
- Understanding core concepts: < 10 minutes

**Daily Use**:
- Most common operations: 1 line of code
- Debugging problems: Clear, visual tools
- Error handling: Standard Python patterns

**Growth**:
- Simple agents → Complex orchestrations
- Local testing → Global network
- Free usage → Revenue generation

## Success Metrics

- **Adoption**: 10,000 developers in 6 months
- **Network Growth**: 1,000 unique agents in 3 months
- **Usage**: 1M agent-to-agent calls per day by month 6
- **Developer Joy**: "I can't imagine building agents without this"

## Principles We Follow

1. **One-line simplicity** - Common tasks = 1 line of code
2. **Progressive disclosure** - Simple first, power when needed
3. **Fail gracefully** - Handle errors naturally with Python try/except
4. **Local first** - Works without internet
5. **Trust through experience** - Not certificates

## What We DON'T Build

❌ Complex authentication systems
❌ Global reputation scores
❌ Central registries
❌ API key management
❌ Permission hierarchies
❌ Blockchain anything

## The Promise

**"Make your agent discoverable in 1 line. Discover others in 1 line. Compose them like functions."**

That's the entire learning curve.