"""Project discovery prompt implementation."""
from typing import Optional, Dict, Any
async def project_discovery(criteria: Optional[Dict[str, Any]] = None) -> str:
"""
Guide users through project discovery and analysis.
Helps explore ecological projects generating carbon credits.
"""
# Customize based on search criteria
if criteria:
if criteria.get("location"):
focus_section = f"""
**🎯 Focus: Projects in {criteria['location']}**
You're looking for projects in a specific location. Let's find:
• All projects in {criteria['location']}
• Their credit generation history
• Market activity for these projects
"""
elif criteria.get("credit_class"):
focus_section = f"""
**🎯 Focus: {criteria['credit_class']} Projects**
You're interested in projects using a specific methodology. Let's explore:
• All {criteria['credit_class']} projects
• Their performance metrics
• Credit issuance patterns
"""
else:
focus_section = """
**🎯 Custom Search Criteria**
Let's find projects matching your specific requirements!
"""
else:
focus_section = """
**🎯 Open Project Discovery**
Let's explore all ecological projects on Regen Network!
"""
return f"""🌿 **Regen Project Discovery Session**
{focus_section}
**🌍 Understanding Regen Projects:**
Projects are real-world ecological initiatives that generate carbon credits through verified environmental benefits. Each project represents actual on-the-ground work like reforestation, soil improvement, or ecosystem restoration.
**Project Components:**
• **Project ID**: Unique identifier (e.g., C01-001)
• **Credit Class**: Methodology used (e.g., C01 for reforestation)
• **Jurisdiction**: Geographic location
• **Reference ID**: External registry reference
• **Metadata**: Additional project documentation
---
## 🔍 **Discovery Methods**
### 1. Browse All Projects
```python
# Get complete project list
projects = get_all_projects()
print(f"Total projects on Regen: {{len(projects)}}")
# Quick overview
for project in projects[:10]: # First 10 projects
print(f"{{project['id']}}: {{project.get('name', 'Unnamed')}}")
print(f" Location: {{project.get('jurisdiction', 'Unknown')}}")
print(f" Class: {{project.get('class_id', 'Unknown')}}")
```
### 2. Filter by Credit Class
```python
# Find all reforestation projects (C01)
reforestation = get_projects_by_class('C01')
print(f"Reforestation projects: {{len(reforestation)}}")
# Find soil carbon projects (C02)
soil_carbon = get_projects_by_class('C02')
print(f"Soil carbon projects: {{len(soil_carbon)}}")
# Compare methodologies
def compare_project_classes():
classes = get_credit_classes()
comparison = []
for cls in classes:
projects = get_projects_by_class(cls['id'])
comparison.append({{
'class': cls['id'],
'name': cls.get('name', 'Unknown'),
'project_count': len(projects)
}})
return sorted(comparison, key=lambda x: x['project_count'], reverse=True)
```
### 3. Geographic Search
```python
def find_projects_by_location(location_code):
\"\"\"Find projects in specific geographic regions.\"\"\"
all_projects = get_all_projects()
matching = []
for project in all_projects:
jurisdiction = project.get('jurisdiction', '')
# Check various location formats
if location_code.upper() in jurisdiction.upper():
matching.append(project)
return matching
# Example searches
us_projects = find_projects_by_location('US')
costa_rica = find_projects_by_location('CR')
california = find_projects_by_location('US-CA')
print(f"US Projects: {{len(us_projects)}}")
print(f"Costa Rica: {{len(costa_rica)}}")
print(f"California: {{len(california)}}")
```
---
## 📋 **Project Analysis Workflow**
### Step 1: Project Details
```python
def analyze_project(project_id):
\"\"\"Deep dive into a specific project.\"\"\"
# Get project details
project = get_project_by_id(project_id)
print(f"=== Project Analysis: {{project_id}} ===")
print(f"Name: {{project.get('name', 'N/A')}}")
print(f"Credit Class: {{project.get('class_id', 'N/A')}}")
print(f"Location: {{project.get('jurisdiction', 'N/A')}}")
print(f"Start Date: {{project.get('project_start_date', 'N/A')}}")
print(f"Admin: {{project.get('admin', 'N/A')}}")
# Check for external references
if project.get('reference_id'):
print(f"External Registry: {{project['reference_id']}}")
return project
# Example
project_analysis = analyze_project('C01-001')
```
### Step 2: Credit Issuance History
```python
def analyze_project_credits(project_id):
\"\"\"Analyze all credits issued by a project.\"\"\"
batches = get_batches_by_project(project_id)
if not batches:
return {{'status': 'No credits issued yet'}}
total_issued = 0
vintage_periods = []
for batch in batches:
amount = float(batch.get('total_amount', 0))
total_issued += amount
vintage_periods.append({{
'batch': batch['denom'],
'amount': amount,
'start': batch.get('start_date', 'N/A'),
'end': batch.get('end_date', 'N/A')
}})
# Calculate statistics
avg_batch = total_issued / len(batches) if batches else 0
return {{
'total_credits': total_issued,
'num_batches': len(batches),
'average_batch_size': avg_batch,
'vintages': vintage_periods,
'first_issuance': vintage_periods[0]['start'] if vintage_periods else None,
'latest_issuance': vintage_periods[-1]['end'] if vintage_periods else None
}}
# Analyze credit generation
credits = analyze_project_credits('C01-001')
print(f"Total credits issued: {{credits['total_credits']:,.0f}}")
print(f"Number of batches: {{credits['num_batches']}}")
```
### Step 3: Market Activity
```python
def analyze_project_market_activity(project_id):
\"\"\"Check if project credits are being traded.\"\"\"
batches = get_batches_by_project(project_id)
market_activity = []
for batch in batches:
orders = get_sell_orders_by_batch(batch['denom'])
if orders:
total_for_sale = sum(float(o.get('quantity', 0)) for o in orders)
prices = [float(o.get('ask_price', 0)) for o in orders]
market_activity.append({{
'batch': batch['denom'],
'orders': len(orders),
'credits_for_sale': total_for_sale,
'min_price': min(prices) if prices else 0,
'max_price': max(prices) if prices else 0,
'avg_price': sum(prices) / len(prices) if prices else 0
}})
return {{
'active_batches': len(market_activity),
'total_orders': sum(b['orders'] for b in market_activity),
'details': market_activity
}}
# Check market presence
market = analyze_project_market_activity('C01-001')
print(f"Batches on market: {{market['active_batches']}}")
print(f"Total sell orders: {{market['total_orders']}}")
```
---
## 🎯 **Advanced Discovery Patterns**
### Find High-Performance Projects
```python
def find_top_projects(limit=10):
\"\"\"Find projects with most credits issued.\"\"\"
all_projects = get_all_projects()
project_stats = []
for project in all_projects:
batches = get_batches_by_project(project['id'])
total_credits = sum(float(b.get('total_amount', 0)) for b in batches)
if total_credits > 0:
project_stats.append({{
'id': project['id'],
'name': project.get('name', 'Unnamed'),
'location': project.get('jurisdiction', 'Unknown'),
'class': project.get('class_id', 'Unknown'),
'total_credits': total_credits,
'num_batches': len(batches)
}})
# Sort by total credits
top_projects = sorted(project_stats, key=lambda x: x['total_credits'], reverse=True)
return top_projects[:limit]
# Get top 10 projects
top_10 = find_top_projects(10)
for i, project in enumerate(top_10, 1):
print(f"{{i}}. {{project['id']}}: {{project['total_credits']:,.0f}} credits")
```
### Recent Project Activity
```python
def find_recent_projects(days=30):
\"\"\"Find projects with recent credit issuances.\"\"\"
from datetime import datetime, timedelta
cutoff_date = datetime.now() - timedelta(days=days)
recent_projects = []
all_projects = get_all_projects()
for project in all_projects:
batches = get_batches_by_project(project['id'])
for batch in batches:
# Check if batch is recent (simplified date comparison)
batch_date = batch.get('end_date', '')
if batch_date > cutoff_date.isoformat()[:10]:
recent_projects.append({{
'project': project['id'],
'batch': batch['denom'],
'date': batch_date,
'amount': batch.get('total_amount', 0)
}})
break # Found recent activity, move to next project
return recent_projects
```
### Project Comparison Tool
```python
def compare_projects(project_ids):
\"\"\"Compare multiple projects side by side.\"\"\"
comparison = []
for project_id in project_ids:
project = get_project_by_id(project_id)
batches = get_batches_by_project(project_id)
# Calculate metrics
total_credits = sum(float(b.get('total_amount', 0)) for b in batches)
# Check market activity
market_orders = 0
for batch in batches:
orders = get_sell_orders_by_batch(batch['denom'])
market_orders += len(orders)
comparison.append({{
'id': project_id,
'name': project.get('name', 'Unnamed'),
'location': project.get('jurisdiction', 'Unknown'),
'class': project.get('class_id', 'Unknown'),
'total_credits': total_credits,
'num_batches': len(batches),
'market_orders': market_orders,
'start_date': project.get('project_start_date', 'Unknown')
}})
return comparison
# Compare specific projects
comparison = compare_projects(['C01-001', 'C01-002', 'C01-003'])
```
---
## 🌍 **Project Categories & Types**
### By Methodology
Use `list_classes()` to see the current set of credit classes and their resolved names.
Examples: **C01** (Verified Carbon Standard), **C02** (Urban Forest Carbon Credit Class), **C07** (CarbonPlus Grasslands Credit Class), **BT01**, **MBS01**, **USS01**, **KSH01**.
### By Geography
• **North America**: US, Canada, Mexico
• **Central America**: Costa Rica, Panama, Guatemala
• **South America**: Brazil, Colombia, Peru
• **Europe**: Various EU countries
• **Asia-Pacific**: Australia, Indonesia, Philippines
• **Africa**: Kenya, South Africa, Ghana
### By Scale
• **Small**: < 10,000 credits/year
• **Medium**: 10,000 - 100,000 credits/year
• **Large**: > 100,000 credits/year
---
## 💡 **Discovery Tips**
**Efficient Searching:**
• Cache project lists locally to avoid repeated queries
• Use batch queries when analyzing multiple projects
• Filter early to reduce data processing
**Key Metrics to Track:**
• Credit generation rate (credits per year)
• Market liquidity (% of credits for sale)
• Price premium vs class average
• Vintage consistency
**Due Diligence Questions:**
• How long has the project been active?
• Is credit generation consistent?
• Are credits actively traded?
• What's the project's reputation?
---
## 🎯 **Practice Exercises**
**Exercise 1: Regional Analysis**
```python
# Task: Find all projects in Latin America and calculate total credits
# Hint: Check jurisdictions for country codes like CR, BR, CO, etc.
```
**Exercise 2: Methodology Comparison**
```python
# Task: Compare average project size across different credit classes
# Hint: Group projects by class and calculate average credits issued
```
**Exercise 3: Market Readiness**
```python
# Task: Find projects with credits issued but not yet on market
# Hint: Compare batches list with sell orders
```
Ready to discover ecological projects? What type of projects are you looking for?"""
