---

name: agricultural-output-forecasting description: Agricultural Product Output Forecasting Based on Big Data. Predicts crop yields and agricultural output using historical data, weather patterns, and market trends. Use when forecasting agricultural production, estimating crop yields, analyzing farming trends, or making data-driven decisions in agriculture. version: 1.0.1

Agricultural Output Forecasting

Version: 1.0.1
Category: Agriculture / Analytics
Billing: SkillPay (1 token per call, ~0.001 USDT)
Free Trial: 10 free calls per user

A big data-driven agricultural product output forecasting tool that helps farmers, agronomists, and agricultural businesses predict crop yields and production outputs.

Features

1. Yield Prediction - Forecast crop yields based on historical data and current conditions
2. Weather Impact Analysis - Factor in weather patterns and climate data
3. Market Trend Integration - Consider market prices and demand trends
4. Multi-Crop Support - Support for various agricultural products (grains, vegetables, fruits, etc.)
5. SkillPay Billing - Pay-per-use monetization (1 token per call, ~0.001 USDT)
6. Free Trial - 10 free calls for every new user

Free Trial

Each user gets 10 free calls before billing begins. During the trial:

• No payment required
• Full feature access
• Trial status returned in API response

{
    "success": True,
    "trial_mode": True,      # Currently in free trial
    "trial_remaining": 7,    # 7 free calls left
    "balance": None,         # No balance needed in trial
    "forecast": {...}
}

After 10 free calls, normal billing applies.

Quick Start

Forecast agricultural output:

from scripts.forecast import forecast_output
import os

# Set environment variables (only needed after trial)
os.environ["SKILL_BILLING_API_KEY"] = "your-api-key"
os.environ["SKILL_ID"] = "your-skill-id"

# Forecast wheat yield
result = forecast_output(
    crop_type="wheat",
    area_hectares=100,
    region="North China Plain",
    season="spring",
    user_id="user_123"
)

# Check result
if result["success"]:
    print("预测产量:", result["forecast"])
    if result.get("trial_mode"):
        print(f"免费试用剩余: {result['trial_remaining']} 次")
    else:
        print("剩余余额:", result["balance"])
else:
    print("错误:", result["error"])
    if "paymentUrl" in result:
        print("充值链接:", result["paymentUrl"])

API Usage:

# Set environment variables (only needed after trial)
export SKILL_BILLING_API_KEY="your-api-key"
export SKILL_ID="your-skill-id"

# Run forecast
python scripts/forecast.py \
  --crop wheat \
  --area 100 \
  --region "North China Plain" \
  --season spring \
  --user-id "user_123"

Environment Variables

This skill requires the following environment variables:

Required Variables (After Trial)

Variable	Description	Required	Example
SKILL_BILLING_API_KEY	Your SkillPay API key for billing	After trial	skp_abc123...
SKILL_ID	Your Skill ID from SkillPay dashboard	After trial	skill_def456...

Optional Variables

Variable	Description	Default
OPENWEATHER_API_KEY	OpenWeatherMap API key for weather data	-
WEATHERAPI_KEY	WeatherAPI key for alternative weather data	-
USDA_API_KEY	USDA API key for US agricultural data	-
OPENAI_API_KEY	OpenAI API key for enhanced forecasting	-
CACHE_DURATION_MINUTES	Cache duration for weather/market data	60
MAX_FORECAST_AREA	Maximum area in hectares per request	10000

See .env.example for a complete list of environment variables.

Configuration

The skill uses SkillPay billing integration:

• Provider: skillpay.me
• Pricing: 1 token per call (~0.001 USDT)
• Chain: BNB Chain
• Free Trial: 10 calls per user
• API Key: Set via SKILL_BILLING_API_KEY environment variable
• Skill ID: Set via SKILL_ID environment variable
• Minimum deposit: 8 USDT

Supported Crops

• Grains: wheat, rice, corn, barley, sorghum
• Vegetables: tomato, potato, cabbage, cucumber
• Fruits: apple, orange, grape, peach
• Others: soybean, cotton, sugarcane

Output Format

Forecast results include:

• Predicted yield (tons/hectare)
• Confidence interval
• Weather impact factor
• Market price prediction
• Risk assessment
• Recommendations

Response Format

{
    "success": True,
    "trial_mode": False,        # True during free trial
    "trial_remaining": 0,       # Remaining free calls
    "balance": 95.5,            # User balance (None during trial)
    "forecast": {
        "forecast_id": "AGR_20240306120000",
        "crop_type": "wheat",
        "yield_forecast": {...},
        "risk_assessment": {...},
        "recommendations": [...]
    }
}

Security Considerations

Data Privacy

• Agricultural data is treated as confidential business information
• No personally identifiable information (PII) is collected
• Weather and market data is cached to minimize API calls

API Key Security

• Never commit API keys to version control
• Use environment variables for all sensitive configuration
• Rotate API keys regularly

References

• For forecast methodology: see references/forecast-methodology.md
• For billing API details: see references/skillpay-billing.md
• For full documentation: see README.md