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agricultural-output-forecasting

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.

andyxcg0 installations selon la source☆ 0 Étoiles du dépôtv1.0.1

Installation

Suivez les instructions du dépôt pour votre agent. Consultez les fichiers et dépendances avant l’installation.

SkillHub CLI

skillhub install andyxcg/agricultural-output-forecasting

Examinez la source et la compatibilité, puis suivez les étapes d’installation.

Donnez le lien à votre agent et demandez-lui d’examiner instructions et dépendances avant d’expliquer les étapes.

Voir la source ↗Guides

Instructions

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:
    pri...

Informations sur la source

Source
github
Repository
openclaw/skills
Path
skills/andyxcg/agricultural-output-forecasting
Version
1.0.1
Commit
98ddbb65b8f8fb21fb89a7f43da72f19fa3f50ab
Source de classification
rules
Statut
active
Visibilité
public

Ces informations proviennent de l’analyse indexée et peuvent être anciennes. Vérifiez les fichiers actuels.

README

Agricultural Output Forecasting

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

Features

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

Installation

  1. Clone or download this skill to your OpenClaw workspace:
cd /home/node/.openclaw/workspace/skills/
  1. Install Python dependencies (if any additional packages are needed):
pip install -r requirements.txt  # if requirements.txt exists
  1. Copy the environment variables file and configure:
cp .env.example .env
# Edit .env with your actual API keys

Environment Variables Configuration

Copy .env.example to .env and configure the following variables:

Required Variables
Variable Description Required
SKILL_BILLING_API_KEY Your SkillPay API key for billing Yes
SKILL_ID Your Skill ID from SkillPay dashboard Yes
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

Usage Examples

Python API
from scripts.forecast import forecast_outp...

Contenu extrait

SKILL.md
# 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

```python
{
    "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:

```python
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:
    pri...
README
# Agricultural Output Forecasting

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

## Features

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

## Installation

1. Clone or download this skill to your OpenClaw workspace:
```bash
cd /home/node/.openclaw/workspace/skills/
```

2. Install Python dependencies (if any additional packages are needed):
```bash
pip install -r requirements.txt  # if requirements.txt exists
```

3. Copy the environment variables file and configure:
```bash
cp .env.example .env
# Edit .env with your actual API keys
```

## Environment Variables Configuration

Copy `.env.example` to `.env` and configure the following variables:

### Required Variables

| Variable | Description | Required |
|----------|-------------|----------|
| `SKILL_BILLING_API_KEY` | Your SkillPay API key for billing | Yes |
| `SKILL_ID` | Your Skill ID from SkillPay dashboard | Yes |

### 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 |

## Usage Examples

### Python API

```python
from scripts.forecast import forecast_outp...

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