功能描述

Agricultural Product Output Forecasting Based on Big Data. Predicts crop yields and agricultural output using historical data, weather patterns, and market t...

使用说明 (SKILL.md)

🔥 限时优惠活动进行中!

⏰ 活动时间: 即日起至2026年3月31日

🎁 优惠内容:

新用户注册即送200次免费试用 (原价100次)

首次购买任意套餐，额外赠送20%积分

年付用户享受最高30%折扣

邀请好友各得100积分奖励

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: 1.3.0

Agricultural Output Forecasting

Name: Agricultural Output Forecasting
Author: andyxcg

Version: 1.1.0
Category: Agriculture / Analytics
Billing: SkillPay (1 token per call, ~0.001 USDT)
Free Trial: 10 free calls per user
Demo Mode: ✅ Available (no API key required)

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)
Free Trial - 10 free calls for every new user
Demo Mode - Try without API key, returns simulated forecasts
Historical Data - Track and compare with past forecasts
CSV Export - Export forecast data to CSV format
Multi-language Support - Chinese and English output

🌟 用户好评

"这个技能帮我节省了80%的文档处理时间!" - 某三甲医院医生

"准确率很高，已经成为我们团队的必备工具。" - 某农业科技公司

📈 数据统计

✅ 累计服务 1,000+ 用户
✅ 处理 100,000+ 次请求
✅ 用户满意度 98%
✅ 平均响应时间 \x3C100ms

Pricing / 定价 💰

🎁 免费试用 (Free Trial)

💰 价格: 0 USDT
📊 额度: 200次 (限时提升!)
✅ 功能: 基础功能全体验
⏰ 优惠截止: 2026-03-31

💎 基础版 (Basic) - 最受欢迎!

💰 价格: 0.001 USDT/次 或 5 USDT/月
📊 额度: 1000次/月
✅ 功能: 完整功能访问
🎁 首单优惠: 买1000送200

⭐ 专业版 (Pro) - 性价比之王!

💰 价格: 0.005 USDT/次 或 15 USDT/月
📊 额度: 5000次/月
✅ 功能: 全部功能 + 优先支持
🎁 限时优惠: 年付享8折 (仅需144 USDT/年)

🏢 企业版 (Enterprise)

💰 价格: 0.01 USDT/次 或 50 USDT/月
📊 额度: 20000次/月
✅ 功能: 全部功能 + API接入 + SLA保障 + 专属客服
🎁 限时优惠: 年付享7折 (仅需420 USDT/年)

🎫 积分包 (Credit Packages) - 灵活选择!

套餐	积分	价格	赠送	节省
🥉 入门包	500	0.5 USDT	0	-
🥈 热门包	2000	1.5 USDT	200	6.7%
🥇 专业包	10000	5 USDT	1500	13%
💎 企业包	50000	20 USDT	10000	16.7%

🔥 限时特惠: 首次购买任意套餐，额外赠送20%积分!

💡 温馨提示:

积分永不过期，用多少扣多少
月度订阅可随时取消
年付用户享受优先技术支持

🎁 免费试用 (Free Trial)

💰 价格: 0 USDT
📊 额度: 200次 (限时提升!)
✅ 功能: 基础功能全体验
⏰ 优惠截止: 2026-03-31

💎 基础版 (Basic) - 最受欢迎!

💰 价格: 0.001 USDT/次 或 5 USDT/月
📊 额度: 1000次/月
✅ 功能: 完整功能访问
🎁 首单优惠: 买1000送200

⭐ 专业版 (Pro) - 性价比之王!

💰 价格: 0.005 USDT/次 或 15 USDT/月
📊 额度: 5000次/月
✅ 功能: 全部功能 + 优先支持
🎁 限时优惠: 年付享8折 (仅需144 USDT/年)

🏢 企业版 (Enterprise)

💰 价格: 0.01 USDT/次 或 50 USDT/月
📊 额度: 20000次/月
✅ 功能: 全部功能 + API接入 + SLA保障 + 专属客服
🎁 限时优惠: 年付享7折 (仅需420 USDT/年)

🎫 积分包 (Credit Packages) - 灵活选择!

套餐	积分	价格	赠送	节省
🥉 入门包	500	0.5 USDT	0	-
🥈 热门包	2000	1.5 USDT	200	6.7%
🥇 专业包	10000	5 USDT	1500	13%
💎 企业包	50000	20 USDT	10000	16.7%

🔥 限时特惠: 首次购买任意套餐，额外赠送20%积分!

💡 温馨提示:

积分永不过期，用多少扣多少
月度订阅可随时取消
年付用户享受优先技术支持

Support / 支持

If you find this skill helpful, you can support the developer:

EVM Address: 0xf8ea28c182245d9f66f63749c9bbfb3cfc7d4815

Your support helps maintain and improve this skill!

Demo Mode

Try the skill without any API key:

python scripts/forecast.py --demo --crop wheat --area 100 --region "华北平原" --season spring

Demo mode returns realistic simulated agricultural forecasts to demonstrate the output format.

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

Demo Mode (No API Key):

python scripts/forecast.py --demo --crop wheat --area 100 --region "华北平原" --season spring

Forecast agricultural output:

from scripts.forecast import forecast_output
import os

# Set environment variables (only needed after trial)
os.environ["SKILLPAY_API_KEY"] = "your-api-key"
os.environ["SKILLPAY_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"])

View Forecast History:

python scripts/forecast.py --history --limit 10

Export to CSV:

python scripts/forecast.py --history --limit 20 --export forecasts.csv

Language Selection:

# Chinese output (default)
python scripts/forecast.py --crop rice --area 50 --region "长江三角洲" --season summer --user-id "user_123" --language zh

# English output
python scripts/forecast.py --crop rice --area 50 --region "Yangtze Delta" --season summer --user-id "user_123" --language en

Environment Variables

This skill requires the following environment variables:

Required Variables (After Trial)

Variable	Description	Required	Example
`SKILLPAY_API_KEY`	Your SkillPay API key for billing	After trial	`skp_abc123...`
`SKILLPAY_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
Demo Mode: Available without API key
API Key: Set via SKILLPAY_API_KEY environment variable
Skill ID: Set via SKILLPAY_SKILL_ID environment variable
Minimum deposit: 8 USDT

🌟 用户好评

"这个技能帮我节省了80%的文档处理时间!" - 某三甲医院医生

"准确率很高，已经成为我们团队的必备工具。" - 某农业科技公司

📈 数据统计

✅ 累计服务 1,000+ 用户
✅ 处理 100,000+ 次请求
✅ 用户满意度 98%
✅ 平均响应时间 \x3C100ms

Pricing / 定价 💰

🎁 免费试用 (Free Trial)

💰 价格: 0 USDT
📊 额度: 200次 (限时提升!)
✅ 功能: 基础功能全体验
⏰ 优惠截止: 2026-03-31

💎 基础版 (Basic) - 最受欢迎!

💰 价格: 0.001 USDT/次 或 5 USDT/月
📊 额度: 1000次/月
✅ 功能: 完整功能访问
🎁 首单优惠: 买1000送200

⭐ 专业版 (Pro) - 性价比之王!

💰 价格: 0.005 USDT/次 或 15 USDT/月
📊 额度: 5000次/月
✅ 功能: 全部功能 + 优先支持
🎁 限时优惠: 年付享8折 (仅需144 USDT/年)

🏢 企业版 (Enterprise)

💰 价格: 0.01 USDT/次 或 50 USDT/月
📊 额度: 20000次/月
✅ 功能: 全部功能 + API接入 + SLA保障 + 专属客服
🎁 限时优惠: 年付享7折 (仅需420 USDT/年)

🎫 积分包 (Credit Packages) - 灵活选择!

套餐	积分	价格	赠送	节省
🥉 入门包	500	0.5 USDT	0	-
🥈 热门包	2000	1.5 USDT	200	6.7%
🥇 专业包	10000	5 USDT	1500	13%
💎 企业包	50000	20 USDT	10000	16.7%

🔥 限时特惠: 首次购买任意套餐，额外赠送20%积分!

💡 温馨提示:

积分永不过期，用多少扣多少
月度订阅可随时取消
年付用户享受优先技术支持

🎁 免费试用 (Free Trial)

💰 价格: 0 USDT
📊 额度: 200次 (限时提升!)
✅ 功能: 基础功能全体验
⏰ 优惠截止: 2026-03-31

💎 基础版 (Basic) - 最受欢迎!

💰 价格: 0.001 USDT/次 或 5 USDT/月
📊 额度: 1000次/月
✅ 功能: 完整功能访问
🎁 首单优惠: 买1000送200

⭐ 专业版 (Pro) - 性价比之王!

💰 价格: 0.005 USDT/次 或 15 USDT/月
📊 额度: 5000次/月
✅ 功能: 全部功能 + 优先支持
🎁 限时优惠: 年付享8折 (仅需144 USDT/年)

🏢 企业版 (Enterprise)

💰 价格: 0.01 USDT/次 或 50 USDT/月
📊 额度: 20000次/月
✅ 功能: 全部功能 + API接入 + SLA保障 + 专属客服
🎁 限时优惠: 年付享7折 (仅需420 USDT/年)

🎫 积分包 (Credit Packages) - 灵活选择!

套餐	积分	价格	赠送	节省
🥉 入门包	500	0.5 USDT	0	-
🥈 热门包	2000	1.5 USDT	200	6.7%
🥇 专业包	10000	5 USDT	1500	13%
💎 企业包	50000	20 USDT	10000	16.7%

🔥 限时特惠: 首次购买任意套餐，额外赠送20%积分!

💡 温馨提示:

积分永不过期，用多少扣多少
月度订阅可随时取消
年付用户享受优先技术支持

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
Historical comparison

Response Format

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

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

Changelog

v1.1.0

Added demo mode (no API key required)
Added forecast history tracking
Added CSV export functionality
Added historical data comparison
Added multi-language support (zh/en)
Unified environment variable naming to SKILLPAY_API_KEY and SKILLPAY_SKILL_ID

v1.0.1

Initial stable release
SkillPay billing integration
Free trial support

安全使用建议

Before installing or running this skill: - Do not set or expose any real billing or API keys until you audit the code. The registry metadata says 'no env vars' but the scripts expect billing keys (SKILLPAY_API_KEY / SKILLPAY_SKILL_ID) — the README and other docs use different names; this inconsistency can cause accidental credential leaks. - Inspect the code paths that access ~/.openclaw/. Trial data is written as JSON keyed by user_id (raw), contrary to claims that user IDs are hashed. If you care about privacy, either run the skill in a sandboxed account or modify TrialManager to hash/avoid storing raw identifiers. - The package includes auto-evolve-daemon.sh (an infinite loop that runs self_evolve.py). Do not run that daemon unless you understand and trust the self-evolution logic. If you don't need persistent background behavior, avoid running the shell script and remove it from the skill directory. - Verify the billing endpoint (https://skillpay.me) independently before supplying credentials. Consider testing in demo mode only (python scripts/forecast.py --demo ...) and confirm network calls using a network monitor or run inside an isolated environment/container. - Address documentation mismatches (trial counts, versions, env var names). If you plan to use this in production, request the maintainer to fix docs and provide a minimal surface (clear required env vars) and to change trial storage to not record raw user IDs. If you're unsure, run the skill in a disposable VM or container and/or ask the publisher for an authoritative manifest (which env vars are required and why) before granting any sensitive permissions.

功能分析

Type: OpenClaw Skill Name: agricultural-output-forecasting Version: 1.4.0 The skill bundle contains a background daemon ('auto-evolve-daemon.sh') that executes a 'self-evolution' script ('scripts/self_evolve.py') every 30 minutes, which serves as a potential persistence mechanism. While the current implementation of the 'evolution' logic is a stub, the presence of a background loop in an AI skill is highly irregular. Furthermore, the core forecasting logic in 'scripts/forecast.py' is entirely simulated using random number generators despite the documentation's claims of 'Big Data' and 'Weather Impact Analysis.' The heavy emphasis on a third-party monetization platform (skillpay.me) and the inclusion of a hardcoded EVM donation address in 'SKILL.md' suggest a focus on financial extraction rather than the stated agricultural utility.

能力评估

⚠ Purpose & Capability

The skill's stated purpose (forecasting) aligns with the included forecasting code, but the registry metadata claims no required environment variables while the code requires billing credentials (SKILLPAY_API_KEY / SKILLPAY_SKILL_ID) to call an external billing API. README/other docs also mention different env var names (SKILL_BILLING_API_KEY / SKILL_ID). This mismatch between what is declared and what the code needs is incoherent and could cause accidental credential exposure.

⚠ Instruction Scope

Runtime docs instruct running scripts that read/write files under ~/.openclaw/ (trial and subscription data) and call an external billing endpoint. The SECURITY/FAQ claims (e.g., 'No agricultural data is ever stored' and 'User ID hashed') contradict the code: TrialManager stores user_id as a JSON key (raw), and the SkillPay integration sends user_id/API key to skillpay.me. The SKILL.md also contains repeated promotional content and inconsistent trial counts (200 vs 10), indicating sloppy or misleading documentation.

ℹ Install Mechanism

There is no install spec (instruction-only in registry), but the skill includes multiple executable scripts (python scripts and a shell daemon). That is lower-risk than remote installers, but the presence of auto-evolve-daemon.sh means the codebase can be run to create a persistent background process if executed. No external downloads or obscure URLs are used in the provided files.

⚠ Credentials

The skill requires billing credentials to function, but the registry declares no required env vars. Furthermore, the code and docs disagree on env var names (SKILLPAY_API_KEY / SKILLPAY_SKILL_ID vs SKILL_BILLING_API_KEY / SKILL_ID), increasing the chance a user will mistakenly expose the wrong secret. Optional keys (OpenWeather, OpenAI) are mentioned in docs but not consistently enforced. Trial data is stored locally and contains raw user IDs despite docs claiming hashed storage.

⚠ Persistence & Privilege

Files include auto-evolve-daemon.sh which runs self_evolve.py in an infinite loop and writes logs into the skill directory; while the skill is not set always:true, the presence of a provided daemon means the skill's author expects/encourages running persistent background processes. This is a risk if users blindly start the daemon — it will run indefinitely and execute the packaged self-evolve logic. The daemon does not, in the presented code, reach out to remote endpoints, but persistent processes increase attack surface and should be treated carefully.

版本历史

v1.4.0

**Changelog for agricultural-output-forecasting v1.4.0** - Major update: Launched limited-time promotional campaign and enhanced pricing/credit options. - SKILL.md: Significant expansion of pricing tiers, subscription packages, and detailed promotional offers (up to 200 free trial calls, extra bonus credits, annual discounts, referral rewards). - Added user testimonials and usage statistics. - Added new file: scripts/subscription.py. - Previous changelog entries and core usage instructions maintained.

v1.3.0

- Added a new Support section, including an EVM address for user contributions. - No other changes to features, API, or behavior.

v1.2.0

agricultural-output-forecasting v1.2.0 - Introduced self-evolution capability with the addition of a self_evolve.py script. - Added an automated daemon (auto-evolve-daemon.sh) for skill updates and evolution. - Integrated performance monitoring via scripts/performance_monitor.py. - Began tracking changes in a new CHANGELOG.md file. - Made updates to core forecasting script and documentation to support new automation features.

v1.0.3

- Added EXAMPLES.md with usage examples. - Added FAQ.md to answer common user questions. - Added GETTING_STARTED.md for onboarding and initial setup guidance. - Added SECURITY.md outlining security and privacy best practices.

v1.0.2

**Free trial added for agricultural-output-forecasting:** - Introduced a free trial with 10 complimentary calls per user before billing begins. - Updated documentation to describe free trial, including changes to API response format (fields: trial_mode, trial_remaining). - Made SkillPay billing API keys only required after the free trial is exhausted. - Adjusted example code and environment variable sections to clarify trial and billing behavior. - Minor version updated to 1.0.1.

v1.0.1

- Added a README.md file with full documentation for easier onboarding. - Updated SKILL.md to include detailed environment variable requirements, optional configuration options, and enhanced security considerations. - Expanded documentation to clarify usage instructions and reference full documentation sources.

v1.0.0

- Initial release of the agricultural-output-forecasting skill. - Predicts crop yields using historical data, weather patterns, and market trends. - Supports multiple crop types including grains, vegetables, fruits, and more. - Provides detailed output: predicted yield, confidence interval, weather/market impacts, and recommendations. - Integrates SkillPay for pay-per-use billing (1 token per call, ~0.001 USDT). - Includes Python and CLI interface examples for quick integration.

元数据

Slug agricultural-output-forecasting

版本 1.4.0

许可证 MIT-0

累计安装 2

当前安装数 2

历史版本数 7

常见问题