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Agri Intelligence

Agri Intelligence 是农业场景分析助手,可根据作物、地区、土壤和历史数据,输出病害诊断、种植日历、产量预测、农产品市场行情及土壤与虫害管理建议,并以报告形式给出可执行方案;不包含独立数据接口或检测工具。

ai-gaoqian
ai-gaoqian
热度 20.96
最近更新 2026-06-12 14:14:59
分类:数据依赖:纯提示词应用场景:市场分析 / 报告撰写 / 推荐 / 研究 ...

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执行命令安装此 skill: npx secure-skills-cli add agri-intelligence
Metadata
name
Agri Intelligence
slug
agri-intelligence
description
Smart agriculture analytics assistant - crop disease identification, planting optimization, yield prediction, and agricultural market intelligence. Supports multi-region farming data analysis.
version
1.0.0
author
ai-gaoqian
tags
["agriculture","farming","crop-analysis","yield-prediction","agritech","smart-farming"]
metadata
{"openclaw":{"requires":"openclaw>=2.0.0"}}

Agri Intelligence - Smart Agriculture AI Skill

Core Capabilities

Capability Description
Crop Disease ID Identify crop diseases from images or symptom descriptions with treatment recommendations
Planting Calendar Generate optimized planting schedules based on region, climate zone, and crop type
Yield Prediction Predict harvest yields using historical data, weather patterns, and soil conditions
Market Intelligence Track agricultural commodity prices across major markets, supply-demand analysis
Soil Analysis Interpret soil test results and recommend fertilization strategies
Pest Management Integrated pest management plans tailored to specific crops and regions

Trigger Scenarios

  • "What disease is affecting my tomato plants?"
  • "When should I plant wheat in Henan province?"
  • "Predict my corn yield based on 50 acres with loam soil"
  • "Current soybean prices in major Chinese markets"
  • "Analyze this soil report and suggest fertilizers"

Execution Flow

Phase 1: Context Gathering

  • Collect crop type, region, field size, soil data, and historical records
  • Request images if disease/ pest identification is needed

Phase 2: Domain Analysis

  • Cross-reference symptoms with agricultural pathology database
  • Factor in regional climate data and seasonal patterns
  • Apply crop-specific growth models for yield estimation

Phase 3: Recommendation Output

  • Disease: diagnosis confidence score, treatment options (organic/chemical), prevention tips
  • Planting: week-by-week calendar with action items
  • Market: price trends table with buy/sell timing suggestions
  • Yield: predicted range with confidence interval and key influencing factors

Output Template

## Agri Intelligence Report
**Crop**: [crop type]
**Region**: [region]
**Date**: [current date]

### Analysis Results
[Key findings]

### Recommendations
[Actionable steps with priority levels]

### Data Sources
- [Source 1]
- [Source 2]

Notes

  • Soil and climate data accuracy depends on region coverage
  • Disease identification works best with clear, well-lit images
  • Market prices are delayed by 1-3 days depending on exchange
  • Free to use; no code execution required