Agri Intelligence

Other

Smart agriculture analytics assistant - crop disease identification, planting optimization, yield prediction, and agricultural market intelligence. Supports multi-region farming data analysis.

Install

openclaw skills install agri-intelligence

Agri Intelligence - Smart Agriculture AI Skill

Core Capabilities

CapabilityDescription
Crop Disease IDIdentify crop diseases from images or symptom descriptions with treatment recommendations
Planting CalendarGenerate optimized planting schedules based on region, climate zone, and crop type
Yield PredictionPredict harvest yields using historical data, weather patterns, and soil conditions
Market IntelligenceTrack agricultural commodity prices across major markets, supply-demand analysis
Soil AnalysisInterpret soil test results and recommend fertilization strategies
Pest ManagementIntegrated 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