Plant Nutrition Diagnosis Analysis

Problem

Plant nutrient disorders often appear first in leaf color, texture, and morphology, but yellowing alone is not enough. Old-leaf chlorosis, new-leaf fading, interveinal chlorosis, and leaf-margin scorch may point to different nitrogen, phosphorus, potassium, or trace element deficiencies or excesses. The practical issue is deciding which nutrient is likely missing and why.

How the skill works

The skill accepts leaf photos, videos, local files, or network URLs and runs the bundled script to produce a diagnosis:
- Input handling: --input for local jpg/jpeg/png files, or --url for resources downloaded by the API;
- Pattern diagnosis: combines computer vision with plant physiology to assess symptom location and visual patterns;
- Structured output: returns nutrient judgment, cause analysis, fertilization suggestion, and report link;
- History lookup: --list queries cloud report history and returns a Markdown table.

Boundaries

The output is for fertilization reference only; final plans should incorporate soil tests and local agronomy guidance. Photos should show a complete symptomatic leaf under even natural light. Historical reports are read from the cloud API rather than local memory or manual summaries.