crop-yield

Audit precision agriculture and crop management software for yield prediction model accuracy, soil analysis integration, irrigation optimization algorithms, pest and disease detection pipelines, satellite and drone imagery processing, weather data integration, and harvest timing optimization. Covers NDVI/EVI index computation, DSSAT/APSIM crop simulation, variable-rate prescription map generation, Penman-Monteith ET estimation, GDD-based maturity modeling, and field-level data pipeline evaluation. Use when reviewing ag-tech platforms, farm management software, remote sensing pipelines, IoT sensor systems, or any codebase that predicts crop yields, optimizes inputs, or processes agricultural data. It's a reusable SKILL.md instruction set that loads into your AI coding assistant on demand, no prompt engineering, no copy-pasting every session.

Run `npx @skills-hub-ai/cli install crop-yield` from your terminal. The CLI writes the SKILL.md to the correct location for your AI tool (e.g. ~/.claude/skills/crop-yield/ for Claude Code or ~/.cursor/skills/ for Cursor with --target cursor) and adds it to your project's .skills.json lockfile.

crop-yield runs in Claude Code. It follows the open Agent Skills standard (SKILL.md), so the same skill works in every supported tool without modification.

Yes. Every skill on skills-hub.ai is free and open-source. There are no premium tiers, paywalls, or usage limits. You only pay for whatever AI assistant you're already using.

In Claude Code, type `/crop-yield` (or whatever slash command the skill registers) and the AI follows the skill's instructions immediately. You can also reference it by name in natural language, your AI loads the skill into context when relevant.

Yes. Commit your project's .skills.json lockfile and teammates run `npx @skills-hub-ai/cli install` (no args) to install every skill at the exact version you pinned. Organization-scoped installs work via skills-hub.ai organizations.