plant-management

Centralize plant registry management with JSON schema validation and deterministic care evaluation.

Updated Mar 30, 2026
One-click install
npx skills add https://github.com/D-o-c-labs/Plant-management-skills --skill plant-management
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: plant-management
Source: https://github.com/D-o-c-labs/Plant-management-skills/tree/main/skill
Command: npx skills add https://github.com/D-o-c-labs/Plant-management-skills --skill plant-management

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires requests, jsonschema, and includes scripts (resource) components.

What problem does it solve?

Managing household plant data, care schedules, and reminders can be error-prone without a single source of truth. This skill provides a centralized, schema-validated registry with a deterministic evaluation engine to surface timely care actions.

Core Features & Use Cases

  • Central plant registry with JSON-backed data model and schema validation
  • Deterministic care evaluation to surface due actions and reminders
  • CLI-based workflows for plants, locations, microzones, irrigation systems, events, and lookups

Quick Start

Initialize a fresh data directory with the CLI and then add your first plant, then run python3 scripts/plant_mgmt_cli.py eval run to view due actions.

Frequently Asked Questions about plant-management

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate plant care reminders using a CLI?

You can automate plant care reminders by running the CLI evaluation engine against a centralized, schema-validated registry to surface deterministic care actions and maintenance schedules.

What is deterministic plant registry management for household plants?

Deterministic plant registry management provides a single source of truth for plant data and care profiles by enforcing data integrity with JSON schemas, ensuring reliable evaluation of care events.

How do I validate plant care data and enforce schemas for multiple locations?

You validate plant care data by applying JSON schemas to the registry entries, enforcing data integrity across plants, locations, microzones, and irrigation systems within the CLI workflows.

Do I need Python dependencies to run plant registry and reminder scripts?

Yes, you need the requests and jsonschema Python dependencies installed to execute the CLI scripts that handle data validation and environment-driven configuration for the registry.

Can I manage irrigation systems and microzones via command line workflows?

Yes, the CLI provides dedicated workflows to manage irrigation systems, microzones, and locations, centralizing plant data and care profiles into a validated registry for deterministic evaluation.

What's the best way to track due plant care actions without manual errors?

The best way to track due actions is initializing a data directory via CLI, adding plants to the registry, and running the evaluation engine to deterministically surface timely care reminders.