command-design

Design bot command interfaces with parsing, validation, and help flows.

1|Updated Oct 16, 2025

Search Tags:#design #validation #commands #parsing #error-handling #bot #help-system

Ready to run

npx skills add https://github.com/forever19735/Garbage --skill command-design

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: command-design
Source: https://github.com/forever19735/Garbage/tree/main/.agent/skills/command-design
Command: npx skills add https://github.com/forever19735/Garbage --skill command-design

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Designers and developers need a structured framework to craft clear, maintainable bot command interfaces with consistent help systems, reducing confusion and onboarding time for users.

Core Features & Use Cases

Command Design: create intuitive command names and syntax that are easy to remember.
Parsing & Validation: robust input parsing and validation to prevent errors.
Help System: build contextual and hierarchical help topics that guide users.
Error Handling: provide consistent, actionable feedback and examples.
Use Case: when building a chat bot, you can design a new command set for a feature like scheduling or reminders and automatically generate help for it.

Quick Start

Define a new bot command like @remind and wire it to parsing and help topics using the patterns shown in this Skill.

Frequently Asked Questions about command-design

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

FAQPage Schema

How do I design intuitive bot commands with clear help systems?▼

Bot command design involves creating intuitive command names, robust input parsing, and validation to prevent errors. It provides a structured framework ensuring consistent syntax and actionable feedback for chat interfaces.

How to build a contextual help system for a chat bot?▼

Build a contextual help system by defining multi-topic help flows within your command structure. This approach guides users through hierarchical topics, providing consistent, actionable feedback and examples for commands like scheduling or member management.

What is the best way to handle input parsing and validation for bot commands?▼

The best way to handle input parsing and validation is using structured implementation patterns with input validation helpers. This prevents errors by ensuring robust data handling before commands execute, providing actionable feedback when validation fails.

Does this command design framework work for scheduling and member management bots?▼

Yes, this command design framework works for scheduling and member management bots. It supports designing new command sets for features like scheduling, reminders, and general queries, automatically generating contextual help for each scenario.

How do I provide consistent error handling and feedback in bot commands?▼

Provide consistent error handling by implementing structured validation helpers and sample implementation patterns. This ensures users receive actionable feedback and examples when commands fail, reducing confusion and improving the bot interaction experience.

Do I need structured frontmatter to implement bot command parsing and help topics?▼

Yes, structured frontmatter is required to implement bot command parsing and help topics. It satisfies documentation and runtime requirements, enabling the system to wire commands to parsing logic and contextual help definitions.