module-design — for Claude Code module-design, better-webhook, community, for Claude Code, ide skills, capture-replay-webhook, local-first-webhook, typesafe-webhook, webhook, webhook-receiver

v1.0.0

Sobre este Skill

Cenario recomendado: Ideal for AI agents that need design an interface. Resumo localizado: Unified toolkit for working with webhooks # Design an Interface Based on "Design It Twice" from "A Philosophy of Software Design": your first idea is unlikely to be the best. It covers better-webhook, capture-replay-webhook, local-first-webhook workflows. This AI agent skill

Recursos

Design an Interface
Gather Requirements
Before designing, understand:
[ ] What problem does this module solve?
[ ] Who are the callers? (other modules, external users, tests)

# Tópicos principais

endalk200 endalk200
[5]
[2]
Atualizado: 4/24/2026

Skill Overview

Start with fit, limitations, and setup before diving into the repository.

Cenario recomendado: Ideal for AI agents that need design an interface. Resumo localizado: Unified toolkit for working with webhooks # Design an Interface Based on "Design It Twice" from "A Philosophy of Software Design": your first idea is unlikely to be the best. It covers better-webhook, capture-replay-webhook, local-first-webhook workflows. This AI agent skill

Por que usar essa habilidade

Recomendacao: module-design helps agents design an interface. Unified toolkit for working with webhooks # Design an Interface Based on "Design It Twice" from "A Philosophy of Software Design": your first idea is

Melhor para

Cenario recomendado: Ideal for AI agents that need design an interface.

Casos de Uso Práticos for module-design

Caso de uso: Design an Interface
Caso de uso: Gather Requirements
Caso de uso: Before designing, understand:

! Segurança e Limitações

  • Limitacao: Ask: "What does this module need to do? Who will use it?"
  • Limitacao: Spawn 3+ sub-agents simultaneously using Task tool. Each must produce a radically different approach.
  • Limitacao: Don't let sub-agents produce similar designs - enforce radical difference

About The Source

The section below is adapted from the upstream repository. Use it as supporting material alongside the fit, use-case, and installation summary on this page.

Demo Labs

Browser Sandbox Environment

⚡️ Ready to unleash?

Experience this Agent in a zero-setup browser environment powered by WebContainers. No installation required.

Boot Container Sandbox

FAQ e etapas de instalação

These questions and steps mirror the structured data on this page for better search understanding.

? Perguntas frequentes

O que é module-design?

Cenario recomendado: Ideal for AI agents that need design an interface. Resumo localizado: Unified toolkit for working with webhooks # Design an Interface Based on "Design It Twice" from "A Philosophy of Software Design": your first idea is unlikely to be the best. It covers better-webhook, capture-replay-webhook, local-first-webhook workflows. This AI agent skill

Como instalar module-design?

Execute o comando: npx killer-skills add endalk200/better-webhook. Ele funciona com Cursor, Windsurf, VS Code, Claude Code e mais de 19 outros IDEs.

Quais são os casos de uso de module-design?

Os principais casos de uso incluem: Caso de uso: Design an Interface, Caso de uso: Gather Requirements, Caso de uso: Before designing, understand:.

Quais IDEs são compatíveis com module-design?

Esta skill é compatível com Cursor, Windsurf, VS Code, Trae, Claude Code, OpenClaw, Aider, Codex, OpenCode, Goose, Cline, Roo Code, Kiro, Augment Code, Continue, GitHub Copilot, Sourcegraph Cody, and Amazon Q Developer. Use a CLI do Killer-Skills para uma instalação unificada.

module-design tem limitações?

Limitacao: Ask: "What does this module need to do? Who will use it?". Limitacao: Spawn 3+ sub-agents simultaneously using Task tool. Each must produce a radically different approach.. Limitacao: Don't let sub-agents produce similar designs - enforce radical difference.

Como instalar este skill

  1. 1. Abra o terminal

    Abra o terminal ou linha de comando no diretório do projeto.

  2. 2. Execute o comando de instalação

    Execute: npx killer-skills add endalk200/better-webhook. A CLI detectará sua IDE ou agente automaticamente e configurará a skill.

  3. 3. Comece a usar o skill

    O skill já está ativo. Seu agente de IA pode usar module-design imediatamente no projeto atual.

! Source Notes

This page is still useful for installation and source reference. Before using it, compare the fit, limitations, and upstream repository notes above.

Upstream Repository Material

The section below is adapted from the upstream repository. Use it as supporting material alongside the fit, use-case, and installation summary on this page.

Upstream Source

module-design

Install module-design, an AI agent skill for AI agent workflows and automation. Explore features, use cases, limitations, and setup guidance.

SKILL.md
Readonly
Upstream Repository Material
The section below is adapted from the upstream repository. Use it as supporting material alongside the fit, use-case, and installation summary on this page.
Upstream Source

Design an Interface

Based on "Design It Twice" from "A Philosophy of Software Design": your first idea is unlikely to be the best. Generate multiple radically different designs, then compare.

Workflow

1. Gather Requirements

Before designing, understand:

  • What problem does this module solve?
  • Who are the callers? (other modules, external users, tests)
  • What are the key operations?
  • Any constraints? (performance, compatibility, existing patterns)
  • What should be hidden inside vs exposed?

Ask: "What does this module need to do? Who will use it?"

2. Generate Designs (Parallel Sub-Agents)

Spawn 3+ sub-agents simultaneously using Task tool. Each must produce a radically different approach.

Prompt template for each sub-agent:

Design an interface for: [module description]

Requirements: [gathered requirements]

Constraints for this design: [assign a different constraint to each agent]
- Agent 1: "Minimize method count - aim for 1-5 methods max"
- Agent 2: "Maximize flexibility - support many use cases"
- Agent 3: "Optimize for the most common case"
- Agent 4: "Take inspiration from [specific paradigm/library]"

Output format:
1. Interface signature (types/methods)
2. Usage example (how caller uses it)
3. What this design hides internally
4. Trade-offs of this approach

3. Present Designs

Show each design with:

  1. Interface signature - types, methods, params
  2. Usage examples - how callers actually use it in practice
  3. What it hides - complexity kept internal

Present designs sequentially so user can absorb each approach before comparison.

4. Compare Designs

After showing all designs, compare them on:

  • Interface simplicity: fewer methods, simpler params
  • General-purpose vs specialized: flexibility vs focus
  • Implementation efficiency: does shape allow efficient internals?
  • Depth: small interface hiding significant complexity (good) vs large interface with thin implementation (bad)
  • Ease of correct use vs ease of misuse

Discuss trade-offs in prose, not tables. Highlight where designs diverge most.

5. Synthesize

Often the best design combines insights from multiple options. Ask:

  • "Which design best fits your primary use case?"
  • "Any elements from other designs worth incorporating?"

Evaluation Criteria

From "A Philosophy of Software Design":

Interface simplicity: Fewer methods, simpler params = easier to learn and use correctly.

General-purpose: Can handle future use cases without changes. But beware over-generalization.

Implementation efficiency: Does interface shape allow efficient implementation? Or force awkward internals?

Depth: Small interface hiding significant complexity = deep module (good). Large interface with thin implementation = shallow module (avoid).

Anti-Patterns

  • Don't let sub-agents produce similar designs - enforce radical difference
  • Don't skip comparison - the value is in contrast
  • Don't implement - this is purely about interface shape
  • Don't evaluate based on implementation effort

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