evolutionary-design

Generate a constraint block from frontmatter to guide feature planning.

Updated Mar 12, 2019
One-click install
npx skills add https://github.com/gustavofsantos/dot-files --skill evolutionary-design-gustavofsantos
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: evolutionary-design
Source: https://github.com/gustavofsantos/dot-files/tree/main/skills/evolutionary-design
Command: npx skills add https://github.com/gustavofsantos/dot-files --skill evolutionary-design-gustavofsantos

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Enables teams to start with a minimal, end-to-end capability and iteratively expand, reducing risk and rework.

Core Features & Use Cases

  • Provides a formal constraint block to guide planning in Claude Code sessions.
  • Encourages building a single end-to-end slice before expanding to subsequent features.
  • Useful for greenfield work, API or module design, and feature integrations.

Quick Start

Paste the constraint block below into the card's Context section before starting the session.

Frequently Asked Questions about evolutionary-design

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

FAQPage Schema
How do I plan new software features incrementally to avoid rework?

Incremental feature planning uses a constraint-driven approach to start with a minimal, end-to-end slice before expanding. This reduces risk and rework by ensuring a single working capability is completed first.

What is a thin slice approach for greenfield software design?

A thin slice approach builds one end-to-end minimal capability before adding subsequent features. It provides a formal constraint block to guide planning sessions, ensuring the foundational design satisfies core requirements first.

How do I generate a constraint block for feature planning sessions?

You generate a constraint block by applying a frontmatter-driven description to guide implementation. Paste the generated block into the session's context section to direct the planning logic for your feature integration.

Does evolutionary design work for API and module integrations?

Evolutionary design works for API and module integrations by applying a repeatable constraint-driven approach. It ensures you build a minimal end-to-end integration slice before expanding into broader feature sets.

When should I not use incremental design planning?

Incremental design planning may not suit projects requiring comprehensive upfront architecture rather than iterative expansion. It focuses on building minimal end-to-end slices, which might constrain contexts needing immediate full-scale feature delivery.