FredAntB

FredAntB / Spec-Driven-Development

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A Claude skill that keeps your AI coding tools from contradicting each other. Generates requirements.md, design.md, and tasks.md before any code is written — then creates matching config files for Claude Code, Cursor, Copilot, Windsurf, and Aider.

ai claude claude-code copilot cursor
31
4
85% credibility
Found May 23, 2026 at 31 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

Spec-Driven Development is a collection of instructions for AI coding assistants that prevents them from building conflicting features or going off in unexpected directions. When you install it, the AI interviews you about your project using simple, focused questions, then generates three planning documents describing what to build, how to structure it, and the exact order to build it. It also creates matching config files for every AI tool your team uses, so Claude Code, Cursor, Copilot, and others all read from the same source of truth and never contradict each other. The project includes a comprehensive test suite to ensure the skill behaves correctly, and is released under a permissive MIT license.

How It Works

1
😐 Tired of AI assistants going rogue

You're working on a project and notice your AI coding helpers keep disagreeing with each other, building things you didn't ask for or contradicting previous work.

2
✨ You find a way to keep everyone in sync

You discover a skill for your AI coding assistant that interviews you about what you want to build, then creates a shared plan that every AI must follow before touching any code.

3
📋 You answer a few short questions

The skill asks you one simple question at a time about your project — what it does, who uses it, how you'll launch it — taking time to make sure each answer is complete before moving on.

4
📄 Three files appear with your shared plan

The skill writes three documents: one describing what your system must do, one showing how it's structured, and one listing exactly what to build next and in what order.

5
Depending on your situation, different things happen next
🌱
Starting a new project

You receive configuration files for Claude Code, Cursor, Copilot, and any other AI tools your team uses, so everyone reads from the same plan.

🔧
Adding structure to existing code

The skill studies what you've already built and fills in the gaps, marking anything it isn't sure about so you can confirm it.

🎉 Every AI follows the plan, nothing drifts

Now when you ask any AI to build something, it reads the shared plan first and stays on track. If it wants to do something not in the plan, it stops and asks your permission instead of guessing.

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AI-Generated Review

What is Spec-Driven-Development?

Spec-Driven Development is a Claude skill that interviews you before any code gets written, generating three spec files: requirements.md, design.md, and tasks.md. It then creates matching config files for every AI tool your team uses - Claude Code, Cursor, Windsurf, Copilot, and Aider - so all your agents read from the same source of truth. Built in Python with a 67/67 passing assertion suite and GitHub Actions CI.

Why is it gaining traction?

The core problem it solves is real: teams using multiple AI coding assistants end up with code that contradicts itself because each agent fills gaps with different assumptions. SDD attacks this at the root by enforcing a spec-first workflow where every AI tool must read the spec files before writing any code. The hook is the "divergence protocol" - a hard constraint that tells your AI agents to stop and ask when they want to deviate from the spec, rather than guessing. It also handles existing codebases through a "retrofit" mode that reverse-engineers specs from what you describe.

Who should use this?

Team leads managing developers who each use different AI tools and want consistency across the codebase. Solo developers working on side projects who keep changing their mind mid-build and end up rewriting everything. Developers handed a legacy codebase with no documentation who need to understand what the system actually does. Startups where AI-assisted pair programming is standard practice but code quality is inconsistent.

Verdict

SDD has solid fundamentals - 135 automated assertions, comprehensive documentation, and a structured approach to keeping AI tools aligned. However, with only 31 stars and public beta status, it has not yet been battle-tested across diverse real-world projects. The credibility score of 0.8500000238418579% signals there is still validation work ahead before recommending it for critical production systems. Worth exploring for teams already invested in AI-assisted development workflows, though treat it as an emerging solution rather than a mature standard.

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