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one-aisama / ai-dev-framework

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A spec-first, quality-gated development framework for AI-assisted software production with Claude Code

10
0
100% credibility
Found Mar 27, 2026 at 10 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

A template-based framework that structures AI-assisted coding into a pipeline of specifications, test stubs, sequential agent roles, reviews, and automated quality checks for producing reliable software modules.

How It Works

1
🔍 Discover the framework

You find this helpful guide online that turns chaotic AI coding into a reliable step-by-step process for building software.

2
📁 Start your project

You make a copy of the ready-made template to set up your own project folder in moments.

3
✏️ Plan your feature

You write a clear description of what the new feature should do, like a shopping list for the AI builders.

4
🧪 Prepare test guides

You set up simple failing tests first, creating a roadmap that forces the AI to build exactly what you need.

5
🤖 Direct AI helpers

You guide specialized AI team members one by one to design the data, build the core logic, add the user screens, and review everything.

6
🔍 Check quality gates

You run automatic scans that catch sloppy code, hidden dangers, or missing pieces, ensuring everything is solid.

🎉 Enjoy reliable code

Your new feature is complete, fully tested, secure, and ready to use without worries.

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AI-Generated Review

What is ai-dev-framework?

This Python-based ai dev framework structures AI-assisted software production with Claude Code into a spec-first, quality-gated pipeline. It solves the chaos of inconsistent AI-generated code—missing tests, edge cases, and error handling—by enforcing detailed specs upfront, generating failing TDD stubs via CLI, and running sub-agents for specialized roles like architecting, implementing, and reviewing. Developers get a repeatable process that outputs production-ready modules with automated GO/NO-GO verdicts.

Why is it gaining traction?

It stands out by ditching probabilistic prompting for deterministic scripts that enforce rules, like three-tier quality gates checking stability, code balance (no secrets, oversized functions), and regressions against baselines. The handoff protocol between read-only reviewers and builders prevents self-review bias, while CLI commands prep modules and validate output. Devs notice fewer "vibe coding" loops and code that actually ships.

Who should use this?

Solo full-stack devs or small teams building Python/TS apps with Claude, especially for modular features like auth or APIs where AI speed meets quality demands. Ideal for backend engineers iterating on business logic or frontend devs handling forms and states, tired of manual test stubs and secret leaks in prototypes.

Verdict

Promising early framework for disciplined AI dev, but at 10 stars and 1.0% credibility score, it's immature—lean docs and no broad testing mean test it on toy projects first. Worth forking if you want spec-first structure in production workflows.

(178 words)

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