dark-factory

Automate software development from natural language goals to production-ready pull requests.

2|2|Updated Mar 6, 2026

Search Tags:#testing #code generation #ai agent #orchestration #pipeline #sealed testing

Ready to run

npx skills add https://github.com/DUBSOpenHub/copilot-skills --skill dark-factory

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: dark-factory
Source: https://github.com/DUBSOpenHub/copilot-skills/tree/main/dark-factory
Command: npx skills add https://github.com/DUBSOpenHub/copilot-skills --skill dark-factory

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill automates the entire process of turning a raw idea into production-ready code, complete with testing and validation, using an AI-driven pipeline.

Core Features & Use Cases

End-to-End Automation: Orchestrates multiple AI agents from product specification to code implementation and testing.
Sealed-Envelope Testing: Ensures code quality by generating tests from the spec before implementation, keeping them hidden from the builder.
Use Case: You need a new CLI tool to audit dependencies. Instead of writing it yourself, you tell Dark Factory the goal, and it delivers a tested, production-ready tool.

Quick Start

Use the dark factory skill to build a CLI that audits dependencies for GPL licenses.

Frequently Asked Questions about dark-factory

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

FAQPage Schema

How do I automate code generation from a natural language goal to a pull request?▼

You can automate code generation by orchestrating a multi-agent AI pipeline that takes a natural language goal and outputs a production-ready pull request with sealed testing. Specialized agents handle product management, architecture, implementation, and validation.

What is sealed-envelope testing in an AI code generation pipeline?▼

Sealed-envelope testing generates tests from the specification before implementation, keeping them hidden from the builder agent. This ensures code quality by validating the implementation against unbiased requirements rather than fitting tests to the code.

Can I use a multi-agent pipeline to build a CLI tool with isolated testing?▼

Yes, a multi-agent pipeline can build a CLI tool end-to-end. It enforces isolation using git worktrees and configuration-driven parameters for models, timeouts, and artifact limits, ensuring a clean, tested production-ready output.

How do AI agents orchestrate software development from product spec to validation?▼

AI agents orchestrate software development by assigning specialized roles for product management, architecture, sealed testing, implementation, and outcome evaluation. This pipeline automates the entire workflow from a raw spec to validated code.

What are the limitations of using an autonomous AI pipeline for software development?▼

The pipeline relies on configuration-driven parameters for models, timeouts, and artifact limits, meaning complex or highly subjective requirements may need manual review. It excels at well-defined tasks like building CLI tools but may require human evaluation for ambiguous goals.

Does dark-factory require any dependencies to run the automated build pipeline?▼

No dependencies are required to run the dark-factory automated build pipeline. It operates independently using scripts, references, and assets to orchestrate the multi-agent workflow from natural language input to a tested pull request.