projex-framework

Orchestrate projex workflows across proposals, plans, executions, and reviews.

4|Updated Jan 26, 2026
One-click install
npx skills add https://github.com/No3371/projex --skill projex-framework
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: projex-framework
Source: https://github.com/No3371/projex/tree/main
Command: npx skills add https://github.com/No3371/projex --skill projex-framework

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Projex-framework provides a comprehensive suite of governance workflows for turning ideas into actionable, traceable projex artifacts, enabling reliable collaboration with LLMs.

Core Features & Use Cases

  • Unified skill for multiple projex types: proposals, plans, executions, evaluations, reviews, audits, patches, simulations, and more, all connected via explicit relationships.
  • Git-driven lifecycle: ephemeral branches for execution and simulation, with formal close/walkthroughs to ensure traceability and rollback.
  • Scalable collaboration: supports nested scopes (projex/closed/archived) and cross-repo workflows, enabling complex multi-team projects.
  • Use Case: A product team drafts a proposal, selects a plan, executes in a sandbox, and closes with a walkthrough, all linked and auditable.

Quick Start

Outline the overall goal with your team, then create a Proposal, a Plan, and an Execute to generate a Walkthrough.

Frequently Asked Questions about projex-framework

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

FAQPage Schema
How do I manage AI-assisted project workflows with reliable traceability?

Managing AI-assisted project workflows requires orchestrating proposals, plans, executions, and reviews. This framework automates that lifecycle to ensure reliable, auditable results with structured collaboration, versioned artifacts, and explicit dependencies across multiple repos.

How does git governance work for LLM collaboration workflows?

Git governance for LLM collaboration applies explicit dependencies, lifecycle states, and guardrails to git operations. It uses ephemeral branches for execution and simulation, ensuring formal close procedures, traceability, and rollback capabilities across project states.

What is the best way to structure complex AI project artifacts across teams?

Structuring complex AI project artifacts across teams requires a unified framework connecting proposals, plans, executions, and audits via explicit relationships. It supports nested scopes and cross-repo workflows, enabling scalable multi-team collaboration with full traceability.

Can I use ephemeral branches for AI project execution and simulation?

Yes, you can use ephemeral branches for AI project execution and simulation. This framework applies a git-driven lifecycle that isolates execution and simulation environments, ensuring formal walkthroughs and reliable rollback upon project closure.

Do I need explicit dependencies for AI project governance?

Yes, explicit dependencies are required for AI project governance. This framework enforces explicit relationships between proposals, plans, and executions, satisfying governance requirements by tracking lifecycle states and applying guardrails to git operations.

How do I start an auditable AI project from idea to walkthrough?

To start an auditable AI project, outline your goal, then create a Proposal, a Plan, and an Execute artifact. This generates a formal Walkthrough, linking all phases from initial draft to sandbox execution with full auditability.