jonggrang

Orchestrate AI software development through a 16-phase pipeline with persistent state.

11|2|Updated Apr 7, 2026
One-click install
npx skills add https://github.com/porcupine-md/jonggrang --skill jonggrang
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: jonggrang
Source: https://github.com/porcupine-md/jonggrang/tree/main
Command: npx skills add https://github.com/porcupine-md/jonggrang --skill jonggrang

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

Jonggrang provides a deterministic orchestration platform for AI-powered software development, ensuring discipline, traceability, and repeatable results in feature delivery.

Core Features & Use Cases

  • Two-mode operation (work loop and orchestrate) with a 16-phase pipeline and explicit phase mapping.
  • Two-tier skill system (core BIOS) plus library skills loaded on demand via a gateway.
  • Five-role assembly line (Lead/Developer/Reviewer/TestLead/Tester) enforced by deterministic hooks for quality gates.
  • Persistent state via MANIFEST.yaml with session resume across restarts and parallel work modes.
  • CLI-first workflow and extensible hooks, plugins, and gateways for diverse toolchains.

Quick Start

Plan a feature, decompose it into tasks, implement with AI agents, and verify results using Jonggrang.

Frequently Asked Questions about jonggrang

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

FAQPage Schema
How do I run deterministic AI workflows for software development?▼

Deterministic AI workflows enforce strict quality gates and phase pipelines for software development. You use a CLI to plan features, decompose them into tasks, and implement them with a five-role assembly line that requires typechecks and tests before completion.

What is orchestration in AI-driven feature delivery?▼

Orchestration in AI-driven feature delivery coordinates a 16-phase pipeline with a five-role assembly line. It ensures discipline and traceability by using deterministic hooks to manage quality gates, moving tasks sequentially through Lead, Developer, Reviewer, TestLead, and Tester roles.

Can I resume an AI workflow orchestration after an interruption?▼

Yes, you can resume AI workflow orchestration after interruptions using persistent state. The system saves progress in a MANIFEST.yaml file, allowing you to restart sessions and continue parallel work modes exactly where they left off.

How do AI workflow hooks enforce code quality gates?▼

AI workflow hooks enforce code quality gates by binding strict validation rules to a 16-phase pipeline. They require typechecks, tests, and reviews to pass before a phase can complete, ensuring repeatable results and preventing unverified code from advancing.

Do I need a specific framework to use deterministic AI orchestration?▼

No specific framework is required because deterministic AI orchestration is CLI-first and supports extensible hooks, plugins, and gateways. This design allows it to integrate with diverse toolchains and load library skills on demand via a gateway.

What is the best way to manage AI agents in a software pipeline?▼

The best way to manage AI agents in a software pipeline is using a two-mode workflow with deterministic hooks. This approach maps explicit phases to a five-role assembly line, ensuring agents produce traceable, repeatable results under strict quality constraints.