pp-core

The Pareto Framework.

A light-weight meta-prompting, context engineering, and spec-driven development system for Claude Code, OpenCode, Gemini CLI, Kimi CLI, Kilo, Codex, Copilot, Cursor, Windsurf, and more.

What is pp-core

pp-core is a context-engineering and spec-driven development framework that drives AI coding agents (Claude Code, Codex, Gemini CLI, Kimi CLI, Copilot, Cursor, and more) through a disciplined phase loop. It solves context rot — the quality degradation that accumulates as an AI fills its context window — by running all heavy research, planning, and execution work in fresh-context subagents while keeping your main session lean.

How it works

Each milestone repeats the same five-step loop, one phase at a time:

1. Discuss — capture implementation decisions before anything is planned
2. Plan — research, decompose, and verify the plan fits a fresh context window
3. Execute — run plans in parallel waves; each executor starts with a clean 200k-token context
4. Verify — walk through what was built; diagnose and fix before declaring done
5. Ship — create the PR, archive the phase, repeat for the next one

Quickstart

npx @pareto4/pp-core@latest

The installer prompts for your runtime (Claude Code, OpenCode, Gemini CLI, Kimi CLI, Kilo, Codex, Copilot, Cursor, Windsurf, and more) and whether to install globally or locally. The installer is required for cross-runtime compatibility — do not copy files from agents/ or commands/ directly.

On another runtime or without Node.js? See Install on your runtime.

Once installed, start your first project:

/pp-new-project

New here? Follow Your first project for a guided walkthrough from install to first shipped phase.

Documentation

Tutorials — learning by doing:

• Your first project
• Onboarding an existing codebase

How-to guides — task-focused recipes:

• Install on your runtime
• Plan a phase
• Verify and ship
• … see all how-to guides

Reference — authoritative facts:

• Commands
• Configuration
• CLI tools

Explanation — concepts and design decisions:

• Context engineering
• The phase loop
• Architecture

Full index: docs/README.md.

Why it works

Most AI-coding setups fail at scale because context bloat silently degrades output quality, there is no shared memory between sessions, and nothing verifies that code actually works. pp-core solves all three: heavy work runs in fresh subagents, structured artifacts like STATE.md and CONTEXT.md survive session boundaries, and the verify step walks through what was built and generates fix plans before a phase is declared done. See docs/explanation/context-engineering.md for the full reasoning.

Troubleshooting? See docs/how-to/recover-and-troubleshoot.md.

License

MIT License. See LICENSE for details.

Claude Code is powerful. pp-core makes it reliable.