Multi-AI Planning

Overview

multi-ai-planning creates comprehensive, agent-executable plans for complex objectives using verification-first approach, hierarchical task decomposition, and rigorous quality validation.

Purpose: Transform objectives into structured, validated plans that agents can execute reliably

Pattern: Workflow-based (6-step sequential process)

Key Innovation: Plans are schema-validated, quality-scored (≥90/100), and designed for multi-agent parallel execution with built-in verification and checkpoint systems.

Core Principles (validated by Claude + Gemini + Codex):

1. Verification-First: Define success criteria before implementation
2. Hierarchical Decomposition: Break down to atomic, executable steps
3. Explicit Dependencies: Map all dependencies, identify parallel opportunities
4. Quality Gates: Multi-layer validation before execution
5. Safe Checkpoints: Git tags + patches for resumption and rollback