ethanplusai/astra-flash-orchestrator

What it solves

It reduces the high cost and token usage associated with using a high-end model (Astra) for the entire software development lifecycle. By delegating high-volume, routine implementation tasks to a faster, cheaper model (DeepSeek V4.1 Flash), it preserves the expensive model's capacity for high-level decision-making and final review while significantly lowering API costs.

How it works

The project implements a tiered orchestration workflow where Astra handles the "brain" work and Flash handles the "muscle" work:

1. Planning: Astra defines the scope, design, and task brief.
2. Implementation: A dedicated astra_flash_builder role (powered by DeepSeek V4.1 Flash) performs repository discovery, coding, testing, debugging, and routine QA.
3. Review: Astra reviews the completed patch and evidence provided by Flash to either accept the work or request fixes.
4. Integration: Astra integrates the work and checkpoints the task.

Who it’s for

Developers using a Codex client with GPT-6 Astra and a Codex Router installation who want to maintain high-quality architectural judgment while drastically reducing their compute spend on implementation loops.

Highlights

• Massive Efficiency Gains: Measured up to 98.9% less Astra input and 97%+ lower total compute costs per 1,000 lines of code.
• Native Delegation: Uses a specialized agent role rather than a separate CLI tool.
• Worker-Owned Execution: Flash manages the full implementation loop (discovery to QA) without requiring constant polling from the root model.
• Safety-First Installation: Includes a guarded installation process with dry runs, backups, and an undo receipt to prevent accidental configuration corruption.