autostar

What problem does it solve?

a* provides a self-contained framework to turn vague improvement goals into a structured, measurable, and repeatable optimisation loop. It converts fuzzy quality aspirations into independent tracks, verifiers, and a disciplined mutation-evaluate-reflect cycle that learns from every attempt.

Core Features & Use Cases

• Onboarding with explicit goal decomposition, track assignment, constraints, and budget before any work begins.
• Multi-track rubric system supporting deterministic, external-tool, llm_judge, hybrid, and human_gate verifiers to quantify progress.
• Durable memory and run artifacts that capture hypotheses, step results, and reflections to enable cross-run learning and improvement.

Quick Start

Describe your goal and I will set up tracks, verifiers, and an initial mission to start the first optimisation loop.