lightningrod-assistant

What problem does it solve?

It helps you turn real-world signals into high-quality forecasting datasets and then fine-tune models from those datasets, without ad-hoc experimentation.

Core Features & Use Cases

• Forecasting-dataset guidance: Builds a pipeline that generates yes/no or numeric forecasting questions from appropriate inputs (often news) with consistent temporal resolution.
• Fine-tuning workflow: Guides you through GRPO-style fine-tuning patterns and the required evaluation setup.
• Quality loop: Enforces a test-at-scale and dataset-lint review step so you can spot framing or label issues before scaling up.

Quick Start

Tell the assistant what you want to forecast (including the general topic and target time horizon), and it will propose example forecasting questions and the next steps to generate and fine-tune your dataset.