self-improving-science

What problem does it solve?

Centralizes capture of learnings, experiment issues, and methodology corrections into structured Markdown logs to improve reproducibility and knowledge sharing across scientific workflows.

Core Features & Use Cases

• Log learnings to LEARNINGS.md, track experiment issues in EXPERIMENT_ISSUES.md, and file feature requests in FEATURE_REQUESTS.md
• Promote broadly applicable insights to experiments checklists, model cards, data governance docs, or tooling guidance
• Link learnings to related files, datasets, and models to build a traceable knowledge base for audits and future experiments

Quick Start

Create the .learnings directory and initial log files, then begin recording your first learning entry.