research-workflow

Automate governance and reproducibility for quantitative research workflows.

Updated Mar 2, 2026

Search Tags:#workflow #research #provenance #reproducibility #notebooks #experiments #artifact-promotion

Ready to run

npx skills add https://github.com/Leiisawesome/feelies --skill research-workflow-leiisawesome

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: research-workflow
Source: https://github.com/Leiisawesome/feelies/tree/main/.cursor/skills/research-workflow
Command: npx skills add https://github.com/Leiisawesome/feelies --skill research-workflow-leiisawesome

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Research environment conventions for reproducible quantitative experiments. This skill defines a structured lifecycle and governance to ensure experiment provenance from hypothesis to promotion, bridging notebook exploration and production-ready artifacts.

Core Features & Use Cases

Establishes a reproducible lifecycle from hypothesis to promotion
Enforces notebook discipline, provenance, and artifact versioning
Guides experiment tracking, backtest-ready handoffs, and auditability
Supports notebook-to-production handoff and artifact promotion across the research lifecycle

Quick Start

Define a hypothesis, run explorations in notebooks, formalize results into production-ready modules, and enable promotion through the governance pipeline

Frequently Asked Questions about research-workflow

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I make quantitative research notebooks reproducible and production-ready?▼

To establish provenance in quantitative research workflows, you capture experiment tracking data, enforce notebook discipline, version artifacts, and apply promotion gates to ensure auditable handoffs from hypothesis to production.

What is the best way to track experiment provenance from hypothesis to promotion?▼

The best way to track experiment provenance is to automate governance across the research lifecycle, defining a hypothesis, running explorations in notebooks, and formalizing results into production-ready modules through artifact promotion gates.

How do I enforce notebook discipline and artifact versioning for backtest-ready experiments?▼

You enforce notebook discipline and artifact versioning for backtest-ready experiments by applying automated governance processes, linting rules, and promotion gates that ensure auditable, provenance-captured artifacts across the research lifecycle.

Can I use this workflow for notebook-to-production handoffs and artifact promotion?▼

Yes, the workflow explicitly supports notebook-to-production handoffs by formalizing exploratory notebook results into production-ready modules, applying promotion gates, and ensuring artifact auditability throughout the research lifecycle.

What do I need to set up to start governing reproducibility for quantitative experiments?▼

To start governing reproducibility for quantitative experiments, you need to define a hypothesis, run explorations in notebooks, and enable promotion through the governance pipeline to formalize results into production-ready modules.