research-pipeline

Automate end-to-end research workflows from idea discovery to submission-ready manuscripts.

1|Updated Mar 24, 2026

Search Tags:#automation #research #pipeline #experimentation #publication #idea-discovery

Ready to run

npx skills add https://github.com/kitcaf/skills --skill research-pipeline-kitcaf

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: research-pipeline
Source: https://github.com/kitcaf/skills/tree/main/skills/skills-codex/skills/research-pipeline
Command: npx skills add https://github.com/kitcaf/skills --skill research-pipeline-kitcaf

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Automates the end-to-end research lifecycle, turning vague directions into a structured, experiment-driven path toward publication-ready work.

Core Features & Use Cases

Idea discovery, implementation, experiments, auto-review loop, and final submission packaging.
Literature integration, governance with gating controls, and transparent artifact generation (IDEA_REPORT.md, AUTO_REVIEW.md).
Use Case: A team wants to explore a research direction, run experiments, and auto-revise to submission-ready status.

Quick Start

Launch the full research pipeline with a topic and let it auto-discover ideas, implement experiments, and produce a submission-ready manuscript.

Frequently Asked Questions about research-pipeline

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

FAQPage Schema

How do I automate an end-to-end research pipeline from idea discovery to publication?▼

You can automate an end-to-end research pipeline by providing a broad topic, allowing the system to autonomously discover ideas, run experiments, and package a submission-ready manuscript. This workflow includes literature integration, implementation, and auto-review loops.

Can I set human checkpoints in an automated research workflow?▼

Yes, you can configure human checkpoints using the HUMAN_CHECKPOINT automation control. This allows you to govern the research pipeline stages and review outputs before proceeding to the next phase of experimentation or publication.

How does the auto-review loop work for experiment-driven research?▼

The auto-review loop evaluates experiment results and iterates on the implementation to produce submission-ready papers. It generates transparent artifacts like AUTO_REVIEW.md to log stage-by-stage outputs and self-contained revisions throughout the research lifecycle.

Do I need to manually download arXiv papers for literature integration during research automation?▼

No, you do not need to manually download arXiv papers because the ARXIV_DOWNLOAD automation control handles literature integration autonomously. The pipeline integrates relevant literature directly into the idea discovery and experimentation stages.

What artifacts are generated when running an autonomous experimentation pipeline?▼

Running an autonomous experimentation pipeline generates self-contained artifacts such as IDEA_REPORT.md and AUTO_REVIEW.md. These files provide stage-by-stage output logging for idea discovery, experiment implementation, and final submission packaging.

When should I use configurable gates in a research automation pipeline?▼

You should use configurable gates when you need governance over specific stages of the research lifecycle, such as transitioning from idea discovery to experimentation. Gates ensure structured, experiment-driven progress toward a publication-ready output.