research-pipeline

Name: research-pipeline
Availability: InStock
Author: dogekiki

Orchestrate autonomous research workflows from idea discovery to paper generation.

1|Updated Jul 21, 2026

Search Tags:#automation #research #academic #pipeline #experimentation #autonomous

Ready to run

npx skills add https://github.com/dogekiki/SP-test --skill research-pipeline-dogekiki

💬 Prompt for ChatGPT / Claude Chat▼

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

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill solves the fragmentation of the research lifecycle by automating the entire process from initial idea discovery and experimental validation to final paper drafting.

Core Features & Use Cases

Autonomous Research Lifecycle: Orchestrates idea discovery, experiment implementation, cross-model code review, and paper writing in a single pipeline.
Resilient Execution: Features stall detection, structural pivoting, and state-tracking to ensure long-running research tasks complete successfully even after interruptions.
Use Case: A researcher can provide a broad direction, and the system will autonomously generate hypotheses, run experiments, iterate based on adversarial reviews, and produce a formatted paper draft.

Quick Start

Invoke the research-pipeline skill with your research topic to initiate the full autonomous lifecycle.

Frequently Asked Questions about research-pipeline

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

FAQPage Schema

How do I automate the academic research lifecycle from idea generation to paper writing?▼

To automate the academic research lifecycle, you need an autonomous pipeline that orchestrates idea discovery, experiment execution, and paper generation. This skill handles the entire workflow by integrating iterative review loops and automated code validation into a continuous research cadence.

What is the best way to run continuous experiments and generate academic papers autonomously?▼

The best way to run continuous experiments and generate academic papers is using an autonomous research pipeline. It orchestrates hypothesis generation, executes experiments, performs cross-model code reviews, and drafts the final paper automatically while maintaining a continuous research cadence.

Can I use an autonomous research pipeline to handle long-running experimentation tasks without stalling?▼

Yes, autonomous research pipelines can handle long-running experimentation tasks without stalling. This skill features built-in stall detection, structural pivoting, and state-tracking mechanisms to ensure that complex research lifecycles complete successfully even after interruptions.

Do I need a specific environment setup to run an end-to-end autonomous research workflow?▼

Yes, you need a structured environment with access to experiment runners, review models, and document generation tools. The pipeline relies on these external components to validate code, perform adversarial reviews, and maintain the continuous research cadence required for paper generation.

How does cross-model code review work in an autonomous experimentation pipeline?▼

Cross-model code review in an autonomous experimentation pipeline works by integrating adversarial review models that iteratively validate experiment code. This automated review loop ensures the structural integrity and accuracy of the implementation before proceeding to the final paper drafting phase.

Why does my automated research pipeline stall during complex experiment implementation?▼

Automated research pipelines stall during complex experiment implementation due to execution bottlenecks or structural failures. This skill mitigates stalling through built-in stall detection mechanisms and structural pivoting, allowing the workflow to recover and maintain a continuous research cadence.