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Orchestrate iterative research analysis workflows with script generation and documentation updates.

1|Updated Apr 19, 2026
Search Tags:#workflow orchestration#data analysis#project analysis#research automation#iterative research
One-click install
npx skills add https://github.com/hsigstad/research-kit --skill next-hsigstad
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: next
Source: https://github.com/hsigstad/research-kit/tree/main/skills/next
Command: npx skills add https://github.com/hsigstad/research-kit --skill next-hsigstad

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pandas, numpy, scikit-learn, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill streamlines the iterative analysis process for research projects, orchestrating the workflow from proposing the next analysis to propagating the results across various documentation files.

Core Features & Use Cases

  • Analysis Loop Orchestration: Automates the entire analysis cycle, from accepting proposals to finalizing and propagating results.
  • Customizable Commands: Supports various commands for different stages of the analysis, like proposing the next task, specifying a detailed task, or executing autonomously.
  • Integrated Documentation Propagation: Updates and creates documentation files based on the analysis outcomes.
  • Use Case: For a researcher in the middle of a project, this Skill can help automatically propose the next task, generate the analysis script, run the analysis, and update the project documentation accordingly.

Quick Start

To begin the analysis cycle, run: /next

Frequently Asked Questions about next

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

FAQPage Schema
How do I automate iterative research workflows with Claude Code syntax?▼

Automate iterative research workflows by running the `/next` command to orchestrate the analysis cycle, which proposes tasks, generates scripts, executes data analysis, and propagates results across documentation files.

What is research workflow orchestration for project analysis cycles?▼

Research workflow orchestration automates the iterative analysis process, handling state transitions from proposing the next analysis task to generating scripts, running data analysis, and automatically updating project documentation.

Do I need pandas and scikit-learn installed to run data analysis orchestration?▼

Yes, this data analysis orchestration requires pandas, numpy, and scikit-learn installed in your environment, as these dependencies support the script generation and execution tasks within the research automation workflow.

How do I propagate analysis results to documentation files in an automated research workflow?▼

Propagate analysis results to documentation files through integrated documentation propagation, which automatically updates and creates project documentation based on the outcomes of the executed data analysis tasks.

What are the limitations of using workflow orchestration for iterative research analysis?▼

A key limitation is that this workflow orchestration requires prior knowledge of your project layout and uses Claude Code syntax, meaning it cannot operate effectively without a clearly defined project structure and compatible environment.

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