storm

Generates grounded, long-form articles via STORM-style multi-perspective Q&A and retrieval.

5|Updated Aug 8, 2016
One-click install
npx skills add https://github.com/gbencke/dotfiles --skill storm
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: storm
Source: https://github.com/gbencke/dotfiles/tree/main/pi/skills/storm
Command: npx skills add https://github.com/gbencke/dotfiles --skill storm

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill eliminates the pain of turning vague topics into deeply researched, well-structured, citation-backed long-form articles.

Core Features & Use Cases

  • Deep research to outline to article: Converts a topic into a draft outline, refined outline, and fully assembled final article using multi-perspective retrieval and Q&A.
  • Source-grounded writing with citation integrity: Ensures every visited/used source is preserved locally and cited in the final article’s References table.
  • Human checkpoints at every critical stage: Stops for approvals during perspective selection, research depth validation, outline approval, section review, and final review.

Quick Start

Ask the AI to run the STORM pipeline for the topic “How AI code agents work end-to-end,” stopping at each human checkpoint and producing a 50,000+ word final article with properly generated citations.

Frequently Asked Questions about storm

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

FAQPage Schema
How do I generate a long-form research article with citations from a single topic?

To generate a long-form research article with citations, provide a topic to trigger STORM-style synthesis. The pipeline creates an outline, gathers facts via multi-perspective Q&A, and drafts sections into a heavily cited final article.

What is multi-perspective Q&A in deep research and how does it structure an outline?

Multi-perspective Q&A in deep research simulates different editorial viewpoints to interrogate a topic. This STORM-style mechanism generates questions, retrieves web data, and iteratively refines a topic outline into structured sections.

Can I review and approve the research outline before the full article is generated?

Yes, you can approve the research outline before generation. The workflow enforces human checkpoints at perspective selection, outline approval, and section review, ensuring you validate research depth before the final article drafts.

How does web scraping and knowledge synthesis map citations in a generated research document?

Web scraping and knowledge synthesis map citations by preserving visited sources locally. The pipeline generates deterministic citation mapping via a local references/index.json file and appends a References table to the final article.

What is the minimum word count for a generated deep research article using this workflow?

The minimum word count for a generated deep research article is 50,000 words. The pipeline enforces this length for the final_article.md output to ensure comprehensive topic coverage and deep knowledge synthesis.

Where are the research artifacts and scraped sources stored during the article generation process?

Research artifacts and scraped sources are stored locally under a .storm/<topic-slug> directory. This isolated environment contains the drafted sections, references/index.json, and the final assembled article for deterministic retrieval.