Summary
Nate Herk walks through implementing Stanford’s STORM research methodology as a custom Claude Code skill, producing verified multi-perspective research briefings that peer-reviewed testing found 25% more organized than competing methods. STORM — Synthesis of Topic Outlines through Retrieval and Multi-perspective question asking — works by assigning five distinct expert personas (practitioner, academic, skeptic, economist, historian) to independently research a topic, then running a second wave of six verification agents to fact-check findings, rank source reliability on a 1–10 scale, and surface where perspectives contradict each other.
The output is a self-contained HTML report with a 60-second executive summary, reliability-scored key findings, explicit notation of which expert lenses supported or challenged each claim, and a list of analytical blind spots — including a missing sixth lens the report itself flags for follow-up investigation. Herk compares this head-to-head against Claude Code’s native deep research feature, submitting both outputs to Codex for evaluation; Codex rates the STORM HTML briefing superior on evidence quality and depth.
The skill is installed by placing two files — a `skill.md` prompt and an HTML report template — in Claude’s `.claude` folder, after which invoking it requires only a natural language topic prompt. The same skill structure is compatible with Codex and other agent frameworks using their respective config folders. Both files are available free in Herk’s School community. This is a practical guide for anyone wanting systematic, source-verified research automation without relying on single-prompt generation.
📺 Source: Nate Herk | AI Automation · Published June 29, 2026
🏷️ Format: Hands On Build
