storm-research

name	storm-research
description	Use this skill when the user wants deep, PhD-level, multi-perspective research on a topic and says things like "storm research <topic>", "run STORM on <topic>", "deep research <topic>", "research <topic> from every angle", "multi-perspective deep dive", "give me a PhD-level briefing on <topic>", "research <topic> properly", "I need to really understand <topic>", or "brief me on <topic> before I decide/invest/write/present". Orchestrates five expert persona agents, a contradiction map, a synthesized cited briefing, and an adversarial peer review. Inspired by Stanford's STORM method.
version	1.0.0
user-invocable	true

STORM Research — Multi-Perspective Deep Research Orchestrator

Run the full STORM pipeline on a topic. One prompt asks one question and returns the majority view — the surface. STORM asks the same topic from five independent expert lenses, maps where they fight, synthesizes a briefing no single expert could write, then red-teams its own output. In Stanford's peer-reviewed testing, multi-perspective articles were ~25% more organized and ~10% broader than single-pass research. This skill operationalizes that with dedicated sub-agents so the heavy reading happens off the main context window.

The Pipeline

Topic
 └─ Phase 1  FAN-OUT (parallel): practitioner · skeptic · economist · historian · academic
 └─ Phase 2  CONTRADICTION MAP: contradiction-mapper reads all 5 → finds clashes/agreement/gaps
 └─ Phase 3  SYNTHESIS: synthesizer reads 5 + map → cited research briefing
 └─ Phase 4  PEER REVIEW: peer-reviewer audits the briefing → reliability grade + fixes
 └─ Present consolidated result to the user

Workflow

Step 0 — Scope the Topic

1. Get the topic. If the user supplied one (storm research <topic>), use it. If it's vague or sprawling (e.g. "AI", "the economy"), ask one sharpening question to narrow it — a tight topic produces a far better briefing than a broad one.
2. Capture the audience and angle if offered (deciding / investing / writing / presenting / learning). It tunes the synthesizer's recommendations. Don't interrogate — one optional ask.
3. Derive a slug (lowercase, hyphenated, canonical: e.g. lab-grown-meat-viability).
4. Set the workspace: .storm/{slug}/. Create it: mkdir -p .storm/{slug}.

Step 0.5 — Tune the Panel (optional, powerful)

The five default personas fit most topics. For some topics, a swap sharpens the analysis — e.g. add a Clinician for a medical topic, a Regulator for a policy topic, an End User for a product topic. If a swap clearly helps, mention it to the user and spawn the extra persona with the Task tool using the same output contract as the built-in agents (worldview + owned bias + evidence-gathering + structured file with sources). Keep the panel at 5–6; more dilutes. Default to the standard five if unsure.

Step 1 — Fan Out the Five Perspectives (parallel)

Launch all five persona agents in a single message with five Task tool calls so they run concurrently. Give each the topic, the workspace path, and its output filename. Example prompt per agent:

"Topic: {topic}. Workspace: .storm/{slug}/. Write your analysis to .storm/{slug}/{persona}.md following your output contract. Audience for downstream use: {audience}. Gather real evidence with WebSearch/WebFetch and cite it."

• practitioner → .storm/{slug}/practitioner.md
• skeptic → .storm/{slug}/skeptic.md
• economist → .storm/{slug}/economist.md
• historian → .storm/{slug}/historian.md
• academic → .storm/{slug}/academic.md

Each agent writes its own file and returns only a one-line confirmation, keeping your context lean. If a persona agent fails, note it and continue — the pipeline degrades gracefully with four perspectives; tell the downstream agents which files exist.

Step 2 — Map the Contradictions

When all perspective files exist, spawn the contradiction-mapper agent (single Task call):

"Topic: {topic}. Workspace: .storm/{slug}/. Read the perspective files that exist ({list}) and write .storm/{slug}/contradiction-map.md per your output contract."

Step 3 — Synthesize the Briefing

Spawn the synthesizer agent (single Task call):

"Topic: {topic}. Workspace: .storm/{slug}/. Read all perspective files and contradiction-map.md; write the research briefing to .storm/{slug}/briefing.md. Audience: {audience}. Carry citations forward."

Step 4 — Peer Review (close STORM's blind spot)

Spawn the peer-reviewer agent (single Task call):

"Topic: {topic}. Workspace: .storm/{slug}/. Audit briefing.md against the perspective files and contradiction map; spot-check shaky claims with WebSearch; write .storm/{slug}/peer-review.md with a reliability grade and ranked fixes."

Step 4.5 — Optional Revision Loop

If the peer review returns a grade of C or below, or flags high-severity factual problems, offer the user a single revision pass: re-spawn the synthesizer with the peer review attached and instructions to fix the ranked issues, then re-run the peer review. Do this only if the user wants it — don't loop unprompted.

Step 5 — Present the Result

Read briefing.md and peer-review.md and present a tight consolidated summary in chat (not the full files — point to them):

STORM Research Complete — {topic}
==================================
Workspace: .storm/{slug}/

Reliability grade: {grade} ({High/Medium/Low})

Headline finding
  {1–2 sentences from the executive summary}

Central tension
  {the key contradiction and how to think about it}

Top recommendation
  {the headline action, tuned to the audience}

⚠ Peer-review flags
  • {top 1–3 required fixes, if any}

Artifacts
  • .storm/{slug}/briefing.md          ← the full cited briefing
  • .storm/{slug}/contradiction-map.md ← where the experts disagree
  • .storm/{slug}/peer-review.md       ← reliability audit + fixes
  • .storm/{slug}/{persona}.md ×5      ← raw perspective analyses

Then ask whether they want the full briefing inline, a revision pass, or a deeper dive on any single perspective.

Notes

• Why sub-agents, not four prompts? The original STORM-in-Claude method is four sequential pastes that flood one context window. Delegating each phase to a dedicated agent keeps the main context clean, runs the five perspectives in true parallel, and lets each persona stay in character without bleeding into the others.
• Credits. The four-prompt method is adapted from Nav Toor's (@heynavtoor) X thread "STORM in Claude: 4 Prompts for PhD-Level Research in 5 Minutes" (post), which builds on Stanford OVAL Lab's STORM (github.com/stanford-oval/storm). See the plugin README for full attribution.
• Model choice matters. Perspective quality scales with reasoning ability — the personas run on Sonnet, the synthesizer and peer-reviewer on Opus. Adjust in the agent frontmatter if needed.
• The workspace is reusable. Re-running on the same slug overwrites prior artifacts. Copy a run elsewhere before re-running if you want to keep it. .storm/ is gitignored by default.
• Partial use. For just the five views, use the multi-perspective-scan skill; for just the contradiction map or just an audit of existing research, use contradiction-map or research-peer-review.

Limitations

This skill researches and reasons over public sources and the model's knowledge; it cannot access paywalled literature, guarantee every citation, or replace domain expertise for high-stakes decisions. The peer-review phase reduces — but does not eliminate — hallucination and bias. Treat the briefing as a rigorous starting point, not a final authority.