deep-research
Universal deep research agent team. 13-agent pipeline for rigorous academic research on any topic. 7 modes: full research, quick brief, paper review, lit-review, fact-check, Socratic guided research dialogue, and systematic review with optional meta-analysis. Covers research question formulation, Socratic mentoring, methodology design, systematic literature search, source verification, cross-source synthesis, risk of bias assessment, meta-analysis, APA 7.0 report compilation, editorial review, devil's advocate challenges, ethics review, and post-research literature monitoring. Triggers on: res
Profile →npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill deep-research --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
What it does
Translates a research task into a multi-agent, multi-phase workflow to produce APA 7.0-compliant reports, including scoping, literature search, verification, synthesis, and editorial review.
How it works
- Executes an orchestration workflow across six phases: Scoping, Investigation, Analysis, Composition, Review, Revision.
- Agents perform specific roles: transform vague topics into precise research questions, design methodology, conduct systematic literature search with inclusion/exclusion criteria, verify sources and assess risk of bias, synthesize findings, and draft the full APA 7.0 report.
- Includes checkpoints by a devil's advocate and an ethics review; revisions are capped (max 2 loops) and final delivery follows editorial and ethics clearance.
- Produces an APA 7.0 report with structure: Title Page, Abstract, Introduction, Literature/Theoretical Framework, Methodology, Findings, Discussion, Conclusion, References, Appendices.
- Optional post-research monitoring is supported for ongoing alerts and updates.
When to use it
Use when you need a full, systematic, and ethically-sound academic research pipeline that ends in an APA-formatted report. Initiates in Scoping phase and proceeds through Investigation, Analysis, and Composition, with parallel review activities and potential revision loops. Trigger keywords include: research, deep research, literature review, systematic review, meta-analysis, PRISMA, evidence synthesis, fact-check, methodology, APA report, academic analysis, policy analysis, guide my research, monitor this topic.
What it can touch
Tools declared: claude-code. Interfaces include supporting agents for literature search, verification, synthesis, and report compilation within an APA 7.0 framework.
Caveats
Version 2.4; license NOASSERTION. Writing quality improvements apply to the report compiler, including optional Style Profile consumption and a writing quality checklist. The workflow emphasizes adherence to ethical attribution, bias checks, and vulnerability screening, with explicit checkpoints and a limit on revision loops.
# Deep Research — Universal Academic Research Agent Team Universal deep research tool — a domain-agnostic 13-agent team for rigorous academic research on any topic. **v2.4** adds writing quality improvements to the report compiler: - **Style Profile consumption** (optional) — If a Style Profile is available from academic-paper intake, the report compiler applies it as a soft guide for the Executiv
What does the deep-research skill do?
Universal deep research agent team. 13-agent pipeline for rigorous academic research on any topic. 7 modes: full research, quick brief, paper review, lit-review, fact-check, Socratic guided research dialogue, and systematic review with optional meta-analysis. Covers research question formulation, Socratic mentoring, methodology design, systematic literature search, source verification, cross-source synthesis, risk of bias assessment, meta-analysis, APA 7.0 report compilation, editorial review, devil's advocate challenges, ethics review, and post-research literature monitoring. Triggers on: res
How do I install it?
Run `npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill deep-research --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From brycewang-stanford/Auto-Empirical-Research-Skills, a repository with 3,244 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.