academic-research_skill

Overview

This skill conducts deep academic research across philosophy, neuroscience, cognitive science, and theoretical computer science. It locates, evaluates, and synthesizes scholarly literature to produce concise, citation-ready reports and reading lists. Use it to transform broad questions into targeted literature reviews, annotated bibliographies, or research gap analyses.

How this skill works

I begin by scoping the query: domain, depth (quick/standard/deep), and focus (empirical, theoretical, historical, or debate). I search in waves across focused repositories (arXiv, Semantic Scholar, PhilPapers, PubMed/NCBI) and follow citations to high-impact work. Each source is evaluated for relevance, authority, recency, and type, then triangulated to identify consensus, debates, and gaps. Output is a structured research report with summary, key findings, theoretical landscape, open questions, and recommended reading in APA-style citations.

When to use it

• You need a literature review or annotated bibliography on a topic in the covered domains.
• You want a list of seminal and recent papers with short annotations and direct links/DOIs.
• You need synthesis of empirical findings or competing theoretical positions.
• You want to map research gaps and propose next-step questions or experiments.
• You need to verify claims with peer-reviewed sources and distinguish preprints.

Best practices

• Specify domain and desired depth (quick/standard/deep) so results match your needs.
• Give a clear focus (empirical findings vs. theory vs. history) to prioritize sources appropriately.
• Ask one clarifying question if scope or terminology is ambiguous before the search.
• Prefer primary sources; flag preprints and note peer-review status in outputs.
• Request follow-up actions: expanded source lists, full-text retrieval, or write-ups for different audiences.

Example use cases

• Literature review on predictive processing in cognitive neuroscience with 15–20 prioritized papers.
• Survey of computability results related to probabilistic Turing machines and recent complexity bounds.
• Annotated reading list for philosophy of mind covering materialism, dualism, and functionalism.
• Synthesis of empirical evidence on neural correlates of consciousness with consensus map and open questions.
• Rapid briefing on state of AI alignment theory with key authors, debates, and research gaps.