Brutal technical white paper editor that performs merciless review with research-backed validation. Use when reviewing, editing, or improving white papers, technical documents, research papers, or any document requiring rigorous technical scrutiny. Triggers on requests to review white papers, validate citations, check technical accuracy, perform gap analysis, or score document quality.
Automatically convert arXiv papers to well-structured Markdown documentation. Invoke with an arXiv ID to fetch materials (LaTeX source or PDF), convert to Markdown, and generate implementation-ready reference documentation with preserved mathematics and section structure.
Read and analyze academic papers from Zotero library. Use when the user requests to read, access, or analyze a paper by title, author, or topic from their Zotero library. Automatically searches Zotero, converts PDFs to markdown, saves to Notes/PaperInMarkdown, and provides analysis.
Deep analysis of documentation/articles with practical application guidance. Use when user asks to "analyze and apply", "digest and implement", "read and integrate", or provides a document they want analyzed for implementation in the codebase.
Automated LLM-driven hypothesis generation and testing on tabular datasets. Use when you want to systematically explore hypotheses about patterns in empirical data (e.g., deception detection, content analysis). Combines literature insights with data-driven hypothesis testing. For manual hypothesis formulation use hypothesis-generation; for creative ideation use scientific-brainstorming.
Comprehensive toolkit for creating, analyzing, and visualizing complex networks and graphs in Python. Use when working with network/graph data structures, analyzing relationships between entities, computing graph algorithms (shortest paths, centrality, clustering), detecting communities, generating synthetic networks, or visualizing network topologies. Applicable to social networks, biological networks, transportation systems, citation networks, and any domain involving pairwise relationships.
Data structure for annotated matrices in single-cell analysis. Use when working with .h5ad files or integrating with the scverse ecosystem. This is the data format skill—for analysis workflows use scanpy; for probabilistic models use scvi-tools; for population-scale queries use cellxgene-census.
Synthesizes research findings into design decisions via codebase investigation. Use when (1) translating research into implementation approaches, (2) selecting between design alternatives, (3) executing after /research or deep-research, or (4) preparing input for /plan phase.
Generate structured research reports with findings, comparisons, recommendations, and citations. Use when documenting investigation results or creating technical comparisons. This skill provides comprehensive research report templates: - Investigation findings with proper structure - Technology comparison tables - Best practices summaries - Citation and reference management - Executive summaries Triggers: "create report", "summarize findings", "compare technologies", "research report", "調査レポート", "技術比較", "ベストプラクティス"
Extracts structured data from cybersecurity fatigue research papers and calculates statistical correlations
Query Reactome REST API for pathway analysis, enrichment, gene-pathway mapping, disease pathways, molecular interactions, expression analysis, for systems biology studies.
Fetch and aggregate data from 17 external APIs including Census, arXiv, NASA, Wikipedia, PubMed, and GitHub.
Expert guide for creating Airalogy Protocols (AIMD), Assigners (Python logic), and Validation Models. Use this to design digital workflows and experiments.
Summarize robotics-related text, research papers, or lecture notes into concise, clear, and structured summaries. Use when user asks to condense or simplify robotics content.
Reference skill for Splatoon ability families, AP rungs, token constraints, and domain rules for mechinterp experiments
Generates a comprehensive learning graph from a course description, including 200 concepts with dependencies, taxonomy categorization, and quality validation reports. Use this when the user wants to create a structured knowledge graph for educational content.
Run GPT-Researcher multi-agent deep research framework locally using OpenAI GPT-5.2. Replaces ChatGPT Deep Research with local control. Researches 100+ sources in parallel, provides comprehensive citations. Use for Phase 3 industry/technical research or comprehensive synthesis. Takes 6-20 min depending on report type. Supports multiple LLM providers.
Optimize websites for AI assistant recommendations. ChatGPT, Gemini, Perplexity, Claude. Get cited in AI answers.
Provide L1-L5 pedagogy layer reference for the AI-Native Robotics Textbook. Use when assigning layers to content, understanding layer requirements, or validating layer progression.
Performs accurate research and fact-checking using reliable sources. Ideal for validating claims, clarifying complex topics, summarizing findings, and ensuring information accuracy.
