Computational text analysis for sociology research using R or Python. Guides you through topic models, sentiment analysis, classification, and embeddings with systematic validation. Supports both traditional (LDA, STM) and neural (BERT, BERTopic) methods.
Documentation of available data science libraries (scipy, numpy, pandas, sklearn) and best practices for statistical analysis, regression modeling, and organizing analysis scripts. **CRITICAL:** All analysis scripts MUST be placed in reports/{topic}/scripts/, NOT in root scripts/ directory.
Multi-phase research orchestration for thorough codebase, documentation, and external knowledge investigation. Invoked by /ai-eng/research command. Use when conducting deep analysis, exploring codebases, investigating patterns, or synthesizing findings from multiple sources.
Code Query with AI-enhanced deterministic analysis via SplitMix ternary classification
Comprehensive research, analysis, and content extraction system. Multi-source parallel research using available researcher agents. Deep content analysis with extended thinking. Intelligent retrieval for difficult sites. Fabric pattern selection for 242+ specialized prompts. USE WHEN user says 'do research', 'extract wisdom', 'analyze content', 'find information about', or requests web/content research.
Efficiently research topics using parallel agents via Contextune's /ctx:research command. Use when users ask to research, investigate, find information about topics, compare options, or evaluate libraries/tools. Activate for questions like "research best X", "what's the best library for Y", or "investigate Z".
Transforms an academic paper into deep, multi-layered understanding. Use when asked to explain a paper, break down a research paper, understand an arXiv paper, or build intuition for a technical concept from a paper. Generates explanations at multiple levels plus visual intuition diagrams.
Guides you through implementing a research paper step-by-step from scratch. Use when asked to implement a paper, code up a paper, reproduce research results, or build a model from a paper. Focuses on building understanding through implementation with checkpoint questions.
Conduct comprehensive, multi-source research on any topic using web search, documentation lookup, and critical analysis. This skill should be used when users request thorough investigation, deep research, or comprehensive analysis of topics including but not limited to AI systems, technology trends, academic subjects, business strategies, or current events. | 任意のトピックに対して、Web検索、ドキュメント参照、批判的分析を用いた包括的な調査を実施。徹底的な調査、詳細なリサーチ、包括的な分析が必要な場合や、AIシステム、技術トレンド、学術的テーマ、ビジネス戦略、時事問題などについて深く知りたい場合に使用。
Quality criteria, workflows, and multi-agent analysis patterns for curating high-quality golden dataset entries
Power spectrum analysis for frequency domain insights and periodicity detection
Signal correlation analysis for similarity and delay detection
Assignment of vectors to points in phase space defining dynamics
Power spectral density estimation for frequency content analysis
Vector distance calculations for similarity analysis
Time crystal-inspired schedule stability analysis. Use when analyzing schedule churn, detecting natural periodicities, or optimizing for minimal disruption.
