Claude Skills by majiayu000

Local speech-to-text with the Whisper CLI (no API key).

Local speech-to-text with the Whisper CLI (no API key).

Local speech-to-text with the Whisper CLI (no API key).

Local speech-to-text with the Whisper CLI (no API key).

Local speech-to-text with the Whisper CLI (no API key).

Local speech-to-text with the Whisper CLI (no API key).

Local speech-to-text with the Whisper CLI (no API key).

Local speech-to-text with the Whisper CLI (no API key).

Local speech-to-text with the Whisper CLI (no API key).

Local speech-to-text with the Whisper CLI (no API key).

GPU-accelerate Python code using CuPy, Numba CUDA, Warp, cuDF, cuML, cuGraph, KvikIO, cuCIM, cuxfilter, cuVS, cuSpatial, and RAFT. Use whenever the user mentions GPU/CUDA/NVIDIA acceleration, or wants to speed up NumPy, pandas, scikit-learn, scikit-image, NetworkX, GeoPandas, or Faiss workloads. Covers physics simulation, differentiable rendering, mesh ray casting, particle systems (DEM/SPH/fluids), vector/similarity search, GPUDirect Storage file IO, interactive dashboards, geospatial analys...

Full-featured computational pathology toolkit. Use for advanced WSI analysis including multiplexed immunofluorescence (CODEX, Vectra), nucleus segmentation, tissue graph construction, and ML model training on pathology data. Supports 160+ slide formats. For simple tile extraction from H&E slides, histolab may be simpler.

Performs pseudo-bulk differential gene expression analysis using DESeq2 or edgeR. Aggregates single-cell counts to sample-level pseudo-bulk data, then identifies differentially expressed genes between conditions while accounting for biological replicates. Supports complex experimental designs including batch effects, paired samples, and interaction terms.

Differential gene expression analysis (Python DESeq2). Identify DE genes from bulk RNA-seq counts, Wald tests, FDR correction, volcano/MA plots, for RNA-seq analysis.

Bayesian statistical modeling with PyMC v5+. Use when building probabilistic models, specifying priors, running MCMC inference, diagnosing convergence, or comparing models. Covers PyMC, ArviZ, pymc-bart, pymc-extras, nutpie, and JAX/NumPyro backends. Triggers on tasks involving: Bayesian inference, posterior sampling, hierarchical/multilevel models, GLMs, time series, Gaussian processes, BART, mixture models, prior/posterior predictive checks, MCMC diagnostics, LOO-CV, WAIC, model comparison,...

Multi-objective optimization framework. NSGA-II, NSGA-III, MOEA/D, Pareto fronts, constraint handling, benchmarks (ZDT, DTLZ), for engineering design and optimization problems.

Multi-objective optimization framework. NSGA-II, NSGA-III, MOEA/D, Pareto fronts, constraint handling, benchmarks (ZDT, DTLZ), for engineering design and optimization problems.

Data discovery and analysis specialist focused on extracting actionable insights from complex datasets, identifying patterns and anomalies, and transforming raw data into strategic intelligence. Excels at multi-source data integration, advanced analytics, and data-driven decision support.

Expert-level data science, analytics, visualization, and statistical modeling

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.

Data science and analytics expertise for statistical analysis, machine learning pipelines, data governance, business intelligence, predictive modeling, and analytics strategy. Use when building ML models, analyzing data, creating dashboards, or designing data architectures.

Data Story Outliner - Auto-activating skill for Data Analytics. Triggers on: data story outliner, data story outliner Part of the Data Analytics skill category.

Transform data into compelling narratives using visualization, context, and persuasive structure. Use when presenting analytics to stakeholders, creating data reports, or building executive presentations.

NGS analysis toolkit. BAM to bigWig conversion, QC (correlation, PCA, fingerprints), heatmaps/profiles (TSS, peaks), for ChIP-seq, RNA-seq, ATAC-seq visualization.

Multiagent AI system for scientific research assistance that automates research workflows from data analysis to publication. This skill should be used when generating research ideas from datasets, developing research methodologies, executing computational experiments, performing literature searches, or generating publication-ready papers in LaTeX format. Supports end-to-end research pipelines with customizable agent orchestration.

生成GOAL/SubPlan依赖DAG和关键路径分析，并执行SubPlan划分。当需要分析技术依赖、业务依赖、识别关键路径、发现并行执行机会、执行SubPlan分配时使用。基于GOAL的dependencies字段和业务逻辑分析生成Mermaid依赖图和SubPlan划分方案。

Visualize and analyze issue dependencies in Linear. Finds blocking chains, circular dependencies, and critical path items.

Long-running design anthropologist that builds comprehensive visual databases from 500-1000 real-world examples, extracting color palettes, typography patterns, layout systems, and interaction design across any domain (portfolios, e-commerce, SaaS, adult content, technical showcases). This skill should be used when users need exhaustive design research, pattern recognition across large example sets, or systematic visual analysis for competitive positioning.

Selects the appropriate quasi-experimental method (DiD, ITS, SC) based on data structure and research questions. Use when the user is unsure which method to apply.

Refines an active research session by drilling deeper into a subtopic. Use after tome:research to narrow results to a specific channel or angle.

Эксперт анализа распределений. Используй для statistical distributions, data analysis и hypothesis testing.

Differentially methylated region (DMR) detection using methylKit tiles, bsseq BSmooth, and DMRcate. Use when identifying contiguous genomic regions with methylation differences between experimental conditions or cell types.

Searching internet for technical documentation using llms.txt standard, GitHub repositories via Repomix, and parallel exploration. Use when user needs: (1) Latest documentation for libraries/frameworks, (2) Documentation in llms.txt format, (3) GitHub repository analysis, (4) Documentation without direct llms.txt support, (5) Multiple documentation sources in parallel

Fetch up-to-date documentation for any library, framework, API, or service into context. Use when the user wants to look up API references, check function signatures or required fields, find feature-specific docs, or verify how an external tool actually works. Triggers for queries about third-party libraries like Stripe, SQLAlchemy, Tailwind, FastAPI, shadcn, Drizzle, Hono, Better Auth — any time the answer lives in official docs rather than in the project codebase. Use this instead of guessi...

Search technical documentation using executable scripts to detect query type, fetch from llms.txt sources (context7.com), and analyze results. Use when user needs: (1) Topic-specific documentation (features/components/concepts), (2) Library/framework documentation, (3) GitHub repository analysis, (4) Documentation discovery with automated agent distribution strategy

Search technical documentation using executable scripts to detect query type, fetch from llms.txt sources (context7.com), and analyze results. Use when user needs: (1) Topic-specific documentation (features/components/concepts), (2) Library/framework documentation, (3) GitHub repository analysis, (4) Documentation discovery with automated agent distribution strategy

Detect and alert on emerging anomalies and risk flags from pilot metrics and data streams. Use when monitoring live data, threshold breaches, or statistical outliers to trigger governance reviews and corrective actions.

Analyzes why stocks moved after 8-K earnings filings. Use ultrathink for all analyses. Invoke when asked to analyze stock movements, earnings reactions, or determine the primary driver of price changes.

Analyzes why stocks moved after 8-K earnings filings. Use ultrathink for all analyses. Invoke when asked to analyze stock movements, earnings reactions, or determine the primary driver of price changes.

When the user wants to calculate optimal order quantities, minimize total inventory costs using EOQ models, or determine the economic lot size. Also use when the user mentions "EOQ," "Wilson formula," "economic lot size," "order quantity optimization," "production batch size," "quantity discounts," "EPQ" (Economic Production Quantity), "backorder models," or "reorder point calculations." For multi-echelon systems, see multi-echelon-inventory. For stochastic models, see stochastic-inventory-mo...

Reading a habitat — identifying biome, plant community, food web structure, successional stage, and the keystone species that hold the system together. Covers the elevational and latitudinal gradients that Humboldt first mapped, the structural vocabulary for describing a habitat, the core concepts of food-web and trophic analysis, and the practice of diagnosing habitat health from indicator species. Use when the task is to understand a place rather than a species.

当社EHR-RWDの強み（経過記録テキスト、臨床サマリー、検査値）を最大限活用する 研究デザインを設計する。クレームDB（JMDC/MDV）では不可能な研究要素を具体化。

Use when searching for concepts, ideas, or similar content without exact keywords; when user asks "find similar to...", needs semantic discovery, research across perspectives, or explicitly mentions exa

Analyze imports and identify all module dependencies. Use when mapping project structure.

Convert websites into LLM-ready data with Firecrawl API. Features: scrape, crawl, map, search, extract, agent (autonomous), batch operations, and change tracking. Handles JavaScript, anti-bot bypass, PDF/DOCX parsing, and branding extraction. Prevents 10 documented errors. Use when: scraping websites, crawling sites, web search + scrape, autonomous data gathering, monitoring content changes, extracting brand/design systems, or troubleshooting content not loading, JavaScript rendering, bot de...

Extract transcripts from YouTube videos and generate comprehensive, detailed summaries using intelligent analysis frameworks

Access ZINC (230M+ purchasable compounds). Search by ZINC ID/SMILES, similarity searches, 3D-ready structures for docking, analog discovery, for virtual screening and drug discovery.

Access ZINC (230M+ purchasable compounds). Search by ZINC ID/SMILES, similarity searches, 3D-ready structures for docking, analog discovery, for virtual screening and drug discovery.

Expert on Plaid accounts and account management. Covers account data retrieval, balance checking, account types, multi-account handling, and account webhooks. Invoke when user mentions Plaid accounts, account balance, account types, or account management.

Expert on Plaid accounts and account management. Covers account data retrieval, balance checking, account types, multi-account handling, and account webhooks. Invoke when user mentions Plaid accounts, account balance, account types, or account management.