數據科學

TODO: [What it does]. Use when [specific triggers]. Example: "Analyzes Excel spreadsheets and generates charts. Use when working with Excel files, .xlsx, spreadsheet analysis, or data visualization." REQUIRED: Include "Use when..." with trigger keywords (file types, domains, tasks). Third person. Max 1024 chars.

Business model design using Osterwalder's Business Model Canvas and Lean Canvas. Creates 9-block canvases with structured analysis for business model innovation and startup validation.

Comprehensive scientific document review and analysis. Use when Claude needs to review scientific papers, reports, preprints, or other research documents for: (1) Identifying and evaluating claims and supporting evidence, (2) Assessing logical argumentation and experimental design, (3) Reviewing citation adequacy and suggesting additional references, (4) Determining document type and research contribution, (5) Checking technical accuracy and methodology, (6) Providing constructive feedback on presentation and clarity. Also handles language, grammar, and formatting review separately.

Use when asked to review MERN stack code - comprehensive code reviewer that checks project health, security, maintainability, performance, testing, and architecture. Combines general code quality analysis with MERN-specific expertise.

Use when the user asks to enhance documentation, add code comments, create API docs, improve technical documentation, or document code. Triggers on keywords like "document", "documentation", "API docs", "comments", "JSDoc", "XML comments", "explain code".

Use when the user asks to run Codex CLI (codex exec, codex resume) or references OpenAI Codex for code analysis, refactoring, or automated editing

Assists with security incident response, investigation, and remediation. This skill is triggered when the user requests help with incident response, mentions specific incident types (e.g., data breach, ransomware, DDoS), or uses terms like "incident response plan", "containment", "eradication", or "post-incident activity". It guides the user through the incident response lifecycle, from preparation to post-incident analysis. It is useful for classifying incidents, creating response playbooks, collecting evidence, constructing timelines, and generating remediation steps. Use this skill when needing to respond to a "security incident".

Generate pivot tables and charts from raw data using natural language - analyze sales by region, summarize data by category, and create visualizations effortlessly Activates when you request "excel pivot wizard" functionality.

This skill performs transcription factor (TF) footprint analysis using TOBIAS on ATAC-seq data. It corrects Tn5 sequence bias, quantifies TF occupancy at motif sites, generates footprint scores, and optionally compares differential TF binding across conditions.

Use when the user asks to run Codex CLI (codex exec, codex resume) or references OpenAI Codex for code analysis, refactoring, or automated editing

This skill generates conventional commit messages using AI analysis of staged Git changes. It automatically determines the commit type (feat, fix, docs, etc.), identifies breaking changes, and formats the message according to conventional commit standards. Use this when asked to create a commit message, write a Git commit, or when the user uses the `/commit-smart` or `/gc` command. It is especially useful after changes have been staged with `git add`.

This skill enables Claude to profile application performance, analyzing CPU usage, memory consumption, and execution time. It is triggered when the user requests performance analysis, bottleneck identification, or optimization recommendations. The skill uses the application-profiler plugin to identify performance bottlenecks and suggest code-level optimizations. Use it when asked to "profile application", "analyze performance", or "find bottlenecks". It is also helpful when the user mentions specific performance metrics like "CPU usage", "memory leaks", or "execution time".

This skill enables Claude to detect potential memory leaks and analyze memory usage patterns in code. It is triggered when the user requests "detect memory leaks", "analyze memory usage", or similar phrases related to memory leak detection and performance analysis. The skill identifies potential issues such as unremoved event listeners, closures preventing garbage collection, uncancelled timers, unbounded cache growth, circular references, detached DOM nodes, and unnecessary global state accumulation. It then provides detailed fix recommendations. Use this skill to proactively identify and resolve memory leaks, improving application performance and stability.

This skill enables Claude to generate data visualizations, plots, charts, and graphs from provided data. It analyzes the data, selects the most appropriate visualization type, and creates a visually appealing and informative graphic. Use this skill when the user requests a visualization, plot, chart, or graph; when data needs to be presented visually; or when exploring data patterns. The skill is triggered by requests for "visualization", "plot", "chart", or "graph".

Analyzes recent conversation history using chat tools to identify recurring workflow patterns and generate Custom Skills recommendations with statistical rigor. Use when users request workflow analysis, pattern identification, skill generation suggestions, or automation opportunities based on their AI usage patterns without requiring conversation exports.

複雑な問題を分解し、推論の流れを整理して短い根拠サマリーを作成するスキル。前提整理、論点分解、選択肢比較、判断理由の要約を通じて、説明責任のあるアウトプットを作る。Anchors:• The Pragmatic Programmer / 適用: 問題分解 / 目的: 実践的な整理• Thinking, Fast and Slow / 適用: 判断バイアス確認 / 目的: 判断根拠の明確化• Critical Thinking / 適用: 論点整理 / 目的: 根拠の一貫性Trigger:Use when structuring reasoning, summarizing decision rationale, clarifying assumptions, or documenting a step-by-step analysis.

Research ethics, IRB compliance, and data privacy analysis.

Conduct user research and validation. Use when discovering user needs, validating assumptions, creating personas, or understanding pain points. Covers interviews, surveys, analysis, and synthesis.

This skill is used to perform genomic feature annotation and visualization for any file containing genomic region information using Homer (Hypergeometric Optimization of Motif EnRichment). It annotates regions such as promoters, exons, introns, intergenic regions, and TSS proximity, and generates visual summaries of feature distributions.

Create leveraged buyout (LBO) models in Excel with sources & uses, debt schedules, cash flow waterfalls, and IRR calculations for private equity analysis