「analysis」の検索結果

Generate or improve a company-specific data analysis skill by extracting tribal knowledge from analysts. BOOTSTRAP MODE - Triggers: "Create a data context skill", "Set up data analysis for our warehouse", "Help me create a skill for our database", "Generate a data skill for [company]" → Discovers schemas, asks key questions, generates initial skill with reference files ITERATION MODE - Triggers: "Add context about [domain]", "The skill needs more info about [topic]", "Update the data skill with [metrics/tables/terminology]", "Improve the [domain] reference" → Loads existing skill, asks targeted questions, appends/updates reference files Use when data analysts want Claude to understand their company's specific data warehouse, terminology, metrics definitions, and common query patterns.

日本語の概要は準備中です。原文の説明を表示しています。

Apply statistical methods including descriptive stats, trend analysis, outlier detection, and hypothesis testing. Use when analyzing distributions, testing for significance, detecting anomalies, computing correlations, or interpreting statistical results.

日本語の概要は準備中です。原文の説明を表示しています。

Build business cases with cost-benefit analysis, ROI calculations, risk assessment, implementation timeline, and stakeholder analysis

日本語の概要は準備中です。原文の説明を表示しています。

Real DCF (Discounted Cash Flow) model creation for equity valuation. Retrieves financial data from SEC filings and analyst reports, builds comprehensive cash flow projections with proper WACC calculations, performs sensitivity analysis, and outputs professional Excel models with executive summaries. Use when users need to value a company using DCF methodology, request intrinsic value analysis, or ask for detailed financial modeling with growth projections and terminal value calculations.

日本語の概要は準備中です。原文の説明を表示しています。

Conduct comprehensive market research including competitive analysis, customer persona development, market sizing (TAM/SAM/SOM), survey design, and trend analysis. Synthesize insights for strategic decision-making.

日本語の概要は準備中です。原文の説明を表示しています。

Build institutional-grade comparable company analyses with operating metrics, valuation multiples, and statistical benchmarking in Excel/spreadsheet format. **Perfect for:** - Public company valuation (M&A, investment analysis) - Benchmarking performance vs. industry peers - Pricing IPOs or funding rounds - Identifying valuation outliers (over/under-valued) - Supporting investment committee presentations - Creating sector overview reports **Not ideal for:** - Private companies without comparable public peers - Highly diversified conglomerates - Distressed/bankrupt companies - Pre-revenue startups - Companies with unique business models

日本語の概要は準備中です。原文の説明を表示しています。

Collect, normalize, and structure execution traces from instrumented programs (strace, ltrace) into JSON format for downstream analysis. Use when working with system call traces, library call traces, or execution logs that need to be analyzed for debugging, test case reproduction, or verification. Supports parsing strace/ltrace output, filtering noise, extracting debug information, and preparing traces for bug analysis or reproduction workflows.

日本語の概要は準備中です。原文の説明を表示しています。

Identify bug-introducing commits using semantic analysis that extends traditional SZZ algorithm. Distinguishes semantic changes from refactorings or code movements using control-flow and data-flow similarity analysis. Use when analyzing bug-fix commits to trace back to bug-introducing changes, investigating software evolution, conducting empirical studies on defect prediction, or reducing false positives in bug localization. Supports git repositories and provides explanations for why commits are identified as bug-introducing.

日本語の概要は準備中です。原文の説明を表示しています。

Identifies non-deterministic or unreliable tests through static code analysis and test result analysis. Use when Claude needs to find flaky tests, analyze test reliability, or investigate intermittent test failures. Supports Python (pytest, unittest) and Java (JUnit, TestNG) test frameworks. Trigger when users mention "flaky tests", "intermittent failures", "non-deterministic tests", "unreliable tests", or ask to "find flaky tests", "analyze test stability", or "why tests fail randomly".

日本語の概要は準備中です。原文の説明を表示しています。

横纵分析法（Horizontal-Vertical Analysis）深度研究Skill。由数字生命卡兹克提出，融合了索绪尔的历时-共时分析、社会科学的纵向-横截面研究设计、商学院案例研究法与竞争战略分析的核心思想。 当用户想要系统性研究一个产品、公司、概念、技术或人物时使用。核心是双轴分析：纵轴追踪从诞生到当下的完整生命历程（以叙事故事呈现），横轴在当下时间截面上与竞品/同类进行系统性横向对比，最后交叉两条轴产出独到洞察。最终产出一份排版精美的PDF研究报告。 触发词包括但不限于：横纵分析、研究一下、帮我分析、深度研究、做个研究、调研一下、竞品分析、帮我看看这个东西怎么样、这个产品/公司/概念是怎么回事、帮我摸清楚、帮我搞懂、帮我做个deep research。 即使用户只是说"帮我了解一下XX"或"XX是什么来头"，只要上下文暗示需要系统性的深度研究（而非简单的概念解释），都应该触发。也适用于用户丢来一个产品名、公司名、技术名词说"帮我研究一下这个"的场景。 不要用于简单的名词解释（用户只是问"XX是什么"）、不要用于公众号写作（那个用khazix-writer）、不要用于纯标题摘要生成（用wechat-title）。

日本語の概要は準備中です。原文の説明を表示しています。

Use when working with Aws Batch — aWS Batch compute environment management, job queue analysis, scheduling policy review, and array job monitoring. Covers compute resource utilization, job status tracking, failure investigation, Fargate vs EC2 comparison, and queue priority analysis.

日本語の概要は準備中です。原文の説明を表示しています。

Patterns for data loading, exploration, and statistical analysis

日本語の概要は準備中です。原文の説明を表示しています。

Use when needing strategic project analysis from multiple independent expert perspectives. Triggers on business decisions, growth strategy, product direction, competitive analysis, or any situation where diverse C-level opinions reduce blind spots

日本語の概要は準備中です。原文の説明を表示しています。

Analyze open-source license compatibility, obligations, and compliance risks across project dependencies. Use when the user requests license analysis or provides relevant inputs for this workflow.

日本語の概要は準備中です。原文の説明を表示しています。

Identify at-risk customer accounts by analyzing usage patterns, engagement signals, and support history to generate churn risk scores and intervention recommendations. Use when the user requests churn analysis or provides relevant inputs for this workflow.

日本語の概要は準備中です。原文の説明を表示しています。

Analyze NPS, CSAT, and qualitative customer feedback to extract themes, identify trends, and generate actionable insight reports. Use when the user requests customer feedback analysis or provides relevant inputs for this workflow.

日本語の概要は準備中です。原文の説明を表示しています。

Use Xquik to fetch X (Twitter) data or act through a connected account. It covers search, profiles, followers, replies, threads, timelines, media downloads, bulk exports, trends, monitors, signed webhooks, draws, posts, likes, follows, DMs, and AI analysis of posts (sentiment, brand mentions, news, market signals, viral score, custom labels). Also use for hashtag or @handle tracking when no other network is named, Xquik MCP setup, pricing, and X API comparisons. Skip data from other social networks, code that stays on the official X API (such as tweepy with an X developer bearer token), official X widget implementation, and content drafting or analysis without an API task. Not affiliated with X Corp.

日本語の概要は準備中です。原文の説明を表示しています。

Emit the content signals reimagine-it reads from an HTML file — title, anchors, proper nouns, dates, numbers, emails, links, source hex colors, and the derived palette — as JSON without generating a redesign. Use when the user says /reimagine-it extract, "what does the engine see in this page", "extract the palette", "pull the facts from this page", or wants content analysis for research, migration, or design-system work. CLI: npx reimagine-it extract -i page.html -o signals.json. Part of the reimagine-it Content-Derived Design suite.

日本語の概要は準備中です。原文の説明を表示しています。

Price action market structure analysis, trend vs trading range classification, Always In directional framework, buying/selling pressure analysis, market cycle phase identification, the price action methodology

日本語の概要は準備中です。原文の説明を表示しています。

Recent quarter performance analysis, quarterly earnings review, last quarter results, quarterly financial performance, analyze recent quarter, Q4 earnings, quarterly revenue breakdown, EPS this quarter, margin analysis recent quarter, sequential growth, quarterly performance review

日本語の概要は準備中です。原文の説明を表示しています。

Growth strategy analysis, organic growth decomposition, inorganic growth, M&A strategy, pipeline analysis, revenue growth drivers, strategic initiatives, expansion strategy, growth trajectory, product pipeline growth

日本語の概要は準備中です。原文の説明を表示しています。

What-if scenario analysis, scenario tree construction, base bull bear case, sensitivity to macro variables, revenue scenario modeling, cost scenario analysis, margin impact scenarios, interest rate sensitivity, currency impact scenarios, commodity price scenarios

日本語の概要は準備中です。原文の説明を表示しています。

Competitive positioning, strategic group mapping, differentiation analysis, competitive advantage assessment, market positioning map, value chain positioning, brand positioning, cost leadership vs differentiation, niche strategy analysis, disruptive positioning

日本語の概要は準備中です。原文の説明を表示しています。

Qualitative stock analysis, management operating plan MOP assessment, key performance indicator KPI identification, catalyst identification and classification, earnings call transcript analysis, qualitative evidence gathering for investment thesis

日本語の概要は準備中です。原文の説明を表示しています。