スキルを探す

Analyzes CSV files, generates summary stats, and plots quick visualizations using Python and pandas.

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。

Write correct, performant SQL across all major data warehouse dialects (Snowflake, BigQuery, Databricks, PostgreSQL, etc.). Use when writing queries, optimizing slow SQL, translating between dialects, or building complex analytical queries with CTEs, window functions, or aggregations.

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 product roadmaps with quarterly planning, feature prioritization, dependency mapping, and stakeholder alignment. Create actionable roadmaps that communicate strategy and guide execution.

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。

Synthesize user research findings from interviews, surveys, and analytics. Create insight reports, customer journey maps, and actionable recommendations based on research data and qualitative findings.

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。

QA an analysis before sharing with stakeholders — methodology checks, accuracy verification, and bias detection. Use when reviewing an analysis for errors, checking for survivorship bias, validating aggregation logic, or preparing documentation for reproducibility.

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。

Execute read-only SQL queries against multiple PostgreSQL databases. Use when: (1) querying PostgreSQL databases, (2) exploring database schemas/tables, (3) running SELECT queries for data analysis, (4) checking database contents. Supports multiple database connections with descriptions for intelligent auto-selection. Blocks all write operations (INSERT, UPDATE, DELETE, DROP, etc.) for safety.

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。

Comprehensive product launch planning including GTM strategy, launch checklists, stakeholder communication, beta testing plans, and post-launch analysis. Execute successful product launches with coordinated teams.

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。

Manages connected MCP sources for enterprise search. Detects available sources, guides users to connect new ones, handles source priority ordering, and manages rate limiting awareness.

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。

Plan sprints with story point estimation, capacity planning, sprint goals, and retrospective frameworks. Organize teams for effective iteration with clear goals, realistic commitments, and continuous improvement.

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。

Write comprehensive Product Requirements Documents with user stories, acceptance criteria, technical specifications, wireframe descriptions, and prioritization frameworks (RICE, MoSCoW). Create clear specifications for product teams.

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。

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。

Create effective data visualizations with Python (matplotlib, seaborn, plotly). Use when building charts, choosing the right chart type for a dataset, creating publication-quality figures, or applying design principles like accessibility and color theory.

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 self-contained interactive HTML dashboards with Chart.js, dropdown filters, and professional styling. Use when creating dashboards, building interactive reports, or generating shareable HTML files with charts and filters that work without a server.

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。

Write detailed feature specifications with functional requirements, edge cases, data models, API contracts, and UX flows. Create comprehensive technical specifications that enable clear implementation.

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。

Profile and explore datasets to understand their shape, quality, and patterns before analysis. Use when encountering a new dataset, assessing data quality, discovering column distributions, identifying nulls and outliers, or deciding which dimensions to analyze.

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。

Create Quarterly Business Reviews with account health scores, usage analytics, ROI analysis, expansion opportunities, and risk mitigation

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 supplier performance scorecards with KPIs, quality metrics, delivery performance, cost management, and improvement plans

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。

Query decomposition and multi-source search orchestration. Breaks natural language questions into targeted searches per source, translates queries into source-specific syntax, ranks results by relevance, and handles ambiguity and fallback strategies.

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。

Design customer onboarding playbooks with milestone tracking, training plans, health checks, and success criteria

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。

Guidance for composing well-formatted, effective Slack messages using mrkdwn syntax

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。

Prepare for contract negotiations with term analysis, BATNA preparation, negotiation playbooks, and comparison frameworks

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。

Forecast inventory needs using demand analysis, safety stock calculations, reorder point optimization, and seasonal adjustment

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 customer churn patterns, identify at-risk accounts, create retention playbooks, and build early warning systems

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。