136건(w95의 저장소) · 인기순
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.
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Design customer onboarding playbooks with milestone tracking, training plans, health checks, and success criteria
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Guidance for composing well-formatted, effective Slack messages using mrkdwn syntax
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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.
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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.
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Write and maintain knowledge base articles from resolved support issues. Use when a ticket has been resolved and the solution should be documented, when updating existing KB articles, or when creating how-to guides, troubleshooting docs, or FAQ entries.
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Structure and package support escalations for engineering, product, or leadership with full context, reproduction steps, and business impact. Use when an issue needs to go beyond support, when writing an escalation brief, or when assessing whether an issue warrants escalation.
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Research customer questions by searching across documentation, knowledge bases, and connected sources, then synthesize a confidence-scored answer. Use when a customer asks a question you need to investigate, when building background on a customer situation, or when you need account context.
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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.
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Build product roadmaps with quarterly planning, feature prioritization, dependency mapping, and stakeholder alignment. Create actionable roadmaps that communicate strategy and guide execution.
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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.
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Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like "the xlsx in my downloads") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.
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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.
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Analyze customer churn patterns, identify at-risk accounts, create retention playbooks, and build early warning systems
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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.
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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.
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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.
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Guidance for effectively searching Slack to find messages, files, channels, and people
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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.
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Analyzes CSV files, generates summary stats, and plots quick visualizations using Python and pandas.
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Build supplier performance scorecards with KPIs, quality metrics, delivery performance, cost management, and improvement plans
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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.
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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.
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Create Quarterly Business Reviews with account health scores, usage analytics, ROI analysis, expansion opportunities, and risk mitigation
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