From data-and-research
Use when planning or executing a full data analysis workflow, including schema inspection, data quality audit, data cleaning, EDA, relationship analysis, feature engineering, modeling, evaluation, and report generation. Trigger on requests like 資料分析流程, EDA 到建模, 數據分析規劃, 分析報告產出, or end-to-end analytics workflow.
How this skill is triggered — by the user, by Claude, or both
Slash command
/data-and-research:data-analysis-workflowThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
把資料分析任務拆成可重複執行的 12 個步驟,從初始化到最終報告,確保分析完整、可追蹤、可交付。
把資料分析任務拆成可重複執行的 12 個步驟,從初始化到最終報告,確保分析完整、可追蹤、可交付。
Use when:
Do not use when:
Note: 詳細規則、判斷條件、範例與輸出格式請讀 references/data-analysis-flow.md。
schema_reporteda_reportmodel_performanceanalysis_report建議同時保留中間產物:
clean_datasetrelationship_reportinsight_summaryvisualization_setreferences/data-analysis-flow.md。Guides collaborative design exploration before implementation: explores context, asks clarifying questions, proposes approaches, and writes a design doc for user approval.
Creates structured, bite-sized implementation plans from specs or requirements before writing code. Useful for breaking down multi-step tasks into testable steps with file structure and task boundaries.
Synthesizes the current conversation into a structured spec (PRD) and publishes it to the project issue tracker with a ready-for-agent label, without interviewing the user.
npx claudepluginhub timlai666/skills --plugin data-and-research