Data analytics
AI 编程助手的专业技能库，涵盖 30+ 技能，按 6 类组织
npx -y skills add morning-start/agent-skills --skill data-analyticsAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
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Use when the user needs a data analysis skill entry point, a recommended analytics sub-skill, or a guided overview of the analysis workflow.
SKILL.md
2.2 KB, 644 tokens by cl100k_base, as published. Nobody here has run it
Data Analytics Skills
任务目标
- 作为数据分析技能库的入口，帮助用户快速选到正确的子技能
- 提供统一的分析流程视图，避免把流程、处理、可视化和报告混在一起
- 触发条件：用户提到数据分析、数据处理、可视化、分析报告，或需要推荐该用哪个子技能
技能地图
核心流程
- analytics-core - 分析流程：目标设定、七阶段流程、价值实现
数据处理
- analytics-data-processing - 数据处理：获取、清洗、转换、建模准备
结果呈现
- analytics-visualization - 可视化：多维度展示、图表选型、交互设计
- analytics-report - 报告：结构化输出、受众分层、模板化交付
使用方式
1. 先判断用户需求
| 用户说法 | 优先子技能 |
|---|---|
| 想知道分析该怎么做 | analytics-core |
| 需要拉数据、清洗或建模前处理 | analytics-data-processing |
| 需要图表、仪表盘、交互展示 | analytics-visualization |
| 需要报告、周报、专题分析稿 | analytics-report |
2. 再进入对应技能
- 单一任务：直接使用对应子技能
- 组合任务：先用
analytics-core定义目标，再接analytics-data-processing、analytics-visualization或analytics-report - 不明确时：先从
analytics-core开始，它负责把分析问题拆清楚
分析流程总览
- 明确问题和目标
- 获取并理解数据
- 清洗与转换数据
- 建模或分析
- 可视化呈现结果
- 提炼业务结论
- 形成报告或行动建议
注意事项
- 这个技能库是入口，不负责替代具体子技能的详细方法
- 分析任务优先明确目标，再选择工具和表现形式
- 报告和可视化的质量，取决于前面的数据处理是否可靠
Gives 0 of the 12 instructions most analytics metrics skills give in 644 tokens
Counted across 368 of the 369 authors here whose files we hold, read 2026-08-06
- read product marketing context before asking questionsin 18 of 368, across 12 files
- use lowercase with underscores for event namesin 16 of 368, across 6 files
- track events for decisions not vanity metricsin 15 of 368, across 5 files
- use object-action format for event namesin 15 of 368, across 8 files
- produce a tracking plan documentin 14 of 368, across 4 files
- Call RUBE_SEARCH_TOOLS first to get current schemasin 13 of 368, across 2 files
- establish consistent event naming conventions before implementingin 10 of 368, across 4 files
- Verify dimension and metric compatibility before reportingin 9 of 368, across 2 files
- Encrypt data at rest and in transitin 9 of 368, across 3 files
- use snake_case for event namesin 9 of 368, across 5 files
- monitor technical health during the testin 9 of 368, across 5 files
- use consistent property namesin 8 of 368, across 4 files
Said here and by no other author read
- determine user need first
- select corresponding sub-skill
- use core skill to define goals for combined tasks
- start with core skill when intent is unclear
- clarify problem and objectives
- acquire and understand data
Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.