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AutoSkill 大数据概论与技术基础 / 课程目标 / 大数据建模分析原理与应用

General SOP for common requests related to 大数据概论与技术基础, 课程目标, 大数据建模分析原理与应用.

install
source · Clone the upstream repo
git clone https://github.com/ECNU-ICALK/AutoSkill
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/ECNU-ICALK/AutoSkill "$T" && mkdir -p ~/.claude/skills && cp -r "$T/SkillBank/Users/chinese_gpt3.5_8_GLM4.7/大数据概论与技术基础-课程目标-大数据建模分析原理与应用" ~/.claude/skills/ecnu-icalk-autoskill-a159c1 && rm -rf "$T"
manifest: SkillBank/Users/chinese_gpt3.5_8_GLM4.7/大数据概论与技术基础-课程目标-大数据建模分析原理与应用/SKILL.md
source content

大数据概论与技术基础 / 课程目标 / 大数据建模分析原理与应用

General SOP for common requests related to 大数据概论与技术基础, 课程目标, 大数据建模分析原理与应用.

Prompt

Follow this SOP (replace specifics with placeholders like <PROJECT>/<ENV>/<VERSION>):

  1. Offline OpenAI-format conversation source.
  2. Title: 243cb9415a5dfeea61e11a52c14e9aa8.json#conv_1
  3. Use the user questions below as the PRIMARY extraction evidence.
  4. Use the full conversation below as SECONDARY context reference.
  5. In the full conversation section, assistant/model replies are reference-only and not skill evidence.
  6. Primary User Questions (main evidence):
  7. 大数据建模分析原理与应用 修订说明 100字，体现与上一轮的修改之处
  8. 大数据开发技术 修订说明 100字，体现与上一轮的修改之处
  9. 大数据概论与云计算基础 修订说明 100字，体现与上一轮的修改之处
  10. 大数据概论与技术基础 课程目标 3个 简短

For each step, include: action, checks, and failure rollback/fallback plan. Output format: for each step number, provide status/result and what to do next.

Triggers

  • Use when the user asks for a process or checklist.
  • Use when you want to reuse a previously mentioned method/SOP.

Examples

Example 1

Input:

Break this into best-practice, executable steps.