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dev-sciomc

@evolution-foundation · 收录于 5 天前 · 上游提交 2 个月前

Scientific method scaffolding — hypothesis → experiment → evidence → conclusion. Use when you need rigorous causal reasoning rather than vibes-based debugging.

适合你,如果需要在调试或研究中应用科学方法而非直觉判断。

/ 通过 npx 安装 校验哈希
npx oh-my-skill add evolution-foundation/evo-nexus/dev-sciomc
/ 通过 bash 安装
curl -fsSL https://oh-my-skill.com/install.sh | bash -s -- evolution-foundation/evo-nexus/dev-sciomc
/ 已经装过?验证本机副本,不用重装
npx oh-my-skill verify evolution-foundation/evo-nexus/dev-sciomc
安装目标可用 --agent / --scope 或 --to 明确指定;省略时只会在唯一已存在的 agent 目录上自动选择,零命中或多命中会停止并提示。content_hash 缺失或不一致均拒装。
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怎么用

商店整理自技能原文 · 版本 7f5dd76 · 表述以原文为准
它做什么

装上后,Claude 会按照科学方法框架进行工程调查:先明确一个可证伪的假设,然后设计实验(包括变量、对照组和样本量),收集原始数据,进行统计分析,最后给出暂定结论和局限性。

什么时候触发

当你需要严谨的因果推理(而非凭感觉调试)时触发,例如性能优化、A/B 比较或高成本错误场景。

装好后可以这样说
Claude 会生成假设、实验步骤和对照方案。
触发完整的科学调查流程。
技能原文 SKILL.md作者撰写 · Apache-2.0 · 7f5dd76

Dev Sciomc (Scientific Method)

Derived from oh-my-claudecode (MIT, Yeachan Heo). Adapted for the EvoNexus Engineering Layer.

Scientific method discipline applied to engineering investigations. Forces explicit hypothesis statement, experimental design, evidence collection, and provisional conclusions.

Use When
  • Investigation requires rigor beyond "let me try X"
  • Performance optimization (you need controls and measurements, not guesses)
  • A/B comparison of two implementations
  • Anything where the cost of being wrong is high
Do Not Use When
  • Trivial bug → use @hawk-debugger
  • Pure exploration → use @scout-explorer
Workflow
Phase 1 — Hypothesis
  • State the hypothesis as a falsifiable claim
  • "X is faster than Y" not "X feels faster"
  • Identify the dependent variable, independent variables, controls
Phase 2 — Experiment Design
  • What measurement will prove/disprove the hypothesis?
  • What's the minimum sample size for statistical significance?
  • What confounders need to be controlled?
Phase 3 — Evidence Collection
  • Run the experiment
  • Collect raw data
  • Note environmental factors that could affect results
Phase 4 — Analysis
  • Apply statistical tests (delegate to @prism-scientist)
  • Calculate effect size, CI, p-value
  • Compare against the hypothesis
Phase 5 — Conclusion
  • Provisional, never absolute
  • State limitations
  • Identify follow-up experiments
Output

Saved to workspace/development/research/[C]sciomc-{topic}-{date}.md:

## Scientific Investigation — {topic}

### Hypothesis
{Falsifiable claim}

### Experimental Design
- Dependent variable: {what we measure}
- Independent variables: {what we vary}
- Controls: {what we hold constant}
- Sample size: {N}

### Method
{Step-by-step protocol}

### Results
{Raw data summary}

### Statistical Analysis
[delegated to @prism-scientist]

### Conclusion
{Provisional conclusion + limitations}

### Follow-ups
- {next experiment}
Pairs With
  • @prism-scientist (for statistical analysis)
  • @trail-tracer (when investigation is causal)
  • @apex-architect (when conclusion implies architecture change)
按 Apache-2.0 许可原样转载,未经改动 · 在 GitHub 查看 →

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