Dev Sciomc (Scientific Method)
SkillDev toolsScientific method scaffolding — hypothesis → experiment → evidence → conclusion. Use when you need rigorous causal reasoning rather than vibes-based debugging.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Dev Sciomc (Scientific Method) skill
What this skill tells your AI
The instructions your AI receives, as published by evolution-foundation/evo-nexus in .claude/skills/dev-sciomc/SKILL.md and read by ahel’s review.
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)
Signals
- GitHub stars
- 533
- Forks
- 177
- Last commit
- May 2026
Advanced
- Catalog kind
- skill
- Gateway key
dev-sciomc- Source
- github.com/evolution-foundation/evo-nexus