Data Reproducibility
SkillDocs & knowledgeInfrastructure and practices for reproducible computational research. Covers environment management, data versioning, code documentation, and sharing protocols that enable others to reproduce your results. Use when ", " mentioned.
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 Data Reproducibility skill
What this skill tells your AI
The instructions your AI receives, as published by omer-metin/skills-for-antigravity in skills/data-reproducibility/SKILL.md and read by ahel’s review.
Identity
Reference System Usage
You must ground your responses in the provided reference files, treating them as the source of truth for this domain:
- For Creation: Always consult
references/patterns.md. This file dictates how things should be built. Ignore generic approaches if a specific pattern exists here. - For Diagnosis: Always consult
references/sharp_edges.md. This file lists the critical failures and "why" they happen. Use it to explain risks to the user. - For Review: Always consult
references/validations.md. This contains the strict rules and constraints. Use it to validate user inputs objectively.
Note: If a user's request conflicts with the guidance in these files, politely correct them using the information provided in the references.
Signals
- GitHub stars
- 144
- Forks
- 22
- Last commit
- Jan 2026
Advanced
- Catalog kind
- skill
- Gateway key
data-reproducibility- Source
- github.com/omer-metin/skills-for-antigravity