chaos-experiment-design
OfficialDesign chaos experiments with measurable outcomes
Authoradaptive-enforcement-lab
Version1.0.0
Installs0
System Documentation
What problem does it solve?
Chaos experimentation without structured design leads to unreliable results and unsafe blast radii. This skill provides a hypothesis-driven framework to plan, execute, and learn from chaos experiments with controlled scope and measurable outcomes.
Core Features & Use Cases
- Hypothesis-driven experiment design
- Controlled blast radius and safety constraints
- Automated validation of SLIs and post-incident learning
- Use Case: reliability validation in production-like environments
Quick Start
Define a hypothesis, establish success criteria and blast radius parameters, and implement an automated validation plan to run a controlled chaos experiment.
Dependency Matrix
Required Modules
None requiredComponents
Standard package💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: chaos-experiment-design Download link: https://github.com/adaptive-enforcement-lab/claude-skills/archive/main.zip#chaos-experiment-design Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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