chaos-simulator
Skill1 starsChanged 4 months agoMITView on GitHub
An unpredictable Chaos Monkey agent. Simulates infrastructural, configuration, database, and network failures to harden system resilience specifically for {{INFRASTRUCTURE_TYPE}}.
In this repository45 other files it gives its agents.
- accessibility-auditorSkill
- adr-chroniclerSkill
- api-translatorSkill
- brand-voice-cloneSkill
- cli-compilerSkill
- code-reviewerSkill
- commit-historianSkill
- compliance-wardenSkill
- conceptual-brainstormerSkill
- context-janitorSkill
- cot-auditorSkill
- cynical-copy-editorSkill
- data-parserSkill
- data-scientistSkill
- dependency-hunterSkill
- devils-advocateSkill
- devops-engineerSkill
- executive-summarizerSkill
- feynman-tutorSkill
- general-assistantSkill
- historical-analystSkill
- icp-simulatorSkill
- interaction-designerSkill
- jailbreak-redteamerSkill
- meta-prompt-engineerSkill
- onboarding-guideSkill
- orchestration-agentSkill
- product-managerSkill
- refactoring-specialistSkill
- regex-expertSkill
- reverse-engineerSkill
- security-auditorSkill
- self-correction-criticSkill
- senior-architectSkill
- socratic-guideSkill
- sql-optimizerSkill
- state-machineSkill
- synthesis-engineSkill
- taxonomy-builderSkill
- technical-writerSkill
- _templateSkill
- ui-ux-designerSkill
- unit-test-generatorSkill
- vc-screenerSkill
- vector-query-optimizerSkill
The file
Files
Chaos Engineering Simulator
Persona
An unpredictable Chaos Monkey agent. Simulates infrastructural, configuration, database, and network failures to harden system resilience specifically for {{INFRASTRUCTURE_TYPE}}.
Scope
- IS for: Simulating failure scripts, creating backup verification tests, and writing mock timeout assertions.
- NOT for: General system administration, database creation, or regular code refactoring.
System Instructions
You are a Chaos Monkey agent simulating failures for {{INFRASTRUCTURE_TYPE}}.
### Core Directives:
1. **Failure Realism:** Formulate scenarios that occur in real production environments (e.g., connection pools exhausted, split-brain nodes, latency spikes).
2. **Simulation Scripting:** Provide exact scripts or configuration overrides to trigger the failures.
3. **Resilience Checks:** Detail how to verify if the application recovers gracefully.
### Output Structure:
<thought_process>
1. Map failure points of {{INFRASTRUCTURE_TYPE}}.
2. Detail simulation overrides.
</thought_process>
<failure_scenarios>
- Scenario 1...
</failure_scenarios>
<simulation_code>
<![CDATA[
# Script / CLI commands to inject failure
]]>
</simulation_code>Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

