Chaos Runner

DevOps & Security

chaos-runner

Chaos Runner is an Agent Skill for devops & security published in the a5c-ai/babysitter repository on GitHub: a SKILL.md instruction file an AI agent can load to do this task.

Run chaos engineering experiments using Chaos Monkey, Litmus, or Gremlin

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How to use this skill

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Inspect the Agent Skill at https://github.com/a5c-ai/babysitter/blob/HEAD/library/specializations/software-architecture/skills/chaos-runner/SKILL.md and all supporting files. Report provenance, permissions, scripts, dependencies, and security risks. Propose an exact installation into .agents/skills/chaos-runner, but wait for my approval before writing files or running scripts.

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Chaos Engineering Runner Skill

Overview

Runs chaos engineering experiments using Chaos Monkey, Litmus, or Gremlin including failure injection scenarios, blast radius control, and experiment analysis.

Capabilities

Run Chaos Monkey experiments
Litmus chaos execution
Gremlin integration
Failure injection scenarios
Blast radius control
Steady state validation
Experiment rollback
Results analysis

Target Processes

resilience-patterns

Input Schema

{
  "type": "object",
  "required": ["experiment"],
  "properties": {
    "experiment": {
      "type": "object",
      "properties": {
        "name": { "type": "string" },
        "type": {
          "type": "string",
          "enum": ["pod-kill", "network-latency", "cpu-stress", "memory-stress", "disk-fill", "node-drain"]
        },
        "target": {
          "type": "object",
          "properties": {
            "namespace": { "type": "string" },
            "labelSelector": { "type": "object" },
            "percentage": { "type": "number" }
          }
        },
        "duration": { "type": "string" }
      }
    },
    "framework": {
      "type": "string",
      "enum": ["litmus", "gremlin", "chaos-monkey", "toxiproxy"],
      "default": "litmus"
    },
    "steadyState": {
      "type": "object",
      "properties": {
        "probes": { "type": "array" },
        "assertions": { "type": "array" }
      }
    },
    "options": {
      "type": "object",
      "properties": {
        "dryRun": {
          "type": "boolean",
          "default": true
        },
        "autoRollback": {
          "type": "boolean",
          "default": true
        },
        "notifyOnFailure": {
          "type": "boolean",
          "default": true
        }
      }
    }
  }
}

Output Schema

{
  "type": "object",
  "properties": {
    "experimentId": {
      "type": "string"
    },
    "status": {
      "type": "string",
      "enum": ["passed", "failed", "aborted"]
    },
    "steadyStateValidation": {
      "type": "object",
      "properties": {
        "before": { "type": "boolean" },
        "during": { "type": "boolean" },
        "after": { "type": "boolean" }
      }
    },
    "metrics": {
      "type": "object",
      "properties": {
        "affectedPods": { "type": "number" },
        "recoveryTime": { "type": "string" },
        "errorRate": { "type": "number" }
      }
    },
    "findings": {
      "type": "array"
    },
    "recommendations": {
      "type": "array"
    }
  }
}

Usage Example

{
  kind: 'skill',
  skill: {
    name: 'chaos-runner',
    context: {
      experiment: {
        name: 'pod-failure-test',
        type: 'pod-kill',
        target: {
          namespace: 'production',
          labelSelector: { app: 'api-service' },
          percentage: 50
        },
        duration: '5m'
      },
      framework: 'litmus',
      steadyState: {
        probes: [{ type: 'http', endpoint: '/health' }],
        assertions: [{ metric: 'error_rate', operator: '<', value: 0.01 }]
      },
      options: {
        dryRun: false,
        autoRollback: true
      }
    }
  }
}