library/specializations/security-compliance/skills/multi-cloud-security-posture/SKILL.md
Unified cloud security posture management across AWS, Azure, and GCP with normalized metrics and CIS benchmark comparison
npx skillsauth add a5c-ai/babysitter multi-cloud-security-postureInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
Unified cloud security posture management (CSPM) across AWS, Azure, and GCP to aggregate findings, normalize security metrics, compare against CIS benchmarks, and provide a consolidated view of multi-cloud security.
| Category | AWS | Azure | GCP | |----------|-----|-------|-----| | Identity | IAM | Azure AD | Cloud IAM | | Compute | EC2, Lambda | VMs, Functions | Compute, Functions | | Storage | S3, EBS | Storage Accounts | Cloud Storage | | Network | VPC, SGs | VNet, NSGs | VPC, Firewall | | Database | RDS, DynamoDB | SQL, Cosmos | Cloud SQL, Spanner | | Encryption | KMS | Key Vault | Cloud KMS | | Logging | CloudTrail | Activity Log | Audit Logs |
{
"type": "object",
"properties": {
"cloudProviders": {
"type": "array",
"items": {
"type": "string",
"enum": ["AWS", "Azure", "GCP"]
},
"description": "Cloud providers to include"
},
"awsAccounts": {
"type": "array",
"items": { "type": "string" }
},
"azureSubscriptions": {
"type": "array",
"items": { "type": "string" }
},
"gcpProjects": {
"type": "array",
"items": { "type": "string" }
},
"complianceFrameworks": {
"type": "array",
"items": {
"type": "string",
"enum": ["CIS", "SOC2", "PCI-DSS", "HIPAA", "ISO27001", "NIST", "FedRAMP"]
}
},
"reportingPeriod": {
"type": "object",
"properties": {
"startDate": { "type": "string", "format": "date" },
"endDate": { "type": "string", "format": "date" }
}
},
"severityThreshold": {
"type": "string",
"enum": ["critical", "high", "medium", "low"]
},
"includeRemediationStatus": {
"type": "boolean"
}
},
"required": ["cloudProviders"]
}
{
"type": "object",
"properties": {
"reportId": {
"type": "string"
},
"reportTimestamp": {
"type": "string",
"format": "date-time"
},
"cloudsCovered": {
"type": "array"
},
"overallPosture": {
"type": "object",
"properties": {
"aggregateScore": { "type": "number" },
"riskLevel": { "type": "string" },
"trend": { "type": "string", "enum": ["improving", "stable", "degrading"] }
}
},
"postureByCloud": {
"type": "object",
"properties": {
"AWS": {
"type": "object",
"properties": {
"score": { "type": "number" },
"findings": { "type": "integer" },
"criticalFindings": { "type": "integer" }
}
},
"Azure": { "type": "object" },
"GCP": { "type": "object" }
}
},
"findingsByCategory": {
"type": "object",
"properties": {
"identity": { "type": "integer" },
"compute": { "type": "integer" },
"storage": { "type": "integer" },
"network": { "type": "integer" },
"encryption": { "type": "integer" },
"logging": { "type": "integer" }
}
},
"complianceStatus": {
"type": "object"
},
"topFindings": {
"type": "array",
"items": {
"type": "object",
"properties": {
"cloud": { "type": "string" },
"category": { "type": "string" },
"severity": { "type": "string" },
"count": { "type": "integer" },
"description": { "type": "string" }
}
}
},
"remediationProgress": {
"type": "object",
"properties": {
"totalFindings": { "type": "integer" },
"remediated": { "type": "integer" },
"inProgress": { "type": "integer" },
"pending": { "type": "integer" },
"mttr": { "type": "string" }
}
},
"recommendations": {
"type": "array",
"items": { "type": "string" }
}
}
}
skill: {
name: 'multi-cloud-security-posture',
context: {
cloudProviders: ['AWS', 'Azure', 'GCP'],
awsAccounts: ['123456789012'],
azureSubscriptions: ['sub-id-1'],
gcpProjects: ['my-project'],
complianceFrameworks: ['CIS', 'SOC2'],
includeRemediationStatus: true
}
}
development
Model documentation skill for generating model cards following Google's model card framework.
development
MLflow integration skill for experiment tracking, model registry, and artifact management. Enables LLMs to log experiments, compare runs, manage model lifecycle, and retrieve artifacts through the MLflow API.
data-ai
LIME-based local explanation skill for individual predictions across tabular, text, and image data.
devops
Kubeflow Pipelines skill for ML workflow orchestration, component management, and Kubernetes-native ML.