aws-emr-skillsAWS EMR interaction skill for managing EMR Serverless, EMR on EC2, and EMR on EKS. Submit and manage Spark, Hive, and PySpark jobs across all three EMR deplo...
Install via ClawdBot CLI:
clawdbot install yhyyz/aws-emr-skillsGrade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Potentially destructive shell commands in tool definitions
eval (Calls external URL not in known-safe list
https://github.com/yhyyz/aws-emr-skillsUses known external API (expected, informational)
amazonaws.comAI Analysis
The skill interacts only with AWS APIs (amazonaws.com) as documented for its stated purpose of managing EMR resources. The GitHub reference is a public homepage link, not an active external call. The 'eval' pattern is concerning but appears in a limited, controlled context for parsing AWS CLI output, not arbitrary user input.
Audited Apr 16, 2026 · audit v1.0
Generated May 7, 2026
A data engineering team uses EMR Serverless to run PySpark ETL jobs that transform raw data from S3 into structured formats. The skill automates job submission, monitoring, and log retrieval, enabling scalable, serverless data processing without cluster management.
Data analysts submit Hive or Spark SQL queries to EMR Serverless for ad-hoc analysis on large datasets. The skill retrieves query results from S3 and provides logs, allowing quick insights without provisioning infrastructure.
An operations team submits Spark steps to existing EMR clusters for nightly batch processing. The skill manages step lifecycle, retrieves step logs from S3, and cancels jobs if needed, ensuring reliable execution.
A DevOps team submits Spark jobs to virtual clusters on EKS for cost-efficient, containerized workloads. The skill handles job submission, status checks, and log retrieval, integrating with existing Kubernetes infrastructure.
An organization uses all three EMR modes for different workloads. The skill provides a unified interface to manage serverless applications, EC2 clusters, and EKS virtual clusters, streamlining operations across environments.
Offer managed EMR job execution and monitoring as a service. Clients submit jobs via the skill, and you handle infrastructure, job scheduling, and log retrieval, charging a subscription or per-job fee.
Provide pre-built data pipelines using EMR as the execution engine. The skill automates job runs, and you monetize access to processed datasets or analytics outputs, charging per query or data volume.
Consulting engagements to help enterprises adopt EMR across deployment modes. The skill accelerates migrations and optimizations, leading to reduced cloud costs and improved job performance, billed as project or retainer.
💬 Integration Tip
Ensure all required Python dependencies (boto3>=1.26.0) are installed and AWS credentials are configured via the default chain. Use environment variables for configuration to keep the skill portable across environments.
Scored May 7, 2026
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