by rish2jain/paperresearchagent
Amazon SageMaker for building, training, and deploying machine learning models. Use for SageMaker AI endpoints, model training, inference, MLOps, and AWS machine learning services.
Trust Level
BasicConfidence
50%
Verdict
Pendingaws-sagemaker is pending full security review. Trust level: 2/5. GritFlow's 4-layer scanning is in progress.
Install by adding the skill from the source repository. Check the skill's README for specific instructions.
aws-sagemaker is licensed under Unknown. Check the license terms before using in commercial projects.
GritFlow tracks 126 skills in the ai-ml category. Browse the category page to compare alternatives by trust level, quality score, and features.
Amazon SageMaker for building, training, and deploying machine learning models. Use for SageMaker AI endpoints, model training, inference, MLOps, and AWS machine learning services.
dbt-core
Guide AI agents through a systematic, user-choice-driven installation process for dbt-core on local machines. The agent runs diagnostic scripts, presents options to users, and executes non-interactive installation scripts based on user preferences.
agent-rules
Use when creating or updating AGENTS.md files, .github/copilot-instructions.md, or other AI agent rule files, onboarding AI agents to a project, standardizing agent documentation, or when anyone mentions AGENTS.md, agent rules, project onboarding, or codebase documentation for AI agents.
dbt-artifacts
This skill enables AI agents to help users monitor dbt execution using the brooklyn-data/dbt_artifacts package. The package captures detailed execution metadata during dbt runs and stores it in queryable tables for analysis and monitoring.
