exploring-data-catalog

Full inventory and audit of AWS Glue Data Catalog assets across S3 Tables, Redshift-federated, and remote Iceberg catalogs. Triggers on: inventory the catalog, audit databases, list all tables, catalog overview, data landscape, enumerate catalogs, data inventory, search the catalog. Do NOT use for finding specific data (use finding-data-lake-assets), running queries (use querying-data-lake), or creating tables (use creating-data-lake-table).

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저장소: aws/agent-toolkit-for-aws
최근 소스 활동: 2026년 8월 6일 15:11
감지된 SKILL.md 언어: 영어
스타: 3,470
포크: 451

설치 방법

기본적으로 소스를 먼저 확인하는 Prompt가 선택됩니다. 직접 명령으로 전환하거나 로컬 사본을 다운로드할 수도 있습니다.

AI 어시스턴트로 설치

이 프롬프트를 복사해 사용 중인 AI 어시스턴트에 입력하세요.

Follow https://skillsmp.com/skill-install/prompt.md to install only the Agent Skill at https://github.com/aws/agent-toolkit-for-aws/tree/main/plugins/aws-data-analytics/skills/exploring-data-catalog.

직접 명령은 검토 Prompt를 거치지 않습니다. 실행하기 전에 소스를 확인하세요.

npx skills add https://github.com/aws/agent-toolkit-for-aws --skill exploring-data-catalog

명령은 한 줄로 유지됩니다. 복사하기 전에 가로로 스크롤해 전체 내용을 확인하세요.

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2 개 파일

SKILL.md

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name

exploring-data-catalog

description

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agent-advisor

Entry point for AI-agent work on AWS: pick a runtime, plan a migration for existing workloads, and build an executable POC — one phased flow. Triggers on: which runtime for my agent, AgentCore vs ECS vs EKS vs Lambda, AgentCore vs Lambda MicroVMs, deploy an AI agent on AWS, agent architecture on AWS, I have an agent idea what do I build, move/migrate my agents to AWS, agent migration plan, add AgentCore services (memory, gateway, identity, policy, observability) to an agent already on AWS, Temporal on AWS (migrate/run Temporal workers on AWS, a service orchestrated by Temporal, Temporal Cloud vs self-hosted). Temporal Workflow code is never rewritten into Step Functions. Requires at least one agentic component — a purely non-agent system (plain services, batch jobs, HTTP endpoints, non-agent Temporal Activities) is out of scope, redirected to gcp-to-aws / heroku-to-aws / llm-to-bedrock. Not for: compute/data migration with no AI agent; pure LLM SDK rewrite (use llm-to-bedrock); per-model pricing.

2026-11-12

bedrock-migration-assessment

Source-cloud-neutral assessment of AI/LLM usage for a migration to Amazon Bedrock. Use when the user wants to find which OpenAI (direct or Azure OpenAI), Anthropic, Google/Gemini, or OpenRouter calls their code makes, or already has a provider-neutral ai-workload-profile.json (schema 1.0 or 1.1), and wants to answer the AI migration questions. It scans the code or validates the profile, can measure OpenAI, Anthropic, and OpenRouter usage read-only with the user's consent and an admin or management key, shows a short preview, then runs Clarify, and needs no infrastructure skill installed. This release stops after Clarify: it does not design, estimate, generate artifacts, or rewrite code. To rewrite SDK calls to Bedrock and get a branch, use llm-to-bedrock; for infrastructure migrations use gcp-to-aws, azure-to-aws, or heroku-to-aws.

2026-11-11

azure-to-aws

Migrate Microsoft Azure workloads to AWS. Triggers on: Azure to AWS, move off Azure, AKS to EKS, App Service or Azure VMs to AWS compute, Azure SQL/Database to RDS, Cosmos DB to DynamoDB, Azure OpenAI to Bedrock, Azure cost estimates, or what-if workshops. Discovery uses the authenticated read-only `az` CLI, Terraform, a Resource Discovery for Azure (RDfA) report, and app code, with optional consent-gated OpenAI, OpenRouter, and Anthropic usage APIs. Terraform is optional. Runs Discover, Clarify, Design, Estimate, optional repricing, Generate, and Feedback; Clarify gates later phases and Generate is opt-in. Bicep/ARM discovery is not implemented; billing-export discovery is not implemented. Do not use for GCP or Heroku migrations, reverse migrations, general AWS architecture, or Azure-to-Azure refactoring.

2026-11-11

이 저장소의 모든 Skills 보기

exploring-data-catalog

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AI 어시스턴트로 설치

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