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AWS Bedrock AgentCore comprehensive expert for deploying and managing AI agents at scale. Use when working with any AgentCore service including Gateway, Runtime, Memory, Identity, Code Interpreter, Br
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SOC 職業分類に基づく
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| name | aws-agentic-ai |
| description | AWS Bedrock AgentCore comprehensive expert for deploying and managing AI agents at scale. Use when working with any AgentCore service including Gateway, Runtime, Memory, Identity, Code Interpreter, Br |
| category | AI & Agents |
| source | antigravity |
| tags | ["api","mcp","claude","ai","agent","llm","automation","workflow","template","document"] |
| url | https://github.com/sickn33/antigravity-awesome-skills/tree/main/skills/aws-agentic-ai |
Use this skill when you need aWS Bedrock AgentCore comprehensive expert for deploying and managing AI agents at scale. Use when working with any AgentCore service including Gateway, Runtime, Memory, Identity, Code Interpreter, Browser, Observability, Agent Registry, or Evaluations. Covers agent deployment, MCP...
AWS Bedrock AgentCore provides a complete platform for deploying and scaling AI agents with nine core services. This skill covers service selection, deployment patterns, and integration workflows using AWS CLI.
How to use this skill: Identify the service(s) the user needs from the table below, then read the corresponding service README before responding. For cross-service patterns (credentials, security, registry integration), check the Cross-Service Resources section. Verify AWS-specific details using the MCP documentation tools.
Always verify AWS facts using MCP tools before answering. Two documentation sources are available:
mcp__acdocs__*) — bundled with this plugin, provides search_agentcore_docs and fetch_agentcore_doc for AgentCore documentationmcp__aws-mcp__* or mcp__*awsdocs*__*) — loaded via the aws-mcp-setup dependency for broader AWS documentationPrefer the AgentCore docs MCP for AgentCore-specific questions. If MCP tools are unavailable, guide the user through the aws-mcp-setup skill's setup flow.
| Service | Use For | Documentation |
|---|---|---|
| Gateway | Converting REST APIs to MCP tools | services/gateway/README.md |
| Runtime | Deploying and scaling agents | services/runtime/README.md |
| Memory | Managing conversation state | services/memory/README.md |
| Identity | Credential and access management | services/identity/README.md |
| Code Interpreter | Secure code execution in sandboxes | services/code-interpreter/README.md |
| Browser | Web automation and scraping | services/browser/README.md |
| Observability | Tracing and monitoring | services/observability/README.md |
| Agent Registry | Catalog, discover, and govern agents/tools (Preview) | services/registry/README.md |
| Evaluations | Automated agent quality assessment (LLM-as-a-Judge) | services/evaluations/README.md |
Read services/gateway/README.md before implementing — Gateway setup involves deployment strategies, IAM, and auth choices that vary significantly by use case.
Credential provider is only needed for API key authentication. Lambda targets use IAM roles, and MCP servers use OAuth.
Read cross-service/credential-management.md first — credential patterns differ across services and getting them wrong causes hard-to-debug auth failures.
Read services/registry/README.md first — the registry has governance workflows,