Build, test, migrate, integrate, and deploy Amazon Bedrock AgentCore agents. Use for AgentCore runtime, local development, import/migration, deployment, Memory, Gateway/MCP tools, Identity, Observability, Browser, Code Interpreter, policy, and harness-vs-code-path decisions. Load references only when that component is needed.
Scanned 5/27/2026
Install via CLI
openskills install Raishin/vanguard-frontier-agentic---
name: aws-agentcore
description: Build, test, migrate, integrate, and deploy Amazon Bedrock AgentCore agents. Use for AgentCore runtime, local development, import/migration, deployment, Memory, Gateway/MCP tools, Identity, Observability, Browser, Code Interpreter, policy, and harness-vs-code-path decisions. Load references only when that component is needed.
allowed-tools: Read Edit Write MultiEdit Grep Glob Bash
metadata:
author: "github: Raishin"
version: "0.1.6"
updated: "2026-05-05"
category: ai
---
# AWS AgentCore
## Purpose
Build and operate Amazon Bedrock AgentCore agents without stuffing runtime, harness, Memory, Gateway, Identity, Observability, Browser, Code Interpreter, policy, and environment/skills details into every prompt.
## When to use
Use this skill when the user asks to:
- create or adapt an AgentCore project,
- configure local development, invocation, packaging, deployment, runtime settings, harness settings, or environment/skills paths,
- integrate AgentCore Memory, Gateway, MCP tools, Identity, Observability, Browser, or Code Interpreter,
- review AgentCore security, least privilege, policy, tool exposure, credential handling, migration, or production readiness.
## Lean operating rules
- First decide whether the user has an existing agent or needs a new project. Do not scaffold over an existing codebase.
- For new projects, prefer the npm AgentCore CLI package `@aws/agentcore` because current AWS documentation recommends it.
- Treat the Python starter toolkit as legacy/migration-oriented unless the user is explicitly working inside an existing Python-based toolkit workflow.
- Separate code-based agents from config-based harnesses. Do not mix their guidance casually; current AWS docs describe the harness path as preview.
- Prefer `AwsDocumentationMcpServer` when available via `uvx awslabs.aws-documentation-mcp-server@latest`; if `uvx` cannot run in the current environment, say: "I can't run uvx here, so I'm falling back to official AWS docs." Then fall back to current official AWS AgentCore docs, Context7, or configured AgentCore MCP tools.
- Treat CLI syntax as version-sensitive; verify exact commands with installed tooling before production use.
- Treat Gateway policy, identity propagation, skill-path loading, and observability prerequisites as first-class concerns, not afterthoughts.
- Never ask users to paste AWS credentials, client secrets, access tokens, account IDs, customer data, or private keys into chat.
- Load only the reference needed for the component in scope.
## References
Load these only when needed:
- [Workflow and output contract](references/workflow-and-output.md) — use for end-to-end AgentCore project, local test, deployment, and output formatting.
- [Safety checklist](references/safety-checklist.md) — use before deployment, tool exposure, credential integration, Memory/Gateway changes, or production recommendations.
- [Official sources](references/official-sources.md) — use when grounding current AgentCore service behavior and docs URLs.
- [Getting started](references/getting-started.md) — use for project/runtime/harness/local workflow details, then verify commands against current toolkit version.
- [Memory integration](references/memory-integration.md) — use only for AgentCore Memory resource and agent wiring work.
- [Gateway integration](references/gateway-integration.md) — use only for Gateway, MCP tools, and tool target integration.
## Response minimum
Return, at minimum:
- the AgentCore component in scope,
- evidence level and docs/tooling used,
- safest next action,
- command or code path to verify,
- security and rollback caveats.
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