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aws-agentic-ai skill

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This skill helps you deploy and manage AWS Bedrock AgentCore services across Gateway, Runtime, Memory, and Identity with best-practice guidance.

npx playbooks add skill zxkane/aws-skills --skill aws-agentic-ai

Review the files below or copy the command above to add this skill to your agents.

Files (13)

SKILL.md

6.5 KB

---
name: aws-agentic-ai
aliases:
  - bedrock-agentcore
  - aws-agentic-ai
description: AWS Bedrock AgentCore comprehensive expert for deploying and managing all AgentCore services. Use when working with Gateway, Runtime, Memory, Identity, or any AgentCore component. Covers MCP target deployment, credential management, schema optimization, runtime configuration, memory management, and identity services.
context: fork
model: sonnet
skills:
  - aws-mcp-setup
allowed-tools:
  - mcp__aws-mcp__*
  - mcp__awsdocs__*
  - Bash(aws bedrock-agentcore-control *)
  - Bash(aws bedrock-agentcore-runtime *)
  - Bash(aws bedrock *)
  - Bash(aws s3 cp *)
  - Bash(aws s3 ls *)
  - Bash(aws secretsmanager *)
  - Bash(aws sts get-caller-identity)
hooks:
  PreToolUse:
    - matcher: Bash(aws bedrock-agentcore-control create-*)
      command: aws sts get-caller-identity --query Account --output text
      once: true
---

# AWS Bedrock AgentCore

AWS Bedrock AgentCore provides a complete platform for deploying and scaling AI agents with seven core services. This skill guides you through service selection, deployment patterns, and integration workflows using AWS CLI.

## AWS Documentation Requirement

**CRITICAL**: This skill requires AWS MCP tools for accurate, up-to-date AWS information.

### Before Answering AWS Questions

1. **Always verify** using AWS MCP tools (if available):
   - `mcp__aws-mcp__aws___search_documentation` or `mcp__*awsdocs*__aws___search_documentation` - Search AWS docs
   - `mcp__aws-mcp__aws___read_documentation` or `mcp__*awsdocs*__aws___read_documentation` - Read specific pages
   - `mcp__aws-mcp__aws___get_regional_availability` - Check service availability

2. **If AWS MCP tools are unavailable**:
   - Guide user to configure AWS MCP using the `aws-mcp-setup` skill (auto-loaded as dependency)
   - Help determine which option fits their environment:
     - Has uvx + AWS credentials → Full AWS MCP Server
     - No Python/credentials → AWS Documentation MCP (no auth)
   - If cannot determine → Ask user which option to use

## When to Use This Skill

Use this skill when you need to:
- Deploy REST APIs as MCP tools for AI agents (Gateway)
- Execute agents in serverless runtime (Runtime)
- Add conversation memory to agents (Memory)
- Manage API credentials and authentication (Identity)
- Enable agents to execute code securely (Code Interpreter)
- Allow agents to interact with websites (Browser)
- Monitor and trace agent performance (Observability)

## Available Services

| Service | Use For | Documentation |
|---------|---------|---------------|
| **Gateway** | Converting REST APIs to MCP tools | [`services/gateway/README.md`](services/gateway/README.md) |
| **Runtime** | Deploying and scaling agents | [`services/runtime/README.md`](services/runtime/README.md) |
| **Memory** | Managing conversation state | [`services/memory/README.md`](services/memory/README.md) |
| **Identity** | Credential and access management | [`services/identity/README.md`](services/identity/README.md) |
| **Code Interpreter** | Secure code execution in sandboxes | [`services/code-interpreter/README.md`](services/code-interpreter/README.md) |
| **Browser** | Web automation and scraping | [`services/browser/README.md`](services/browser/README.md) |
| **Observability** | Tracing and monitoring | [`services/observability/README.md`](services/observability/README.md) |

## Common Workflows

### Deploying a Gateway Target

**MANDATORY - READ DETAILED DOCUMENTATION**: See [`services/gateway/README.md`](services/gateway/README.md) for complete Gateway setup guide including deployment strategies, troubleshooting, and IAM configuration.

**Quick Workflow**:
1. Upload OpenAPI schema to S3
2. *(API Key auth only)* Create credential provider and store API key
3. Create gateway target linking schema (and credentials if using API key)
4. Verify target status and test connectivity

> **Note**: Credential provider is only needed for API key authentication. Lambda targets use IAM roles, and MCP servers use OAuth.

### Managing Credentials

**MANDATORY - READ DETAILED DOCUMENTATION**: See [`cross-service/credential-management.md`](cross-service/credential-management.md) for unified credential management patterns across all services.

**Quick Workflow**:
1. Use Identity service credential providers for all API keys
2. Link providers to gateway targets via ARN references
3. Rotate credentials quarterly through credential provider updates
4. Monitor usage with CloudWatch metrics

### Monitoring Agents

**MANDATORY - READ DETAILED DOCUMENTATION**: See [`services/observability/README.md`](services/observability/README.md) for comprehensive monitoring setup.

**Quick Workflow**:
1. Enable observability for agents
2. Configure CloudWatch dashboards for metrics
3. Set up alarms for error rates and latency
4. Use X-Ray for distributed tracing

## Service-Specific Documentation

For detailed documentation on each AgentCore service, see the following resources:

### Gateway Service
- **Overview**: [`services/gateway/README.md`](services/gateway/README.md)
- **Deployment Strategies**: [`services/gateway/deployment-strategies.md`](services/gateway/deployment-strategies.md)
- **Troubleshooting**: [`services/gateway/troubleshooting-guide.md`](services/gateway/troubleshooting-guide.md)

### Runtime, Memory, Identity, Code Interpreter, Browser, Observability
Each service has comprehensive documentation in its respective directory:
- [`services/runtime/README.md`](services/runtime/README.md)
- [`services/memory/README.md`](services/memory/README.md)
- [`services/identity/README.md`](services/identity/README.md)
- [`services/code-interpreter/README.md`](services/code-interpreter/README.md)
- [`services/browser/README.md`](services/browser/README.md)
- [`services/observability/README.md`](services/observability/README.md)

## Cross-Service Resources

For patterns and best practices that span multiple AgentCore services:

- **Credential Management**: [`cross-service/credential-management.md`](cross-service/credential-management.md) - Unified credential patterns, security practices, rotation procedures

## Additional Resources

- **AWS Documentation**: [Amazon Bedrock AgentCore](https://docs.aws.amazon.com/bedrock-agentcore/latest/devguide/what-is-bedrock-agentcore.html)
- **API Reference**: [Bedrock AgentCore Control Plane API](https://docs.aws.amazon.com/bedrock-agentcore-control/latest/APIReference/)
- **AWS CLI Reference**: [bedrock-agentcore-control commands](https://awscli.amazonaws.com/v2/documentation/api/latest/reference/bedrock-agentcore-control/index.html)

Overview

This skill is an AWS Bedrock AgentCore expert that guides deployment and management of all AgentCore services including Gateway, Runtime, Memory, Identity, Code Interpreter, Browser, and Observability. It focuses on practical patterns for MCP target deployment, credential management, runtime configuration, memory handling, and identity services. Use it to plan, validate, and operationalize agent infrastructures on AWS.

How this skill works

The skill inspects service selection, deployment workflows, and integration steps and provides CLI-driven procedures and checks for AWS MCP-based deployments. It details how to upload schemas, create credential providers, link gateway targets, configure runtimes, and enable observability and tracing. When AWS MCP tools are available it instructs you to verify documentation and regional availability; otherwise it helps configure MCP options or advises which setup to choose.

When to use it

Deploy REST APIs or convert OpenAPI schemas into MCP tools (Gateway).
Provision and scale serverless agent runtimes or Lambda targets (Runtime).
Add, store, and rotate conversation memory for agents (Memory).
Manage API keys, IAM roles, and credential providers (Identity).
Enable secure code execution sandboxes and browser automation for agents (Code Interpreter, Browser).
Instrument agents with metrics, CloudWatch dashboards, and X-Ray tracing (Observability).

Best practices

Always verify service details and regional availability using AWS MCP documentation tools before deploy.
Upload OpenAPI schemas to S3 and validate them before creating Gateway targets; use Lambda targets with IAM roles for lower credential surface.
Enable observability for each agent, create dashboards for latency/error metrics, and add alarms for abnormal behavior.
Follow least-privilege IAM patterns for runtimes and credential providers; test deploys in a staging account first.

Example use cases

Create a Gateway target from an OpenAPI schema to expose internal services to agents with API key auth managed by Identity.
Deploy a serverless Runtime cluster to run high-concurrency agents and attach observability for tracing and performance tuning.
Add persistent conversation Memory for agents to retain context across sessions and manage storage lifecycle and rotation.
Configure Code Interpreter service to run user-submitted code in isolated sandboxes with monitoring and resource limits.
Set up Browser service to automate web interactions and scrape data for agents while enforcing credential and rate limits.

FAQ

Do I need AWS MCP tools to use this skill?

Yes—use AWS MCP tools to verify documentation and regional availability. If they are unavailable, the skill helps you configure AWS MCP options or choose the correct documentation-only path.

How should I store and rotate API credentials?

Use the Identity service credential providers, reference them by ARN from other services, rotate quarterly or per policy, and monitor usage in CloudWatch.