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aws-agentic-ai

Skill4 starsChanged 25 days agoMITView on GitHub

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.

2 other projects use a version of this, 1 of them edited.

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We split this skill into the rules it gives an agent

8 rules. About 0 are common, 8 are distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈8

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    No Python/credentials → AWS Documentation MCP (no auth)

    line 28
  2. Distinctive:

    If cannot determine → Ask user which option to use

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  3. Distinctive:

    Use this skill when you need to:

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  4. Distinctive:

    Add conversation memory to agents (Memory)

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  5. Distinctive:

    Create gateway target linking schema (and credentials if using API key)

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  6. Distinctive:

    Verify target status and test connectivity

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  7. Distinctive:

    Use Identity service credential providers for all API keys

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  8. Distinctive:

    Use X-Ray for distributed tracing

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≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

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: See AWS MCP Setup Guide
    • 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

ServiceUse ForDocumentation
GatewayConverting REST APIs to MCP toolsservices/gateway/README.md
RuntimeDeploying and scaling agentsservices/runtime/README.md
MemoryManaging conversation stateservices/memory/README.md
IdentityCredential and access managementservices/identity/README.md
Code InterpreterSecure code execution in sandboxesservices/code-interpreter/README.md
BrowserWeb automation and scrapingservices/browser/README.md
ObservabilityTracing and monitoringservices/observability/README.md

Common Workflows

Deploying a Gateway Target

MANDATORY - READ DETAILED DOCUMENTATION: See 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 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 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
  • Deployment Strategies: services/gateway/deployment-strategies.md
  • Troubleshooting: 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/memory/README.md
  • services/identity/README.md
  • services/code-interpreter/README.md
  • services/browser/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 - Unified credential patterns, security practices, rotation procedures

Additional Resources

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