Skip to main content
ClaudeWave
Skill309 repo starsupdated 1mo ago

aws-agentic-ai

This skill provides guidance on deploying and managing AI agents using AWS Bedrock AgentCore's nine core services, including Gateway, Runtime, Memory, Identity, Code Interpreter, Browser, Observability, Agent Registry, and Evaluations. Use it when building, deploying, integrating, monitoring, or governing AI agents on AWS, or when working with MCP tool integration, credential management, agent discovery, or automated quality assessment.

Install in Claude Code
Copy
git clone --depth 1 https://github.com/zxkane/aws-skills /tmp/aws-agentic-ai && cp -r /tmp/aws-agentic-ai/plugins/aws-agentic-ai/skills/aws-agentic-ai ~/.claude/skills/aws-agentic-ai
Then start a new Claude Code session; the skill loads automatically.

SKILL.md

# AWS Bedrock AgentCore

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.

## AWS Documentation Requirement

Always verify AWS facts using MCP tools before answering. Two documentation sources are available:
- **AgentCore-specific docs** (`mcp__acdocs__*`) — bundled with this plugin, provides `search_agentcore_docs` and `fetch_agentcore_doc` for AgentCore documentation
- **General AWS docs** (`mcp__aws-mcp__*` or `mcp__*awsdocs*__*`) — loaded via the `aws-mcp-setup` dependency for broader AWS documentation

Prefer 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.

## 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) |
| **Agent Registry** | Catalog, discover, and govern agents/tools (Preview) | [`services/registry/README.md`](services/registry/README.md) |
| **Evaluations** | Automated agent quality assessment (LLM-as-a-Judge) | [`services/evaluations/README.md`](services/evaluations/README.md) |

## Common Workflows

### Deploying a Gateway Target

Read [`services/gateway/README.md`](services/gateway/README.md) before implementing — Gateway setup involves deployment strategies, IAM, and auth choices that vary significantly by use case.

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

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

### Managing Credentials

Read [`cross-service/credential-management.md`](cross-service/credential-management.md) first — credential patterns differ across services and getting them wrong causes hard-to-debug auth failures.

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

### Discovering Agents and Tools (Agent Registry)

Read [`services/registry/README.md`](services/registry/README.md) first — the registry has governance workflows, MCP endpoint options, and sync modes that affect how records become discoverable.

1. Create a registry to catalog your organization's AI resources
2. Register resources (MCP servers, agents, skills, custom) with descriptive metadata
3. Submit records for approval (auto-approve for dev, manual for production)
4. Search and discover approved resources via CLI or MCP endpoint

> Agent Registry is in Preview. Available in us-east-1, us-west-2, eu-west-1, ap-northeast-1, ap-southeast-2.

### Evaluating Agent Quality

Read [`services/evaluations/README.md`](services/evaluations/README.md) first — evaluators, scoring modes, and IAM setup vary between online monitoring and on-demand testing.

1. Instrument the agent with OpenTelemetry (ADOT) for trace collection
2. Create evaluators (use built-in like `Builtin.Helpfulness` or create custom)
3. Set up online evaluation with sampling rate and data source
4. Monitor scores in CloudWatch dashboards; investigate low-scoring sessions

### Monitoring Agents

Read [`services/observability/README.md`](services/observability/README.md) for the full monitoring setup — observability configuration depends on your Runtime protocol and framework choice.

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

## Deep-Dive References

Each service README (linked in the table above) contains sub-links to getting-started guides, troubleshooting, and advanced topics. Start with the service README and follow pointers from there.

### Advanced Runtime & OAuth References

Deep-dive reference documentation for Runtime internals, deployment, OAuth integration, and communication protocols. Read these when building production Runtime deployments or configuring OAuth authentication:

- **OAuth Integration**: [`references/agentcore-oauth-integration.md`](references/agentcore-oauth-integration.md) - Three-layer OAuth architecture (Inbound JWT, Outbound Credential Provider, Gateway OAuth), Cognito configuration, supported IdPs, end-to-end CDK examples
- **Runtime Core Mechanisms**: [`references/agentcore-runtime-core.md`](references/agentcore-runtime-core.md) - Container contract, MicroVM Session model, Agent lifecycle (per-request vs per-session), tool integration (MCP/HTTP), startup flow
- **Runtime Deployment & Operations**: [`references/agentcore-runtime-deploy.md`](r
aws-cdk-developmentSkill

AWS Cloud Development Kit (CDK) expert for building cloud infrastructure with TypeScript/Python. Use when creating CDK stacks, defining CDK constructs, implementing infrastructure as code, or when the user mentions CDK, CloudFormation, IaC, cdk synth, cdk deploy, or wants to define AWS infrastructure programmatically. Covers CDK app structure, construct patterns, stack composition, and deployment workflows.

aws-mcp-setupSkill

Configure AWS MCP servers for documentation search and API access. Use when setting up AWS MCP, configuring AWS documentation tools, troubleshooting MCP connectivity, or when user mentions aws-mcp, awsdocs, uvx setup, or MCP server configuration. Covers both Full AWS MCP Server (with uvx + credentials) and lightweight Documentation MCP (no auth required).

aws-cost-operationsSkill

AWS cost optimization, monitoring, and operational excellence expert. Use when analyzing AWS bills, estimating costs, setting up CloudWatch alarms, querying logs, auditing CloudTrail activity, or assessing security posture. Essential when user mentions AWS costs, spending, billing, budget, pricing, CloudWatch, observability, monitoring, alerting, CloudTrail, audit, or wants to optimize AWS infrastructure costs and operational efficiency.

aws-serverless-edaSkill

AWS serverless and event-driven architecture expert based on Well-Architected Framework. Use when building serverless APIs, Lambda functions, REST APIs, microservices, or async workflows. Covers Lambda with TypeScript/Python, API Gateway (REST/HTTP), DynamoDB, Step Functions, EventBridge, SQS, SNS, and serverless patterns. Essential when user mentions serverless, Lambda, API Gateway, event-driven, async processing, queues, pub/sub, or wants to build scalable serverless applications with AWS best practices.