sample-agent-greenhouse

Guide developer teams through AIDLC Inception — structured requirements gathering, design, and artifact generation

Reviews agent code for security vulnerabilities, quality issues, and agent-specific best practices. Checks for prompt injection, credential exposure, unsafe execution, error handling, and testing.

Debugging specialist for AgentCore deployments: container failures, IAM permission errors, runtime exceptions, networking issues, and performance problems. Use when developers report errors, crashes, deployment failures, or need help troubleshooting their agent applications.

Generates deployment configurations for Amazon Bedrock AgentCore. Produces Dockerfiles, IAM policies, CDK stacks, buildspec files, runtime configs, and environment variable templates following AWS security best practices and least-privilege principles.

Reviews agent applications for platform deployment readiness. Checks containerization, secrets, config, health endpoints, statefulness, error handling, dependencies, and security.

Fleet operations specialist for agent restart, scaling, graceful draining, and capacity planning. Use when teams need to restart agents, scale the fleet up or down, drain agents for maintenance, or plan capacity.

Governance specialist for agent registration, Cedar policy management, message routing configuration, and platform compliance. Use when teams need to register agents, configure policies, set up routing patterns, or enforce governance standards.

Create structured GitHub issues from review and compliance findings

Platform knowledge base: readiness requirements (C1-C12), deployment patterns, agent architecture patterns, and troubleshooting guides. Use when developers ask about platform capabilities, best practices, requirements, how to deploy, what is needed, or need help debugging deployment issues.

Production monitoring specialist for AgentCore deployments: CloudWatch metrics, alarms, dashboards, operational best practices. Use when developers need to set up monitoring, configure alerts, analyze metrics, troubleshoot performance issues, or build dashboards.

Observability specialist for agent fleet monitoring, policy violation tracking, audit log analysis, and compliance reporting. Use when teams need to check agent status, investigate violations, analyze audit logs, or generate operational reports.

Onboarding specialist for new team setup, CLAUDE.md generation, agent configuration, and platform standards compliance. Use when teams need to onboard to the platform, set up new agents, generate configuration files, or learn platform standards.

Review GitHub PRs for code quality and spec compliance

Generate project skeletons and boilerplate for agent projects

Verify codebase compliance against spec.md acceptance criteria

Generate structured test cases from spec.md acceptance criteria with 1:1 AC-to-TC traceability

Deep knowledge about AI agent architectures, AWS services, memory patterns, and best practices. Use as reference when answering technical questions.

Analyze and optimize costs for AI agent workloads on AWS — model selection, caching, memory pricing, scaling strategies. Use when the user asks about costs, pricing, or optimization.

Help teams migrate AI agents between frameworks and runtimes — Bedrock Agents to AgentCore, LangChain to Strands, monolith to multi-agent. Use when the user asks about migration, porting, or switching frameworks.

Compile enterprise policies into project-level CLAUDE.md files. Use when onboarding a new project (Phase 1) or when the user asks about policy requirements, compliance, or CLAUDE.md generation.

Review AI agent security — IAM policies, secret management, input validation, prompt injection defense, memory isolation. Use when the user asks about security, hardening, or threat modeling for agent systems.

Help design and implement test strategies for AI agents — unit tests, integration tests, agent evaluation, memory testing, tool mocking. Use when the user asks about testing agents.