Hcls Build Agent

Building an HCLS Agent

When to use this skill

• Developer asks "how do I create a new HCLS agent?"
• Developer needs to structure tools, prompts, and workflows for a healthcare domain
• Developer is building an agent for genomics, drug discovery, clinical trials, or other HCLS workflows

Agent Architecture

An HCLS agent is composed of:

Agent = System Prompt + Tools (MCP) + Skills (Knowledge) + Guardrails

Steps

1. Choose a template

2. Define your agent's domain scope

• What HCLS workflow does it address?
• What data sources does it need? (databases, ontologies, literature)
• What actions should it perform? (query, analyze, generate, validate)
• What guardrails are needed? (PHI handling, clinical disclaimers, data validation)

3. Create tools

Tools are Python functions exposed via AgentCore Gateway (Lambda targets) or as local Strands tools.

# Local Strands tool
from strands import tool

@tool
def search_variants(gene: str, significance: str = "pathogenic") -> dict:
    """Search for genetic variants by gene name and clinical significance."""
    # Implementation
    pass

For Gateway tools (accessible to any MCP client), create Lambda functions and register as Gateway targets. See agents_catalog/28-Research-agent-biomni-gateway-tools/ for the pattern.

4. Write the system prompt

Include:

• Domain expertise and role definition
• Available tools and when to use each
• Output format expectations
• Clinical/scientific disclaimers
• Guardrails (what NOT to do)

5. Add MCP server connections

Reference existing MCP servers for domain tools the agent needs:

• Biomedical databases: deploy Biomni Gateway (mcp-servers/agentcore-gateway/biomni-research-tools/)
• Ontology lookup: deploy OLS server (mcp-servers/agentcore-runtime/ontology-lookup-service/)
• Literature: configure PubMed (mcp-servers/third-party/pubmed/)
• Genomics workflows: configure HealthOmics (mcp-servers/aws-public/aws-healthomics/)

6. Test

# Local testing with Strands
python main.py --prompt "Your test query"

# Test Gateway tools independently
python tests/test_gateway.py --prompt "Your test query"

References

• Reference implementation (simple): agents_catalog/24-Deep-Research-agent/
• Reference implementation (full Gateway): agents_catalog/28-Research-agent-biomni-gateway-tools/
• Reference implementation (FAST template): agents_catalog/35-Terminology-agent/
• Strands Agents docs: use the strands-docs MCP server
• AgentCore docs: use the agentcore-docs MCP server

AWS MCP Servers Used

When building infrastructure for the agent, use:

• aws-mcp — create IAM roles, Lambda functions, S3 buckets
• agentcore-docs — AgentCore API reference for Gateway/Runtime/Memory configuration
• aws-healthomics — if the agent needs genomics workflow capabilities