Official agent skill

Hcls Deploy Agent

by aws-samples in aws-samples/amazon-bedrock-agents-healthcare-lifesciences

OfficialMIT-0Auto-check passedDevOps & Cloud

Install Hcls Deploy Agent

skills CLI

$ npx skills add aws-samples/amazon-bedrock-agents-healthcare-lifesciences --skill hcls-deploy-agent -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI

$ gh skill install aws-samples/amazon-bedrock-agents-healthcare-lifesciences hcls-deploy-agent --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy

$ git clone --depth 1 https://github.com/aws-samples/amazon-bedrock-agents-healthcare-lifesciences.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/hcls-deploy-agent .claude/skills/hcls-deploy-agent && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Paste into Claude Code

Install the "hcls-deploy-agent" agent skill from https://github.com/aws-samples/amazon-bedrock-agents-healthcare-lifesciences/tree/main/skills/hcls-deploy-agent into .claude/skills/hcls-deploy-agent/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "hcls-deploy-agent", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/aws-samples/amazon-bedrock-agents-healthcare-lifesciences/tree/main/skills/hcls-deploy-agent

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add aws-samples/amazon-bedrock-agents-healthcare-lifesciences --skill hcls-deploy-agent -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install aws-samples/amazon-bedrock-agents-healthcare-lifesciences hcls-deploy-agent --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/aws-samples/amazon-bedrock-agents-healthcare-lifesciences.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/hcls-deploy-agent .agents/skills/hcls-deploy-agent && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "hcls-deploy-agent" agent skill from https://github.com/aws-samples/amazon-bedrock-agents-healthcare-lifesciences/tree/main/skills/hcls-deploy-agent into .agents/skills/hcls-deploy-agent/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "hcls-deploy-agent", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add aws-samples/amazon-bedrock-agents-healthcare-lifesciences --skill hcls-deploy-agent -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install aws-samples/amazon-bedrock-agents-healthcare-lifesciences hcls-deploy-agent --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/aws-samples/amazon-bedrock-agents-healthcare-lifesciences.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/hcls-deploy-agent .cursor/skills/hcls-deploy-agent && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "hcls-deploy-agent" agent skill from https://github.com/aws-samples/amazon-bedrock-agents-healthcare-lifesciences/tree/main/skills/hcls-deploy-agent into .cursor/skills/hcls-deploy-agent/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "hcls-deploy-agent", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/aws-samples/amazon-bedrock-agents-healthcare-lifesciences.git --path skills/hcls-deploy-agent

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add aws-samples/amazon-bedrock-agents-healthcare-lifesciences --skill hcls-deploy-agent -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install aws-samples/amazon-bedrock-agents-healthcare-lifesciences hcls-deploy-agent --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/aws-samples/amazon-bedrock-agents-healthcare-lifesciences.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/hcls-deploy-agent .gemini/skills/hcls-deploy-agent && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "hcls-deploy-agent" agent skill from https://github.com/aws-samples/amazon-bedrock-agents-healthcare-lifesciences/tree/main/skills/hcls-deploy-agent into .gemini/skills/hcls-deploy-agent/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "hcls-deploy-agent", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install aws-samples/amazon-bedrock-agents-healthcare-lifesciences hcls-deploy-agent

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add aws-samples/amazon-bedrock-agents-healthcare-lifesciences --skill hcls-deploy-agent -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/aws-samples/amazon-bedrock-agents-healthcare-lifesciences.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/hcls-deploy-agent .github/skills/hcls-deploy-agent && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "hcls-deploy-agent" agent skill from https://github.com/aws-samples/amazon-bedrock-agents-healthcare-lifesciences/tree/main/skills/hcls-deploy-agent into .github/skills/hcls-deploy-agent/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "hcls-deploy-agent", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add aws-samples/amazon-bedrock-agents-healthcare-lifesciences --skill hcls-deploy-agent -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install aws-samples/amazon-bedrock-agents-healthcare-lifesciences hcls-deploy-agent --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/aws-samples/amazon-bedrock-agents-healthcare-lifesciences.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/hcls-deploy-agent .opencode/skills/hcls-deploy-agent && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "hcls-deploy-agent" agent skill from https://github.com/aws-samples/amazon-bedrock-agents-healthcare-lifesciences/tree/main/skills/hcls-deploy-agent into .opencode/skills/hcls-deploy-agent/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "hcls-deploy-agent", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: hcls-deploy-agent
GitHub stars: 274
Token cost: ~813 tokens
SKILL.md length: 174 words
Files: 3 (incl. scripts, references)
Skills in repo: 12
Repo updated: Oct 1, 2026
First seen: Oct 7, 2026
Licence: MIT-0

At a glance

Works in 5 steps: Prerequisites → Deploy Infrastructure → Deploy Agent Runtime → …
A developer wants to deploy an HCLS agent to Amazon Bedrock AgentCore
SKILL.md covers When to use this skill, Deployment Components, Steps and Deployment Templates, plus 2 more sections
Calls python and pip

What it does

Hcls Deploy Agent is an agent skill from aws-samples/amazon-bedrock-agents-healthcare-lifesciences, published by the product's own GitHub organization. Use when a developer wants to deploy an HCLS agent to Amazon Bedrock AgentCore, configure Gateway tools as MCP endpoints, set up authentication with Cognito, configure memory, or register an agent in the AgentCore Registry. Also use for deployment troubleshooting.

Its SKILL.md is about 810 tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including scripts and reference files.

It sits in DevOps & Cloud, covering Deployment and MCP servers. It works with Model Context Protocol, Amazon Web Services and Amazon Bedrock. The licence is MIT-0.

When your agent uses it

A developer wants to deploy an HCLS agent to Amazon Bedrock AgentCore
Configure Gateway tools as MCP endpoints
Set up authentication with Cognito
Configure memory

Example prompts

“/hcls-deploy-agent”

Requirements

Python 3

Workflow steps

5 steps, taken from the step headings in SKILL.md.

Prerequisites
Deploy Infrastructure
Deploy Agent Runtime
Verify
Register in AgentCore Registry (optional)

What it can do on your machine

Read from SKILL.md and the folder at commit 9960565. It shows what the files ask for, not the result of running them.

Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships 1 file in scripts/, which the agent can run.
Shell commands in SKILL.md call:
- python
- pip
From the folder's file list and the shell code blocks in SKILL.md.
Network
Links to these hosts (documentation or services it may open):
- github.com
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Hcls Deploy Agent loads about 813 tokens when it runs. Until then it costs about 71 tokens; SKILL.md has 174 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~71
When it runs · the whole SKILL.md, loaded when a task matches: ~813

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from aws-samples/amazon-bedrock-agents-healthcare-lifesciences at commit 9960565, republished under its MIT-0 licence (© aws-samples). 174 words, ~813 tokens.

Download SKILL.mdSave it as .claude/skills/hcls-deploy-agent/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.

name: hcls-deploy-agent
description: Use when a developer wants to deploy an HCLS agent to Amazon Bedrock AgentCore, configure Gateway tools as MCP endpoints, set up authentication with Cognito, configure memory, or register an agent in the AgentCore Registry. Also use for deployment troubleshooting.

Deploying an HCLS Agent

When to use this skill

Developer asks "how do I deploy this agent?"
Developer needs to configure AgentCore Gateway, Runtime, Memory, or Identity
Developer wants to expose tools as MCP endpoints
Developer wants to register an agent in the AgentCore Registry

Deployment Components

AgentCore Deployment
├── Runtime       — Hosts the agent container
├── Gateway       — Exposes tools as MCP endpoints (Lambda targets)
├── Memory        — Conversation persistence (semantic, summary, preferences)
├── Identity      — Cognito OAuth2 authentication
└── Registry      — Agent discovery for multi-agent workflows

Steps

1. Prerequisites

bash

# Install AgentCore CLI
pip install bedrock-agentcore

# Configure
agentcore configure --entrypoint main.py \
  -rf agent/requirements.txt \
  -er <IAM_ROLE_ARN> \
  --name <agent-name>

2. Deploy Infrastructure

Run the prerequisite script (creates Lambda tools, Cognito, Gateway):

bash

./scripts/prereq.sh

This deploys CloudFormation stacks for:

Lambda functions (tool handlers)
IAM roles (agent execution, Gateway invocation)
Cognito user pool (OAuth2 authentication)
AgentCore Gateway (MCP endpoint with tool targets)
AgentCore Memory (conversation persistence)

3. Deploy Agent Runtime

bash

# Remove stale config
rm -f .agentcore.yaml

# Launch (builds container, pushes to ECR, deploys to Runtime)
agentcore launch

4. Verify

bash

# Invoke the deployed agent
agentcore invoke '{"prompt": "Hello, can you help me?"}'

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

# Test memory
python tests/test_memory.py load-conversation

5. Register in AgentCore Registry (optional)

For multi-agent discovery, register the agent:

python

import boto3
client = boto3.client('bedrock-agentcore')

client.create_registry_record(
    registryName="hcls-registry",
    recordName="<agent-name>",
    description="<rich description for semantic search>",
    descriptorType="MCP",  # or "A2A" for agent-to-agent
    descriptors={...}
)

Deployment Templates

Template	What it deploys
`agentcore_template/`	Backend: Runtime + Gateway + Memory + Streamlit UI
FAST	Full-stack: React/Amplify + Cognito + AgentCore + CDK

AWS MCP Servers Used

When deploying, the following AWS MCP servers help:

agentcore-docs — API reference for Gateway/Runtime/Memory/Registry
aws-mcp — create IAM roles, manage CloudFormation stacks, configure S3
strands-docs — framework patterns for agent code

References

Deployment scripts: agentcore_template/scripts/
Full deployment example: agents_catalog/28-Research-agent-biomni-gateway-tools/scripts/prereq.sh
FAST template deployment: agents_catalog/35-Terminology-agent/

Files

SKILL.md and 2 other files (scripts, references) in skills/hcls-deploy-agent of aws-samples/amazon-bedrock-agents-healthcare-lifesciences.

SKILL.md
references/.gitkeep
scripts/.gitkeep

Open the folder on GitHubat commit 9960565

Compare with similar skills

Hcls Deploy Agent next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Hcls Deploy Agent compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Hcls Deploy Agent this skillaws-samples/amazon-bedrock-agents-healthcare-lifesciences	274	—	~813	Automated safety check: Pass	MIT-0	5 days ago
AWS Agentic AIzxkane/aws-skills	367	1 repos	~2.5k	Automated safety check: Pass	MIT	3 mo ago
AWS Strands Agents Agentcoresammcj/agentic-coding	162	1 repos	~3k	Automated safety check: Pass	Apache-2.0	yesterday
AWS Agentic AImajiayu000/claude-skill-registry	666	1 repos	~1.5k	Automated safety check: Pass	MIT	today
AWS Cdk Developmentzxkane/aws-skills	367	2 repos	~2.5k	Automated safety check: Pass	MIT	3 mo ago
Frontmcp Deploymentagentfront/frontmcp	146	—	~9.2k	Automated safety check: Notes	Apache-2.0	today

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Works with

Questions about Hcls Deploy Agent

What does Hcls Deploy Agent do?

A skill your agent uses when a developer wants to deploy an HCLS agent to Amazon Bedrock AgentCore, configure Gateway tools as MCP endpoints, set up authentication with Cognito, configure memory, or…. Hcls Deploy Agent is an agent skill from aws-samples/amazon-bedrock-agents-healthcare-lifesciences, published by the product's own GitHub organization. Use when a developer wants to deploy an HCLS agent to Amazon Bedrock AgentCore, configure Gateway tools as MCP endpoints, set up authentication with Cognito, configure memory, or register an agent in the AgentCore Registry.

When should I use Hcls Deploy Agent?

Hcls Deploy Agent fits situations like: A developer wants to deploy an HCLS agent to Amazon Bedrock AgentCore; configure Gateway tools as MCP endpoints; set up authentication with Cognito; configure memory.

How do I install Hcls Deploy Agent in Claude Code?

Run `npx skills add aws-samples/amazon-bedrock-agents-healthcare-lifesciences --skill hcls-deploy-agent -a claude-code`. Or copy the skill folder (skills/hcls-deploy-agent in aws-samples/amazon-bedrock-agents-healthcare-lifesciences) into .claude/skills/hcls-deploy-agent in your project. Claude Code loads it when a task matches its description.

How do I install Hcls Deploy Agent in Codex?

Run `npx skills add aws-samples/amazon-bedrock-agents-healthcare-lifesciences --skill hcls-deploy-agent -a codex`. Or copy the skill folder (skills/hcls-deploy-agent in aws-samples/amazon-bedrock-agents-healthcare-lifesciences) into .agents/skills/hcls-deploy-agent in your project. Codex loads it when a task matches its description.

Can I use Hcls Deploy Agent in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add aws-samples/amazon-bedrock-agents-healthcare-lifesciences --skill hcls-deploy-agent -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/hcls-deploy-agent, .gemini/skills/hcls-deploy-agent, .github/skills/hcls-deploy-agent and .opencode/skills/hcls-deploy-agent in your project.

What does Hcls Deploy Agent need to run?

Going by SKILL.md and its folder, Hcls Deploy Agent needs the command-line tools its instructions call (python and pip). Our summary lists: Python 3.

Does Hcls Deploy Agent access the network?

SKILL.md names 1 domain. As links in the text: github.com. This is read from the text; nothing was executed.

Is Hcls Deploy Agent safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Hcls Deploy Agent use?

Hcls Deploy Agent is published under the MIT-0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Hcls Deploy Agent use?

About 813 tokens (SKILL.md is roughly 3.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Hcls Deploy Agent?

Skills that share tags, products or a category with Hcls Deploy Agent: AWS Agentic AI (zxkane/aws-skills, 367 stars), AWS Strands Agents Agentcore (sammcj/agentic-coding, 162 stars), AWS Agentic AI (majiayu000/claude-skill-registry, 666 stars) and AWS Cdk Development (zxkane/aws-skills, 367 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Hcls Deploy Agent?

aws-samples (a GitHub organization, an official publisher) maintains it in aws-samples/amazon-bedrock-agents-healthcare-lifesciences, which has 274 GitHub stars. The repository holds 12 skills in this directory. The repository was last updated on October 1, 2026.

Source: aws-samples/amazon-bedrock-agents-healthcare-lifesciences on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Hcls Deploy Agent

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

Workflow steps

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

Deploying an HCLS Agent

When to use this skill

Deployment Components

Steps

1. Prerequisites

2. Deploy Infrastructure

3. Deploy Agent Runtime

4. Verify

5. Register in AgentCore Registry (optional)

Deployment Templates

AWS MCP Servers Used

References

Files

Compare with similar skills

Similar skills

More from aws-samples/amazon-bedrock-agents-healthcare-lifesciences

Related

Questions about Hcls Deploy Agent