AWS Bedrock AgentCore comprehensive expert for deploying and managing all AgentCore services.
$ npx skills add CommandCodeAI/agent-skills --skill aws-agentic-ai -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install CommandCodeAI/agent-skills aws-agentic-ai --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/CommandCodeAI/agent-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/aws-agentic-ai .claude/skills/aws-agentic-ai && rm -rf skills-srcUse ~/.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/
Install the "aws-agentic-ai" agent skill from https://github.com/CommandCodeAI/agent-skills/tree/main/skills/aws-agentic-ai into .claude/skills/aws-agentic-ai/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aws-agentic-ai", 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 install https://github.com/CommandCodeAI/agent-skills/tree/main/skills/aws-agentic-aiType 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.
$ npx skills add CommandCodeAI/agent-skills --skill aws-agentic-ai -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install CommandCodeAI/agent-skills aws-agentic-ai --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/CommandCodeAI/agent-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/aws-agentic-ai .agents/skills/aws-agentic-ai && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "aws-agentic-ai" agent skill from https://github.com/CommandCodeAI/agent-skills/tree/main/skills/aws-agentic-ai into .agents/skills/aws-agentic-ai/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aws-agentic-ai", 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.
$ npx skills add CommandCodeAI/agent-skills --skill aws-agentic-ai -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install CommandCodeAI/agent-skills aws-agentic-ai --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/CommandCodeAI/agent-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/aws-agentic-ai .cursor/skills/aws-agentic-ai && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "aws-agentic-ai" agent skill from https://github.com/CommandCodeAI/agent-skills/tree/main/skills/aws-agentic-ai into .cursor/skills/aws-agentic-ai/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aws-agentic-ai", 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 https://github.com/CommandCodeAI/agent-skills.git --path skills/aws-agentic-ai--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add CommandCodeAI/agent-skills --skill aws-agentic-ai -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install CommandCodeAI/agent-skills aws-agentic-ai --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/CommandCodeAI/agent-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/aws-agentic-ai .gemini/skills/aws-agentic-ai && rm -rf skills-srcUse ~/.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/
Install the "aws-agentic-ai" agent skill from https://github.com/CommandCodeAI/agent-skills/tree/main/skills/aws-agentic-ai into .gemini/skills/aws-agentic-ai/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aws-agentic-ai", 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.
$ gh skill install CommandCodeAI/agent-skills aws-agentic-aiInstalls 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).
$ npx skills add CommandCodeAI/agent-skills --skill aws-agentic-ai -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/CommandCodeAI/agent-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/aws-agentic-ai .github/skills/aws-agentic-ai && rm -rf skills-srcUse ~/.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/
Install the "aws-agentic-ai" agent skill from https://github.com/CommandCodeAI/agent-skills/tree/main/skills/aws-agentic-ai into .github/skills/aws-agentic-ai/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aws-agentic-ai", 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.
$ npx skills add CommandCodeAI/agent-skills --skill aws-agentic-ai -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install CommandCodeAI/agent-skills aws-agentic-ai --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/CommandCodeAI/agent-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/aws-agentic-ai .opencode/skills/aws-agentic-ai && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "aws-agentic-ai" agent skill from https://github.com/CommandCodeAI/agent-skills/tree/main/skills/aws-agentic-ai into .opencode/skills/aws-agentic-ai/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aws-agentic-ai", 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.
aws-agentic-aiAWS Bedrock AgentCore comprehensive expert for deploying and managing all AgentCore services.
AWS Agentic AI is an agent skill from CommandCodeAI/agent-skills. 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.
Its SKILL.md is about 1.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 21 other files (for example `cross-service/credential-management.md`, `services/browser/README.md` and `services/code-interpreter/README.md`).
It sits in DevOps & Cloud, covering MCP servers. It works with Amazon Web Services, Model Context Protocol and Amazon Bedrock. The repository describes itself as: A curated list of awesome Skills, resources, and tools for customizing coding agent workflows. The licence is MIT.
2 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit f490dd9. It shows what the files ask for, not the result of running them.
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.
Ships script files (Shell, from the files we listed), which the agent can run.
From the folder's file list and the shell code blocks in SKILL.md.
Links to these hosts (documentation or services it may open):
docs.aws.amazon.comawscli.amazonaws.comFrom URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
AWS Agentic AI loads about 1.5k tokens when it runs. Until then it costs about 83 tokens; SKILL.md has 498 words of instructions outside code blocks.
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.
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); files beside SKILL.md are not scanned.
The full file from CommandCodeAI/agent-skills at commit f490dd9, republished under its MIT licence (© CommandCodeAI). 498 words, ~1,531 tokens.
.claude/skills/aws-agentic-ai/SKILL.md (or your agent's skills folder). This skill also uses 13 other files; get the full folder from GitHub.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.
CRITICAL: This skill requires AWS MCP tools for accurate, up-to-date AWS information.
Always verify using AWS MCP tools (if available):
mcp__aws-mcp__aws___search_documentation or mcp__*awsdocs*__aws___search_documentation - Search AWS docsmcp__aws-mcp__aws___read_documentation or mcp__*awsdocs*__aws___read_documentation - Read specific pagesmcp__aws-mcp__aws___get_regional_availability - Check service availabilityIf AWS MCP tools are unavailable:
Use this skill when you need to:
| Service | Use For | Documentation |
|---|---|---|
| Gateway | Converting REST APIs to MCP tools | services/gateway/README.md |
| Runtime | Deploying and scaling agents | services/runtime/README.md |
| Memory | Managing conversation state | services/memory/README.md |
| Identity | Credential and access management | services/identity/README.md |
| Code Interpreter | Secure code execution in sandboxes | services/code-interpreter/README.md |
| Browser | Web automation and scraping | services/browser/README.md |
| Observability | Tracing and monitoring | services/observability/README.md |
MANDATORY - READ DETAILED DOCUMENTATION: See services/gateway/README.md for complete Gateway setup guide including deployment strategies, troubleshooting, and IAM configuration.
Quick Workflow:
Note: Credential provider is only needed for API key authentication. Lambda targets use IAM roles, and MCP servers use OAuth.
MANDATORY - READ DETAILED DOCUMENTATION: See cross-service/credential-management.md for unified credential management patterns across all services.
Quick Workflow:
MANDATORY - READ DETAILED DOCUMENTATION: See services/observability/README.md for comprehensive monitoring setup.
Quick Workflow:
For detailed documentation on each AgentCore service, see the following resources:
services/gateway/README.mdservices/gateway/deployment-strategies.mdservices/gateway/troubleshooting-guide.mdEach service has comprehensive documentation in its respective directory:
services/runtime/README.mdservices/memory/README.mdservices/identity/README.mdservices/code-interpreter/README.mdservices/browser/README.mdservices/observability/README.mdFor patterns and best practices that span multiple AgentCore services:
cross-service/credential-management.md - Unified credential patterns, security practices, rotation procedures© CommandCodeAI, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 13 other files in skills/aws-agentic-ai of CommandCodeAI/agent-skills.
Open the folder on GitHubat commit f490dd9
AWS Agentic AI 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| AWS Agentic AI this skillCommandCodeAI/agent-skills | 132 | — | ~1.5k | Automated safety check: Pass | MIT | |
| Hcls Deploy Agentaws-samples/amazon-bedrock-agents-healthcare-lifesciences | 274 | — | ~813 | Automated safety check: Pass | MIT-0 | |
| AWS Strands Agents Agentcoresammcj/agentic-coding | 162 | — | ~3k | Automated safety check: Pass | Apache-2.0 | |
| AWS Agentic AIzxkane/aws-skills | 367 | — | ~2.5k | Automated safety check: Pass | MIT | |
| AWS Cdk Developmentsickn33/agentic-awesome-skills | 47k | 1 repos | ~2.5k | Automated safety check: Pass | MIT | |
| AWS Cdk Developmentzxkane/aws-skills | 367 | 2 repos | ~2.5k | Automated safety check: Pass | MIT |
aws-samples/amazon-bedrock-agents-healthcare-lifesciences
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…
sammcj/agentic-coding
A skill your agent uses when working with AWS Strands Agents SDK or Amazon Bedrock AgentCore platform for building AI agents.
zxkane/aws-skills
AWS Bedrock AgentCore comprehensive expert for deploying and managing AI agents at scale.
sickn33/agentic-awesome-skills
AWS Cloud Development Kit (CDK) expert for building cloud infrastructure with TypeScript/Python.
zxkane/aws-skills
AWS Cloud Development Kit (CDK) expert for building cloud infrastructure with TypeScript/Python.
aws-samples/appmod-blueprints
Advisory guidance for Amazon EKS architecture and configuration decisions — compute strategy, networking, security, reliability, cost, autoscaling, observability, multi-tenancy, and upgrade planning.
CommandCodeAI/agent-skills
Builds AI agents on Cloudflare using the Agents SDK with state management, real-time WebSockets, scheduled tasks, tool integration, and chat capabilities.
CommandCodeAI/agent-skills
Download YouTube video transcripts when user provides a YouTube URL or asks to download/get/fetch a transcript from YouTube.
CommandCodeAI/agent-skills
Builds remote MCP (Model Context Protocol) servers on Cloudflare Workers with tools, OAuth authentication, and production deployment.
CommandCodeAI/agent-skills
Greet user with a specific message when they say they're new or ask for a welcome message.
Categories
AWS Bedrock AgentCore comprehensive expert for deploying and managing all AgentCore services. AWS Agentic AI is an agent skill from CommandCodeAI/agent-skills. AWS Bedrock AgentCore comprehensive expert for deploying and managing all AgentCore services.
AWS Agentic AI fits situations like: working with Gateway; any AgentCore component.
Run `npx skills add CommandCodeAI/agent-skills --skill aws-agentic-ai -a claude-code`. Or copy the skill folder (skills/aws-agentic-ai in CommandCodeAI/agent-skills) into .claude/skills/aws-agentic-ai in your project. Claude Code loads it when a task matches its description.
Run `npx skills add CommandCodeAI/agent-skills --skill aws-agentic-ai -a codex`. Or copy the skill folder (skills/aws-agentic-ai in CommandCodeAI/agent-skills) into .agents/skills/aws-agentic-ai in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add CommandCodeAI/agent-skills --skill aws-agentic-ai -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/aws-agentic-ai, .gemini/skills/aws-agentic-ai, .github/skills/aws-agentic-ai and .opencode/skills/aws-agentic-ai in your project.
Going by SKILL.md and its folder, AWS Agentic AI needs a shell for the scripts in its folder. Our summary lists: A Bash shell.
SKILL.md names 2 domains. As links in the text: docs.aws.amazon.com and awscli.amazonaws.com. This is read from the text; nothing was executed.
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. Review the folder before installing.
AWS Agentic AI is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 1.5k tokens (SKILL.md is roughly 6.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with AWS Agentic AI: Hcls Deploy Agent (aws-samples/amazon-bedrock-agents-healthcare-lifesciences, 274 stars), AWS Strands Agents Agentcore (sammcj/agentic-coding, 162 stars), AWS Agentic AI (zxkane/aws-skills, 367 stars) and AWS Cdk Development (sickn33/agentic-awesome-skills, 47k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
CommandCodeAI (a GitHub organization) maintains it in CommandCodeAI/agent-skills, which has 132 GitHub stars. The repository holds 5 skills in this directory. The repository was last updated on March 10, 2026.
Source: CommandCodeAI/agent-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.
