Cloudbase Agent Python
TencentCloudBase/CloudBase-AI-Toolkit
Build production-ready AI agent backends using the CloudBase Agent Python SDK — create agents with LangGraph/CrewAI/LlamaIndex, serve them via FastAPI with AG-UI protocol streaming +…
Build a new AI agent on AWS and deploy it easily, OR wrap and deploy an agent you already have, using the Amazon Bedrock AgentCore harness.
Install AWS Harness
$ npx skills add hoodini/ai-agents-skills --skill aws-harness -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install hoodini/ai-agents-skills aws-harness --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/hoodini/ai-agents-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/aws-harness .claude/skills/aws-harness && 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-harness" agent skill from https://github.com/hoodini/ai-agents-skills/tree/master/skills/aws-harness into .claude/skills/aws-harness/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aws-harness", 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/hoodini/ai-agents-skills/tree/master/skills/aws-harnessType 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 hoodini/ai-agents-skills --skill aws-harness -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install hoodini/ai-agents-skills aws-harness --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/hoodini/ai-agents-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/aws-harness .agents/skills/aws-harness && 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-harness" agent skill from https://github.com/hoodini/ai-agents-skills/tree/master/skills/aws-harness into .agents/skills/aws-harness/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aws-harness", 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 hoodini/ai-agents-skills --skill aws-harness -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install hoodini/ai-agents-skills aws-harness --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/hoodini/ai-agents-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/aws-harness .cursor/skills/aws-harness && 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-harness" agent skill from https://github.com/hoodini/ai-agents-skills/tree/master/skills/aws-harness into .cursor/skills/aws-harness/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aws-harness", 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/hoodini/ai-agents-skills.git --path skills/aws-harness--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 hoodini/ai-agents-skills --skill aws-harness -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install hoodini/ai-agents-skills aws-harness --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/hoodini/ai-agents-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/aws-harness .gemini/skills/aws-harness && 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-harness" agent skill from https://github.com/hoodini/ai-agents-skills/tree/master/skills/aws-harness into .gemini/skills/aws-harness/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aws-harness", 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 hoodini/ai-agents-skills aws-harnessInstalls 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 hoodini/ai-agents-skills --skill aws-harness -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/hoodini/ai-agents-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/aws-harness .github/skills/aws-harness && 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-harness" agent skill from https://github.com/hoodini/ai-agents-skills/tree/master/skills/aws-harness into .github/skills/aws-harness/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aws-harness", 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 hoodini/ai-agents-skills --skill aws-harness -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install hoodini/ai-agents-skills aws-harness --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/hoodini/ai-agents-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/aws-harness .opencode/skills/aws-harness && 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-harness" agent skill from https://github.com/hoodini/ai-agents-skills/tree/master/skills/aws-harness into .opencode/skills/aws-harness/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aws-harness", 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
aws-harness- GitHub stars
- 282
- Token cost
- ~4.2k tokens
- SKILL.md length
- 1,157 words
- Files
- 1
- Skills in repo
- 32
- Repo updated
- First seen
- Licence
- None found
At a glance
Build a new AI agent on AWS and deploy it easily, OR wrap and deploy an agent you already have, using the Amazon Bedrock AgentCore harness.
- Works in 8 steps: Install → Create the project → The agent code (this is all an AgentCore… → …
- The goal is to create
- SKILL.md covers What "harness" means (read…, Which path are you on?, Prerequisites and Path A - Build and deploy a…, plus 3 more sections
- Calls pip, docker and aws
What it does
AWS Harness is an agent skill from hoodini/ai-agents-skills. Build a new AI agent on AWS and deploy it easily, OR wrap and deploy an agent you already have, using the Amazon Bedrock AgentCore harness. Explains what an "agent harness" is (the runtime scaffolding around a model - agent loop, tool execution, memory, identity, observability), then gives two fully-working, verified paths - (A) scaffold + ship a new agent with the AgentCore CLI (create/dev/deploy/invoke), and (B) deploy a prepared agent (Strands, LangGraph, or custom) via the SDK wrapper or a FastAPI + Docker +…
Its SKILL.md is about 4.2k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Backend & APIs, covering Project scaffolding, Serverless and Building AI agents. It works with Amazon Web Services, Amazon Bedrock, LangGraph and Docker. The repository describes itself as: 🧠 AI Agent Skills Repository - A curated collection of specialized skills for AI coding agents (Claude Code, GitHub Copilot, Cursor, Windsurf). Created by Yuval Avidani using…
When your agent uses it
- The goal is to create
- Deploy an agent on AWS AgentCore
- Agentcore create
- Agentcore deploy
Example prompts
- “agent harness”
- “/aws-harness”
Requirements
- Python 3
- Node.js
- Docker
Workflow steps
8 steps, taken from the step headings in SKILL.md.
- Install
- Create the project
- The agent code (this is all an AgentCore agent is)
- Test locally (free) before deploying
- Deploy to AWS
- Invoke
- Add production harness components
- Clean up (do NOT skip - this costs money)
What it can do on your machine
Read from SKILL.md and the folder at commit f7a43d8. 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
Shell commands in SKILL.md call:
pipdockerawsnpmuv
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.comdocs.aws.amazon.comstrandsagents.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
AWS Harness loads about 4.2k tokens when it runs. Until then it costs about 220 tokens; SKILL.md has 1,157 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.
Safety
Auto-check: notes
The automated check noted patterns worth knowing about, such as sudo or a known installer.
- NoteMentions a .env fileSKILL.md:99
.env.local # local secrets (gitignored)
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.
SKILL.md
Without a licence we can't republish the file, so here is its outline and opening line. It has 1,157 words (~4,207 tokens).
“Take an AI agent from an empty folder - or from code you already have - to a live, serverless endpoint on AWS. Every command and import below is verified against official docs (sources at the bottom).”
- name
- aws-harness
Files
Just SKILL.md in skills/aws-harness of hoodini/ai-agents-skills.
Open the folder on GitHubat commit f7a43d8
Compare with similar skills
AWS Harness 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 Harness this skillhoodini/ai-agents-skills | 282 | — | ~4.2k | Automated safety check: Notes | None | |
| Cloudbase Agent PythonTencentCloudBase/CloudBase-AI-Toolkit | 1.1k | 2 repos | ~2.9k | Automated safety check: Notes | MIT | |
| Agents Get Startedaws/agent-toolkit-for-aws | 2.8k | — | ~4.3k | Automated safety check: Notes | Apache-2.0 | |
| CloudbaseTencentCloudBase/CloudBase-AI-Toolkit | 1.1k | 1 repos | ~4.8k | Automated safety check: Pass | MIT | |
| Edgeone Makers ToolsTencentEdgeOne/edgeone-makers-tools | 1.9k | 1 repos | ~646 | Automated safety check: Pass | MIT | |
| Flowfile Debugging PlaybookEdwardvaneechoud/Flowfile | 385 | — | ~6.3k | Automated safety check: Pass | MIT |
Similar skills
- Official
Agents Get Started
aws/agent-toolkit-for-aws
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Cloudbase
TencentCloudBase/CloudBase-AI-Toolkit
A skill your agent uses when you develop, design, build, deploy, debug, migrate, or troubleshoot CloudBase (腾讯云开发, 云开发, TCB, 微信云开发) projects — Web, 微信小程序, 小程序, uni-app, mobile (iOS, Android…
Edgeone Makers Tools
TencentEdgeOne/edgeone-makers-tools
EdgeOne Makers platform development router — the single entry point for building, storing data, and deploying on Tencent EdgeOne Makers.
Flowfile Debugging Playbook
Edwardvaneechoud/Flowfile
Symptom-to-cause triage playbook for Flowfile (core/worker/kernel/frontend/AI) — covers "no such table" DB cascades (two distinct causes), import-time Alembic migration corruption, silent…
Add Component
lbedner/aegis-stack
A skill your agent uses when adding a new infrastructure component (worker, scheduler, database, redis, ingress, observability) to the Aegis Stack framework itself, or adding a new variant axis…
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Related
Questions about AWS Harness
What does AWS Harness do?
Build a new AI agent on AWS and deploy it easily, OR wrap and deploy an agent you already have, using the Amazon Bedrock AgentCore harness. AWS Harness is an agent skill from hoodini/ai-agents-skills. Build a new AI agent on AWS and deploy it easily, OR wrap and deploy an agent you already have, using the Amazon Bedrock AgentCore harness.
When should I use AWS Harness?
AWS Harness fits situations like: the goal is to create; deploy an agent on AWS AgentCore; agentcore create; agentcore deploy.
How do I install AWS Harness in Claude Code?
Run `npx skills add hoodini/ai-agents-skills --skill aws-harness -a claude-code`. Or copy the skill folder (skills/aws-harness in hoodini/ai-agents-skills) into .claude/skills/aws-harness in your project. Claude Code loads it when a task matches its description.
How do I install AWS Harness in Codex?
Run `npx skills add hoodini/ai-agents-skills --skill aws-harness -a codex`. Or copy the skill folder (skills/aws-harness in hoodini/ai-agents-skills) into .agents/skills/aws-harness in your project. Codex loads it when a task matches its description.
Can I use AWS Harness 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 hoodini/ai-agents-skills --skill aws-harness -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-harness, .gemini/skills/aws-harness, .github/skills/aws-harness and .opencode/skills/aws-harness in your project.
What does AWS Harness need to run?
Going by SKILL.md and its folder, AWS Harness needs the command-line tools its instructions call (pip, docker, aws, npm and uv). Our summary lists: Python 3; Node.js; Docker.
Does AWS Harness access the network?
SKILL.md names 3 domains. As links in the text: github.com, docs.aws.amazon.com and strandsagents.com. This is read from the text; nothing was executed.
Is AWS Harness safe to install?
Our automated static check of SKILL.md found notes only (mentions a .env file), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.
What licence does AWS Harness use?
No licence was found for AWS Harness or its repository. Without one, default copyright applies: ask the author before reusing or redistributing it.
How many tokens does AWS Harness use?
About 4.2k tokens (SKILL.md is roughly 17k 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 AWS Harness?
Skills that share tags, products or a category with AWS Harness: Cloudbase Agent Python (TencentCloudBase/CloudBase-AI-Toolkit, 1.1k stars), Agents Get Started (aws/agent-toolkit-for-aws, 2.8k stars), Cloudbase (TencentCloudBase/CloudBase-AI-Toolkit, 1.1k stars) and Edgeone Makers Tools (TencentEdgeOne/edgeone-makers-tools, 1.9k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains AWS Harness?
hoodini (a GitHub user) maintains it in hoodini/ai-agents-skills, which has 282 GitHub stars. The repository holds 32 skills in this directory. The repository was last updated on July 11, 2026.
Source: hoodini/ai-agents-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.