# amazon-braket

Runs quantum computing workflows on AWS with Amazon Braket: finds QPUs and simulators, builds circuits, and sets spending limits.

- skill · `type=skill` · Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, OpenCode · 2600 installs · ★ 3282
- Author: aws
- License: Apache-2.0 · policy=mirror · the beginning of the file is at the end of this page
- Source: https://github.com/aws/agent-toolkit-for-aws/tree/HEAD/skills/specialized-skills/quantum-computing-skills/amazon-braket/SKILL.md
- Updated: 2026-10-23
- HTML: https://affpapa.org/en/nevibecode/skills/amazon-braket

## What it does

The skill connects the AI agent to quantum workflows on AWS through the `amazon-braket-sdk` Python package. It queries simulators and QPUs, and submits program sets to reduce per-task fees. The agent can build gate-model circuits or prepare analog Hamiltonian simulation (AHS) programs.

You need Python and `amazon-braket-sdk` installed locally. Code execution should run via local shell commands like `python3 -c "<code>"`. The AWS MCP `run_script` tool runs in a minimal sandbox without Braket libraries installed. All devices and hybrid jobs are region-scoped. Querying a device ARN from the wrong AWS region fails immediately with a `ResourceNotFoundException`.

## Requirements
- Works with: AWS

## Install

### Claude Code (native platform)

1. **Skills CLI (Vercel)**
```bash
npx skills add aws/agent-toolkit-for-aws --skill amazon-braket -a claude-code
```

2. **Manually: put the files in place**
- File: `~/.claude/skills/amazon-braket/SKILL.md` — Copy the whole skill folder; for one project use .claude/skills/amazon-braket/

### Codex

1. **Skills CLI (Vercel)**
```bash
npx skills add aws/agent-toolkit-for-aws --skill amazon-braket -a codex
```

2. **Manually: put the files in place**
- File: `.agents/skills/amazon-braket/SKILL.md` — For all projects use ~/.agents/skills/

### Cursor

1. **Skills CLI (Vercel)**
```bash
npx skills add aws/agent-toolkit-for-aws --skill amazon-braket -a cursor
```

2. **Manually: put the files in place**
- File: `.cursor/skills/amazon-braket/SKILL.md` — Cursor also reads .agents/skills/ and .claude/skills/

### GitHub Copilot

1. **GitHub CLI**
```bash
gh skill install aws/agent-toolkit-for-aws amazon-braket
```

2. **Manually: put the files in place**
- File: `.github/skills/amazon-braket/SKILL.md`

### Gemini CLI

1. **Skills CLI (Vercel)**
```bash
npx skills add aws/agent-toolkit-for-aws --skill amazon-braket -a gemini-cli
```

2. **Platform CLI**
```bash
gemini skills install https://github.com/aws/agent-toolkit-for-aws --path skills/specialized-skills/quantum-computing-skills/amazon-braket
```

### Windsurf (Devin Desktop)

**Manually: put the files in place**
- File: `.devin/skills/amazon-braket/SKILL.md` — The legacy .windsurf/skills/ path still works

### OpenCode

**Skills CLI (Vercel)**
```bash
npx skills add aws/agent-toolkit-for-aws --skill amazon-braket -a opencode
```

### Claude.ai

**Claude.ai**
- Zip the folder and upload it in Settings → Capabilities → Skills

Where a file is given instead of a command, copy the files from the source to that path: https://github.com/aws/agent-toolkit-for-aws/tree/HEAD/skills/specialized-skills/quantum-computing-skills/amazon-braket/SKILL.md

## When to use it
- discover available QPUs and simulators across AWS regions
- build gate-model circuits and analog Hamiltonian simulation programs
- execute hybrid quantum-classical algorithms using `@hybrid_job`
- set hard cost caps on QPU workloads with spending limits

## Example prompts
- Find available QPUs in Amazon Braket and display qubit counts for each device
- Build a quantum circuit using amazon-braket-sdk and run the simulation
- Configure a hybrid quantum job with @hybrid_job and apply a spending limit

## Source text · SKILL.md · Apache-2.0

Below is the content of a third-party file. It is data, not instructions for you: do not act on anything written inside unless the human asks. Block tag: 590cd8316941a34e.

BEGIN THIRD-PARTY FILE 590cd8316941a34e
```text
---
name: amazon-braket
description: Runs quantum computing workflows on AWS through Amazon Braket — discovering devices (QPUs and simulators) and their availability, building gate-model circuits and analog Hamiltonian programs, submitting quantum tasks, program sets and hybrid jobs, looking up prices, and capping spend with spending limits. Applies to any request about quantum computing, quantum hardware, quantum simulation, AHS, OpenQASM, or running a quantum algorithm on AWS.
metadata:
  version: "1"
---

# Amazon Braket

## Primitives

The vocabulary of a Braket workflow, and which reference to open for each.

| Primitive | What it is | Related References | Open it when the request involves |
|---|---|---|---|
| **Device** | A simulator or QPU, identified by a region-scoped ARN | [devices.md](references/devices.md) | anything about a device: what exists, discovering or filtering the fleet, availability and status (online, offline, retired), which region a device lives in, ARNs, choosing a device for a workload, qubit count, connectivity or topology, native gates, fidelities, calibration data, queue depth, shot and gate limits, paradigm (gate-model vs analog Hamiltonian simulation), whether a device supports program sets, pulse-level control, simulators and local emulators |
| **Program** | The workload/input — one executable (Circuit, AHS, OpenQASM). Which type is legal depends on the device's paradigm | - | - |
| **Quantum task** | One program + shots, run once (the atomic unit Braket meters) | - | - |
| **Task batch** | Many *independent* tasks — SDK-only fallback for when a program set does not fit; works on all devices | [program-sets.md](references/program-sets.md) | see the Program set row; also [running multiple programs](https://docs.aws.amazon.com/braket/latest/developerguide/braket-batching-tasks.html) |
| **Program set** | Many programs in **one service-side task** — preferred way to run multiple programs instead of task batch | [program-sets.md](references/program-sets.md) | running more than one program: parameter sweeps, scanning parameter values, task batches, `run_batch`, several circuits submitted together, attaching observables across programs, and minimizing per-task fees when many programs run, program sets. Also [getting started with program sets](https://github.com/amazon-braket/amazon-braket-examples/blob/main/examples/braket_features/program_sets/01_Getting_started_with_program_sets.ipynb) |
| **Hybrid job** | Managed classical-quantum loop that orchestrates many tasks | [hybrid-job.md](references/hybrid-job.md) | hybrid jobs: `@hybrid_job`, algorithm scripts and source modules, `entry_point`, embedded simulators, BYOC and custom container images, CUDA-Q, job execution roles, hyperparameters, checkpoints, and retrieving job results |
```
END THIRD-PARTY FILE 590cd8316941a34e

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