braket-executor

Amazon Braket integration skill for multi-vendor quantum hardware access and hybrid workflows

509 stars

Best use case

braket-executor is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Amazon Braket integration skill for multi-vendor quantum hardware access and hybrid workflows

Teams using braket-executor should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/braket-executor/SKILL.md --create-dirs "https://raw.githubusercontent.com/a5c-ai/babysitter/main/library/specializations/domains/science/quantum-computing/skills/braket-executor/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/braket-executor/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How braket-executor Compares

Feature / Agentbraket-executorStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Amazon Braket integration skill for multi-vendor quantum hardware access and hybrid workflows

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# Braket Executor

## Purpose

Provides expert guidance on executing quantum circuits across multiple hardware vendors using Amazon Braket, enabling hybrid quantum-classical workflows in the AWS ecosystem.

## Capabilities

- Circuit execution on IonQ, Rigetti, OQC hardware
- Hybrid job execution with classical processing
- Quantum annealing on D-Wave
- Local simulator execution
- Cost estimation and job management
- Result storage in S3
- Batch job submission
- Noise simulation

## Usage Guidelines

1. **Device Selection**: Choose appropriate hardware based on circuit requirements and availability
2. **Circuit Translation**: Use Braket SDK to build or import circuits from other frameworks
3. **Hybrid Jobs**: Configure containerized hybrid workflows with classical compute
4. **Cost Management**: Monitor and estimate costs before job submission
5. **Result Retrieval**: Access results from S3 with proper error handling

## Tools/Libraries

- Amazon Braket SDK
- AWS Lambda
- Amazon S3
- Braket Hybrid Jobs
- Braket Local Simulator

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