Braket Executor

SkillDev tools

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

Use Braket Executor in Claude, ChatGPT or Ahel Desktop

Free. Sign in, add Braket Executor and connect your AI. About a minute.

Claude ChatGPT Ahel Desktop

Also: Claude Code · Cursor · Codex

Then ask your AI: use the Braket Executor skill

Details

Instructions available. Your AI can read the instructions. Execution depends on the setup they require.

Account requirements not reviewed. Check the skill instructions before use; Ahel provides instructions and does not run this skill.

No other account needed.

Add Ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.

Braket ExecutorStart free

What this skill tells your AI

The instructions your AI receives, as published by a5c-ai/babysitter in library/specializations/domains/science/quantum-computing/skills/braket-executor/SKILL.md and read by Ahel’s review.

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

Device Selection: Choose appropriate hardware based on circuit requirements and availability
Circuit Translation: Use Braket SDK to build or import circuits from other frameworks
Hybrid Jobs: Configure containerized hybrid workflows with classical compute
Cost Management: Monitor and estimate costs before job submission
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

Signals

GitHub stars: 2k
Forks: 113
Last commit: Sep 2026

Advanced

Item type: skill
Key: braket-executor
Source: github.com/a5c-ai/babysitter

github.com/a5c-ai/babysitter