Backend Selector

SkillDev tools

Multi-backend comparison and selection skill for optimal hardware choice

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.

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

Then ask your AI: use the Backend Selector skill

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/backend-selector/SKILL.md and read by ahel’s review.

Purpose

Provides expert guidance on comparing and selecting quantum backends across multiple providers based on circuit requirements and performance criteria.

Capabilities

Backend capability comparison
Queue time estimation
Cost optimization
Fidelity-based ranking
Connectivity analysis
Job prioritization
Provider API integration
Historical performance tracking

Usage Guidelines

Requirements Analysis: Determine circuit qubit and gate requirements
Backend Query: Fetch available backends from all providers
Filtering: Eliminate backends that cannot support circuit
Ranking: Score backends by fidelity, queue time, and cost
Selection: Choose optimal backend for execution

Tools/Libraries

Qiskit
Amazon Braket
Cirq
Azure Quantum SDK
pytket

Signals

GitHub stars: 2k
Forks: 112
Last commit: Sep 2026

Advanced

Item type: skill
Key: backend-selector
Source: github.com/a5c-ai/babysitter

github.com/a5c-ai/babysitter