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qiskit

8.3

by K-Dense-AI

173Favorites
395Upvotes
0Downvotes

IBM quantum computing framework. Use when targeting IBM Quantum hardware, working with Qiskit Runtime for production workloads, or needing IBM optimization tools. Best for IBM hardware execution, quantum error mitigation, and enterprise quantum computing. For Google hardware use cirq; for gradient-based quantum ML use pennylane; for open quantum system simulations use qutip.

quantum

8.3

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Quick Review

Excellent quantum computing skill with comprehensive coverage of Qiskit framework. The SKILL.md provides crystal-clear descriptions enabling CLI agents to invoke capabilities confidently, with a well-organized decision guide mapping user needs to specific reference files. Structure is exemplary: concise main file with detailed knowledge properly segregated into 8 specialized reference documents covering setup, circuits, primitives, transpilation, visualization, backends, patterns, and algorithms. Task knowledge is outstanding with complete workflows, code examples, and best practices for both simulator and hardware execution. Novelty is strong—quantum computing workflows involve complex transpilation, backend selection, error mitigation, and multi-step optimization that would consume many tokens and require specialized knowledge beyond a general CLI agent's capabilities. The skill meaningfully reduces cost for IBM quantum hardware targeting, variational algorithms, and production quantum workloads. Minor consideration: while highly specialized, quantum computing itself is a niche domain, though this is the intended use case. Overall, this is a production-ready skill that dramatically simplifies quantum computing tasks.

LLM Signals

Description coverage9
Task knowledge10
Structure10
Novelty8

GitHub Signals

6,871
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3
Last commit 1 days ago

Publisher

K-Dense-AI

K-Dense-AI

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K-Dense-AI

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