unitarylab/quantum-practices
Quantum Algorithms Best Practices Quantum Algorithms Best Practices
A DeepSeek Harness tool bundle for quantum algorithm best practices, adapted from unitarylab/quantum-skills. Registers one read-only quantum_practices model tool (list / search / get) over an immutable build-time catalog of 60+ packaged practice guides: primitives (Grover, QPE, amplitude amplification/estimation), linear systems, cryptography, Hamiltonian simulation, Schrodingerization, eigensolvers, gradients, quantum machine learning, state preparation, and quantum error correction — with multi-simulator guidance (UnitaryLab recommended, Qiskit, PennyLane). Progressive disclosure keeps the root skill lightweight; guides load only when needed. Education-friendly for concept explanation, circuit design, code review, and demos.
Install
npx @deepseek-ai/dsh@0.1.0-rc.6 plugin --profile web add github:unitarylab/quantum-practices#mainGitHub install per README (English section): npx @deepseek-ai/dsh@0.1.0-rc.6 plugin --profile web add github:unitarylab/quantum-practices#main, then restart DeepSeek Harness Web. Headless: same command with --profile headless. Local dev: clone and npx @deepseek-ai/dsh@0.1.0-rc.6 plugin --profile web add <checkout-path>.
Compatibility
DeepSeek Harness web / headless profiles (npx @deepseek-ai/dsh 0.1.0-rc.6). Read-only plugin — no network, subprocess, filesystem writes, Python execution, credentials, or native code.
Details
- Repo: unitarylab/quantum-practices
- Category: Other
- Stars: 18
- Version: GitHub source (build-time catalog; no npm package)
- Last push: 2026-08-14
- First seen: 2026-08-14
Recent updates
read-only quantum_practices tool; 60+ guide catalog; progressive disclosure; multi-simulator selection rules; GitHub-sourced corpus; zero runtime side effects.
FAQ
- Does it run quantum code?
- No — it is read-only: list, search and read practice guides. Simulator selection and installation are covered by bundled guides, not executed.
- Which simulators does it cover?
- UnitaryLab (recommended), Qiskit, and PennyLane, with explicit selection rules in the guides.
- Where does the content come from?
- The corpus is adapted from the public unitarylab/quantum-skills project and synced from GitHub only.
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