Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add xi-zhao/OpenQuantum --skill quantum-guide-algorithms-quantum-machine-learninggit clone --depth 1 https://github.com/xi-zhao/OpenQuantumWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/xi-zhao/openquantum/quantum-guide-algorithms-quantum-machine-learning)<a href="https://agentmods.dev/skills/xi-zhao/openquantum/quantum-guide-algorithms-quantum-machine-learning"><img src="https://agentmods.dev/badge/skills/xi-zhao/openquantum/quantum-guide-algorithms-quantum-machine-learning/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/xi-zhao/openquantum/quantum-guide-algorithms-quantum-machine-learning"><img src="https://agentmods.dev/badge/skills/xi-zhao/openquantum/quantum-guide-algorithms-quantum-machine-learning.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00041 | $0.00843 |
| Opus 5.5 | $0.00016 | $0.00337 |
| Sonnet 5.5 | $0.00008 | $0.00169 |
| Haiku 4.5 | $0.00004 | $0.00084 |
Grade A, and why
quantum-guide-algorithms-quantum-machine-learning scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
algorithms/quantum-machine-learning
本地开源适配。上游指南 ID：algorithms/quantum-machine-learning。
分类导航：保留用户显式调用；自动任务直接选择叶子方法 Skill，或使用 quantum-algorithms 查找。
选择工作流
按用户的数学问题、输入表示、计算规模和需要的输出选择一个叶子 Skill。知识解释可直接使用原理；计算任务加载叶子 Skill，使用其中的开源实现和现有代码执行 Tool。无需为阅读指南启动额外服务。
- quantum-cvqnn：两模有限 Fock 空间的位移、压缩、旋转、Kerr 和分束器层；SciPy 有限差分优化替换 Torch autograd，需增加 cutoff 检查截断。
- quantum-fermi-hubbard-vqe：开放边界 Hubbard 链，Jordan-Wigner 与全 Fock 空间 VQE；粒子数是测量值，未强制固定粒子数扇区。
- quantum-ising：开放边界二维矩形 Ising 网格，quimb MPS 与二阶 Strang 演化；报告键维数及截断参数，不分配完整态矢量。
- quantum-qaoa：无权 MaxCut 的交替 cost/mixer 电路与参数优化；输出平均 cut 和最高概率位串。
- quantum-qcbm：参数电路 Born 分布拟合目标概率，KL 目标与 total variation 对照。
- quantum-vqc：RY 特征编码与参数电路二分类；输出训练集指标，不能当作泛化效果。
- quantum-vqe：实 Pauli Hamiltonian、RY/RZ/CX ansatz 和 SciPy 优化；能量、优化记录及保留的参数可复查。
全量条目见覆盖表。如果用户描述跨领域，按实际依赖组合相关叶子 Skill；不要要求用户先阅读整条目录链。
来源与边界
上游 MIT 指南：algorithms/quantum-machine-learning。原文作为参考保存在固定检索库，本文件将执行路线改为开源 SDK。来源摘要和算法模块对应关系见coverage.json，许可证与改动说明见NOTICE。
自定义 SDK 程序
示例用于解释和接口核验，不是可执行任务的边界。用户需要其他模型、数据、算法步骤、梯度或后端时，按原生 SDK 工作台在固定环境中编写并执行自定义代码；由 Agent 完成程序与工件交付。使用 quantum-algorithms 环境定位相关 SDK，保留本算法的数学假设与数值误差说明。
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 4d ago Changed · +4 lines 6226f9a3d3b2
- 22d ago First seen · 31 lines · 41 tokens per session scan A 38892262715b
quantum-guide-algorithms-quantum-machine-learning is a skill published in the GitHub repository xi-zhao/OpenQuantum (75 stars, last pushed yesterday), licensed MIT. It adds 41 tokens to every session and 843 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-25.
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