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 mindquantum-differentiablegit 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/mindquantum-differentiable)<a href="https://agentmods.dev/skills/xi-zhao/openquantum/mindquantum-differentiable"><img src="https://agentmods.dev/badge/skills/xi-zhao/openquantum/mindquantum-differentiable/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/mindquantum-differentiable"><img src="https://agentmods.dev/badge/skills/xi-zhao/openquantum/mindquantum-differentiable.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 | $0.00051 | $0.01100 |
| Opus 5.5 | $0.00020 | $0.00440 |
| Sonnet 5.5 | $0.00010 | $0.00220 |
| Haiku 4.5 | $0.00005 | $0.00110 |
Grade A, and why
mindquantum-differentiable 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.
How it starts
The opening of the file, as written. The whole thing — 32 lines — stays where its author put it; the contents beside it link to each section on GitHub.
MindQuantum 可微分量子线路
原生 SDK 路径
本能力同时支持 MindQuantum 的原生公开 API。用户需要 Circuit、算符、ansatz、模拟器、测量与梯度接口 时，由 Agent 在固定依赖环境中编写和运行任务代码，不限于下文便捷 Tool 的预设模型。
使用 node scripts/sdk-access.mjs inspect mindquantum-differentiable 定位环境，按完整 SDK 工作流执行。模块导航：mindquantum；导航不是 API 白名单。
下文关于模型、门集、输入与预算的限制描述便捷 Tool 的合同；原生 SDK 另受上游版本、可选依赖、宿主资源与用户授权约束。已禁用或被拒绝的动作不能借代码路径绕过。执行状态和科研验收分别报告。
当用户需要用 MindQuantum 计算线路期望、验证变分线路导数或与其他 SDK 交叉对照时，Agent 经 Harness 调用 mindquantum_local 提供的 differentiate_mindquantum_circuit。本 Skill 指导参数选择与结果解释；计算由 mqvector + adjoint gradient 完成。
numQubits与gates定义全零初态的理想酉线路。支持 H、X、Y、Z、S、T、RX、RY、RZ、CX、CZ、SWAP；双比特门的 targets 为[control,target]（SWAP 为两个交换位），角度单位 rad。observables是与量子位数同长的 I/X/Y/Z 字符串，最左字符对应 q0。例如ZI表示 Z0，XY表示 X0Y1；输出期望保留输入顺序。加权 Hamiltonian 可由调用方按系数组合期望和 Jacobian，勿把 Pauli words 当作系数。trainableGateIndices明确选择 gates 数组中需要求导的 RX/RY/RZ；每项是独立参数。可填空数组只做仿真。Jacobian 行对应 observables，列严格对应该索引数组的顺序，不是所有旋转门的隐含顺序。amplitudes[k]为[real,imag]，概率向量按 q0 在最左的二进制字典序排列。返回 SDK 原始数值，不裁剪、不归一化；stateNormSquared用来检查数值漂移。这些是精确线路仿真的数值期望，不是 finite-shots 频数。- 参数数量、量子位数和门数由调用方决定；完整输出按 2^N 增长，可寻址数组表示限制仍适用。资源预算通过独立
execution参数设置，不改变线路语义。 - OpenQuantum Harness 对大结果自动返回
openquantum-science-summary：先查看summary.result中的期望、Jacobian、范数与单位；需要完整态矢量时，用已有文件或 shell Tool 读取会话工作区内的fullResult.path，再取 JSON 的result.amplitudes/result.probabilities。omitted: true表示数据保存在文件中，不表示零值或计算缺失；不要为了获取被省略的数据重新计算。保存失败时仍返回完整输出，科学状态保持not_evaluated。 - MindQuantum 0.12.0 使用 Python 3.11；本工具将上游 q0 为最低位的态向量转换为统一的 q0 最左顺序。
- 梯度仅对当前输入的理想线路有效，不自动构成优化收敛、抗噪声能力或硬件优势结论。对复杂电路先选择解析可核对例子，必要时与第二 SDK、参数移位或有限差分对照。
- 当前是 L1，
scientificValidation=not_evaluated；成功计算与数值回归不等于最终科学 Acceptance。
首次使用前显式运行 node scripts/setup-paper-tools.mjs mindquantum-differentiable 准备固定依赖。计算不会安装依赖、提交云/QPU 或读取凭据，数值库可能写本地缓存。上游许可为 Apache-2.0，详细版本锁见本目录 pyproject.toml 和 uv.lock；官方接口来源。
What ships with it
6 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · +11 lines c333335e5bde
- 5d ago Changed · +1 lines 01964df6fe10
- 19d ago First seen · 20 lines · 51 tokens per session scan A 56e157c2d20f
mindquantum-differentiable is a skill published in the GitHub repository xi-zhao/OpenQuantum (75 stars, last pushed yesterday), licensed MIT. It adds 51 tokens to every session and 1,100 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 2026-09-28.
Other skills, from other repositories
academic-research
Search academic papers, scholarly articles, and research publications through SandBase. Use when asked for literature review, academic citations, scholarly research, paper discovery, or scientific evidence gathering.
rhylthyme
Schedule multi-step procedures that a person carries out against a clock, with parallel tracks, shared equipment and steps that end when the person says so. Use when turning a lab protocol, recipe, event run sheet or workout into a timed plan; when several procedures must share one instrument (one centrifuge, one…
memory-search-mcp
Long-term memory and context retrieval for AI agents. Semantic search across conversation history with care-weighted relevance.
gc-minimal-zine-poster-v0-3
Generate or analyze poetic paper-texture minimal zine posters with large negative space, a small editorial collage or focal element, experimental typography, and one clear color accent. Use when the user gives a theme, sentence, article, mood, object, photo, content brief, reference images, or an image folder and…
ask-sonner
Guide to Sonner, the React toast library — install and wire up the Toaster, pick the right toast() call, promise and loading toasts, updating, dismissing and persisting toasts, styling, theming and icons, positioning and multiple toasters. Use when working with Sonner or troubleshooting it — toasts that don't appear…
kill-ai-slop
Find and remove AI slop — the generic, machine-default visual and copy tics of vibe-coded products — from a web project. Use when the user asks to "kill AI slop", "de-slop", "remove the AI look", "make this not look AI-generated", or clean up a landing page / UI / docs that feels templated. Detects and fixes the…