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 simqn-networkgit 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/simqn-network)<a href="https://agentmods.dev/skills/xi-zhao/openquantum/simqn-network"><img src="https://agentmods.dev/badge/skills/xi-zhao/openquantum/simqn-network/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/simqn-network"><img src="https://agentmods.dev/badge/skills/xi-zhao/openquantum/simqn-network.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 | $0.00044 | $0.00736 |
| Opus 5.5 | $0.00018 | $0.00294 |
| Sonnet 5.5 | $0.00009 | $0.00147 |
| Haiku 4.5 | $0.00004 | $0.00074 |
Grade A, and why
simqn-network 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
SimQN 量子链路
原生 SDK 路径
本能力同时支持 SimQN 的原生公开 API。用户需要 拓扑、节点、信道、存储、事件与自定义协议 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 simqn-network 定位环境，按完整 SDK 工作流执行。模块导航：qns；导航不是 API 白名单。
上游 GPL 许可；保持独立进程，不改变现有 MCP 默认关闭状态。
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。
Agent 经 Harness 调用 simqn_local 的 simulate_simqn_link，比较不同链路参数下的到达次数、到达时间和保真度。这里的 network 是仿真的量子网络，不会访问互联网。
输入 attempts 次独立发送，时间间隔 intervalSeconds、固定传播延迟 delaySeconds，长度 lengthMeters，随机丢失概率 dropProbability，以及 Werner 态初始 initialFidelity。decoherencePerMeter 是每米衰减率；SDK 用 w=(4F-1)/3、w'=w exp(-rate*length) 计算保真度。延迟没有额外加入存储退相干。timeSlotsPerSecond 控制离散时间精度，SDK 向下量化时间；seed 使用 NumPy RandomState 可表示的 32 位无符号整数。
Tool 返回 received、dropped 和逐到达记录；全丢失时 arrivals=[]。这是无限带宽、无排队的独立单链路模型，不包含中继交换、量子存储、路由、BB84 协商或密钥生成。分析丢失时使用多次试验，不能把单次采样比率当成保证值。
固定 SimQN/qns 0.2.3，GPL-3.0，连接默认关闭、由用户自行确认许可并启用。先显式准备 node scripts/setup-paper-tools.mjs simqn-network；Python 3.12 的独立环境及依赖由锁文件确定。SDK 可能写本地缓存，最大副作用为 workspace-write；计算不安装依赖、不使用凭据、不连接服务。
调用方选择试验规模，部署限制用独立的 execution 控制。当前 L1，scientificValidation=not_evaluated；数值与集成测试是开发证据，不等于科学验收。
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 · +13 lines ef0e50cd12d9
- 18d ago First seen · 17 lines · 44 tokens per session scan A ff0724cd83d0
simqn-network is a skill published in the GitHub repository xi-zhao/OpenQuantum (75 stars, last pushed yesterday), licensed MIT. It adds 44 tokens to every session and 736 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 2026-09-29.
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