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 qec-memory-experimentgit 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/qec-memory-experiment)<a href="https://agentmods.dev/skills/xi-zhao/openquantum/qec-memory-experiment"><img src="https://agentmods.dev/badge/skills/xi-zhao/openquantum/qec-memory-experiment/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/qec-memory-experiment"><img src="https://agentmods.dev/badge/skills/xi-zhao/openquantum/qec-memory-experiment.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00114 | $0.01008 |
| Opus 5.5 | $0.00046 | $0.00403 |
| Sonnet 5.5 | $0.00023 | $0.00202 |
| Haiku 4.5 | $0.00011 | $0.00101 |
Grade A, and why
qec-memory-experiment 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 9d 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
QEC Memory Experiment
原生 SDK 路径
本能力同时支持 Stim / PyMatching 的原生公开 API。用户需要 自定义 Stim 电路、detector error model、Matching 图与批量译码 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 qec-memory-experiment 定位环境，按完整 SDK 工作流执行。模块导航：stim、pymatching；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。
核心对象
核心对象是一份可重放的 surface-code memory 实验配置：basis、code distance、rounds、shots、统一物理错误率和 seed。Stim 生成并采样电路，PyMatching 从 detector error model 构建 MWPM 解码器。
固定边界：
basis:x或z；distance: 不小于 3 的奇数；rounds: 正整数；shots: 正整数；physicalErrorRate: 0–1；seed: 0–2^32-1。
统一错误率同时用于 Clifford 后退极化、每轮数据退极化、测量翻转和 reset 翻转。这是版本化实验 profile，不代表某台真实 QPU 的校准模型。
工作流
- 选择 basis、distance、rounds、shots、physicalErrorRate 和显式 seed。
- 调用
run_qec_memory_experiment。主动作加载固定环境并返回packages；依赖须显式准备；缺失或旧锁环境返回准备命令，不在 Tool 中安装。 - 报告实际包版本、电路/DEM 摘要与 SHA-256、逻辑错误数、逻辑错误率、标准误和 Wilson 95% 区间。
- 检查 observations：实验摘要、seed、计数恒等式、错误率重算、区间边界、零噪声不变量、来源链。
- 比较多组实验时，每组都保留固定 shots 与 seed 策略；不要选择性丢弃失败点。环境不可用时报告工具错误，不编造结果。
解释规则
- 零逻辑错误不等于真实错误率为零，必须同时报告 shots 和 Wilson 区间。
- 单个 distance、单个物理错误率的结果不能证明 threshold。
- 不同 distance 的比较必须使用同一噪声 profile 和可比 shots。
physicalErrorRate是模拟器参数，不是硬件校准事实。- 工具完成只产生
observations_available；Result Package 和 Session Event Log 未物化时，不宣称最终科学验收通过。
输出格式
- 固定实验配置和包版本；
- code task、电路/DEM 规模与摘要；
- 逻辑错误数/率、标准误、Wilson 95% 区间；
- validation observations；
- 明确写出不能支持的 threshold 与硬件结论。
码距、存储轮数和采样数由调用方选择，适配器不额外设置人工规模上限。具体资源配置见本地计算说明。
依赖准备
运行前执行 node scripts/setup-paper-tools.mjs qec-memory-experiment。缺失、旧锁和已安装环境的处理见共同准备说明；Tool 不自动安装或升级依赖。
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.
- 9d ago Changed · +11 lines de97146ee918
- 27d ago Changed · +4 lines eb5ae10fe5d7
- 1mo ago Changed · +2 lines · -5 tokens per session 37d7d53c76e7
- 1mo ago Changed · -1 lines c87d234d0077
- 1mo ago First seen · 47 lines · 119 tokens per session scan A 0c74fe1002a1
qec-memory-experiment is a skill published in the GitHub repository xi-zhao/OpenQuantum (75 stars, last pushed yesterday), licensed MIT. It adds 114 tokens to every session and 1,008 once invoked, about $0.0005 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 2026-08-30.
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