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 qsyn-compilationgit 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/qsyn-compilation)<a href="https://agentmods.dev/skills/xi-zhao/openquantum/qsyn-compilation"><img src="https://agentmods.dev/badge/skills/xi-zhao/openquantum/qsyn-compilation/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/qsyn-compilation"><img src="https://agentmods.dev/badge/skills/xi-zhao/openquantum/qsyn-compilation.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 | $0.00047 | $0.00615 |
| Opus 5.5 | $0.00019 | $0.00246 |
| Sonnet 5.5 | $0.00009 | $0.00123 |
| Haiku 4.5 | $0.00005 | $0.00061 |
Grade A, and why
qsyn-compilation 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 3d 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
Qsyn
原生 SDK 路径
本能力使用 Qsyn 的原生公开 API。用户需要 C++ 库、线路综合、ZX/张量变换、优化、验证与 CLI 时,由 Agent 在固定依赖环境中编写和运行任务代码。
使用 node scripts/sdk-access.mjs inspect qsyn-compilation 定位环境,按完整 SDK 工作流执行。模块导航:固定版本的原生头文件与源码;导航不是 API 白名单。
使用完整固定源码与 C++20 构建。输入语言、门集、布局、全局相位和导出语义分别核对;编译成功不构成等价性证明。
Apple Silicon macOS 本轮验证使用 GCC 16.2.0;显式 setup 时用 CC/CXX 指定已安装编译器。Clang 22 与上游 fmt 10.2.1 组合已知构建失败,其他工具链须独立核验。
本入口复用宿主文件与代码工具,没有新增通用执行 Tool。原生 SDK 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。
使用完整固定源码与 C++20 构建。输入语言、门集、布局、全局相位和导出语义分别核对;编译成功不构成等价性证明。
按固定版本的公开文档和签名选择方法;输入、算法与资源预算由任务决定。该 Skill 通过原生 SDK 工作台和宿主代码工具执行自定义程序,没有新增通用执行服务或专用计算 Tool。
保留程序、输入、完整结果、依赖锁摘要和实际检查。原生 API 的执行不推导最终科学验收,scientificValidation=not_evaluated。
原生程序示例
固定版本的可编辑程序展示公开 API 的使用方式,参数与模型可按研究任务修改。先显式准备环境,再在独立任务目录运行,保留结果文件;示例检查不构成最终科学验收。
What ships with it
5 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.
- 3d ago First seen · 36 lines · 47 tokens per session scan A eacd508752e8
qsyn-compilation is a skill published in the GitHub repository xi-zhao/OpenQuantum (75 stars, last pushed yesterday), licensed MIT. It adds 47 tokens to every session and 615 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 2026-10-14.
Other skills, from other repositories
cuopt-numerical-optimization-api
LP, MILP, and QP (beta) with cuOpt — Python, C, and CLI. Use when the user is solving LP, MILP, or QP with any cuOpt interface.
torchtalk-analyzer
Analyze PyTorch internals across Python, C++, and CUDA layers using the TorchTalk MCP server. Use when asked about how PyTorch operators work internally, where functions are implemented, what would break if code is modified, or finding tests for PyTorch operators.
torchtalk-trace
Trace a PyTorch function's cross-language binding chain (Python -> C++ -> CUDA).
sympy
Apply sympy in reproducible local data workflows with version-aware APIs, explicit assumptions, and validation. Use when the user chooses sympy or its strengths fit the task.
opengrok-cpp
Specialized patterns for navigating C++ codebases with OpenGrok MCP.
ue-mcp-native-cpp
Use when writing or modifying native C++ UCLASSes in an Unreal project via ue-mcp. Covers createcppclass → writecppfile → livecodingcompile loop, when to use build vs Live Coding, and the addmoduledependency workflow. Pulls in any time the user asks to write a new native class, add a UPROPERTY, or implement a…