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 flagquantum-workbenchgit 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/flagquantum-workbench)<a href="https://agentmods.dev/skills/xi-zhao/openquantum/flagquantum-workbench"><img src="https://agentmods.dev/badge/skills/xi-zhao/openquantum/flagquantum-workbench/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/flagquantum-workbench"><img src="https://agentmods.dev/badge/skills/xi-zhao/openquantum/flagquantum-workbench.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 | $0.00043 | $0.00749 |
| Opus 5.5 | $0.00017 | $0.00300 |
| Sonnet 5.5 | $0.00009 | $0.00150 |
| Haiku 4.5 | $0.00004 | $0.00075 |
Grade A, and why
flagquantum-workbench 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
FlagQuantum
原生 SDK 路径
本能力同时支持 FlagQuantum 的原生公开 API。用户需要 Circuit、序列化、门、拓扑、路由、训练与后端 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 flagquantum-workbench 定位环境，按完整 SDK 工作流执行。模块导航：flagquantum；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。
这是默认关闭的上游电路工作台。用户需要其 IR、编译、模拟或参数训练方法时，从设置中心启用 flagquantum 并准备固定环境。只使用该 server 命名空间中的 Tool，避免与 Qiskit 同名 Tool 混淆。
根据目标选择所需步骤：原始 gate-list QIR 需要 serialize_circuit_tool 转成 IR；分析用 analyze_circuit_tool，优化/路由用 optimize_circuit_tool / route_circuit_tool，需要导出时再用 emit_openqasm_tool / emit_qcis_tool。已有有效 IR 不必重复序列化；仅模拟不要求先优化、路由和导出。输入是 FlagQuantum IR JSON 或 QIR 门列表；OpenQASM 仅输出，不当作可读入格式。示例 QIR：[{"name":"h","index":[0]},{"name":"cx","index":[0,1]}]。
本地模拟使用 simulate_circuit_tool，核对 output kind、wire 顺序、precision、shots 和执行模式。先读 describe_gate_set_tool 再选不熟悉的门；训练必须有独立基线。17 个上游 Tool 的成功/失败在结果 status 中，不应只看 MCP isError。status=success 与 accuracy.metric=not_measured 不代表科学验收；实际硬件作业没有通过此连接提交。源服务的 readOnlyHint 只描述计算，启动器首次物化环境会写磁盘，因此 OQ 保守按 workspace-write 登记。
此上游协议没有 execution 字段。连接超时由 MCP 设置控制；启动器继承用户配置的数值线程与设备环境（如 OMP_NUM_THREADS），不固定为单线程。首调可能物化锁定环境，因此完整调用为 workspace-write。不要把执行成功或参考相符写成最终科学验收。安装、来源与示例见 候选库接入说明。
可按编译、模拟或训练选用专业工具范围；未选择时保留完整原接口。
What ships with it
4 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 6e8a3e9998fa
- 22d ago Changed · +2 lines · +2 tokens per session 432f86ad24bb
- 26d ago First seen · 15 lines · 41 tokens per session scan A 0492cf4b5937
flagquantum-workbench is a skill published in the GitHub repository xi-zhao/OpenQuantum (75 stars, last pushed yesterday), licensed MIT. It adds 43 tokens to every session and 749 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 2026-09-21.
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