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 openfermion-mappinggit 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/openfermion-mapping)<a href="https://agentmods.dev/skills/xi-zhao/openquantum/openfermion-mapping"><img src="https://agentmods.dev/badge/skills/xi-zhao/openquantum/openfermion-mapping/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/openfermion-mapping"><img src="https://agentmods.dev/badge/skills/xi-zhao/openquantum/openfermion-mapping.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 | $0.00771 |
| Opus 5.5 | $0.00017 | $0.00308 |
| Sonnet 5.5 | $0.00009 | $0.00154 |
| Haiku 4.5 | $0.00004 | $0.00077 |
Grade A, and why
openfermion-mapping 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
OpenFermion 算符映射
原生 SDK 路径
本能力同时支持 OpenFermion 的原生公开 API。用户需要 费米子/玻色子算符、映射、张量、模型与化学接口 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 openfermion-mapping 定位环境,按完整 SDK 工作流执行。模块导航:openfermion;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。
Agent 经 Harness 调用 openfermion_local 提供的 map_openfermion_operator。用途是二次量子化算符到量子位算符的表示转换;已有化学求解能力不由本 Skill 替代。
输入 numModes、mapping 和 terms。每个 term 包含复系数 coefficient: {real, imag} 与有序 operators: [{mode, action}],action 是 create 或 annihilate。乘积按给定顺序书写,最右算符先作用在 ket 上。空 operators 表示常数项;重复项由上游合并。
mapping 选择 jordan_wigner 或 bravyi_kitaev。输出每条 Pauli 字符串最左边表示 qubit 0。Jordan-Wigner 使用占据编码;Bravyi-Kitaev 使用奇偶校验变换后的编码,不能直接用未经基底变换的矩阵元素逐项比较两个表示。
返回 Pauli 项、系数 L1 范数及 hermiticityResidualL1(A-A† 的 Pauli 系数 L1 范数)。hermitian 仅在返回的浮点系数残差恰为 0 时为 true,不借助隐含容差给出科学验收。允许非 Hermitian 输入,便于产生、湮灭及响应算符处理。
工具不求电子结构、分子积分或能谱,不创建稠密矩阵,也不查询 PubChem 等数据库。固定 OpenFermion 1.8.1(Apache-2.0)。
先运行 node scripts/setup-paper-tools.mjs openfermion-mapping 显式准备固定依赖。计算 Tool 不安装依赖、不连接外部服务;SDK 可能写本地缓存,因此最大副作用登记为 workspace-write。部署时间、输出大小与线程设置使用 execution,与方法规模分开。
当前为 L1,scientificValidation=not_evaluated。本地数值、协议与 Harness 测试是开发证据;执行成功不等于 central Acceptance Builder 已推导科学验收。
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 · +11 lines 9c8c7a90df26
- 18d ago First seen · 21 lines · 43 tokens per session scan A 8d2110655bb4
openfermion-mapping 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 771 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.
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…