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 agentmods add skills/lex669/lumericalfdtd-skill/lumericalfdtd-analysisnpx skills add Lex669/LumericalFDTD-skill --skill lumericalfdtd-analysisgit clone --depth 1 https://github.com/Lex669/LumericalFDTD-skillWrote 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/lex669/lumericalfdtd-skill/lumericalfdtd-analysis)<a href="https://agentmods.dev/skills/lex669/lumericalfdtd-skill/lumericalfdtd-analysis"><img src="https://agentmods.dev/badge/skills/lex669/lumericalfdtd-skill/lumericalfdtd-analysis.svg" alt="Measured on agentmods" 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 | $0.00109 | $0.01116 |
| Opus 5 | $0.00055 | $0.00558 |
| Sonnet 5 | $0.00022 | $0.00223 |
| Haiku 4.5 | $0.00011 | $0.00112 |
Grade A, and why
LumericalFDTD-analysis 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 6d 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.
How it starts
The opening of the file, as written. The whole thing — 126 lines — stays where its author put it; the contents beside it link to each section on GitHub.
FDTD 数据分析器
职责范围
本 skill 仅负责数据分析与可视化阶段:读取 .npz 数据、计算光学指标、绘制图表、验证验收条件。输出 .png 图表文件。
不负责:结构建模(→ LumericalFDTD-modeling)、仿真执行(→ LumericalFDTD-simulation)、端到端全流程(→ LumericalFDTD)。
前置条件
.npz 数据文件必须已存在于 data/ 目录。若不存在,先运行仿真。
工作流
1. 确认数据可用
ls path/to/project/data/
# 确认 results.npz 等文件存在
2. 编写分析脚本
按模板生成 *_analysis.py(纯数据分析,不调 lumapi.FDTD):
import numpy as np
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
# 加载数据
data = np.load(os.path.join(data_dir, "results.npz"), allow_pickle=True)
E = data["E"]
T = data["T"]
wavelengths = data["wavelengths"]
# ...
# 计算指标
transmission = np.abs(T)**2
# ...
# 绘图
fig, ax = plt.subplots(figsize=(8, 5))
ax.plot(wavelengths * 1e6, transmission)
ax.set_xlabel("Wavelength (μm)")
ax.set_ylabel("Transmission")
ax.set_title("Transmission Spectrum")
fig.savefig(os.path.join(pic_dir, "transmission.png"), dpi=150)
plt.close()
3. 运行分析脚本
& 'PYTHON_PATH' 'path/to/project_analysis.py'
分析脚本秒级完成,可反复执行迭代图表样式。
4. 验证结果
检查生成的 .png 图表是否满足验收条件:
| 验收维度 | 检查项 |
|---|---|
| 透射率 | 峰值/谷值在预期波长?数值合理(0-1)? |
| 场分布 | 模式图样是否符合物理预期? |
| 衍射图案 | Airy 环是否可见?中央亮斑尺寸是否符合 r₁ = 1.22λL/D? |
| 图表质量 | 坐标轴标注、单位、图例是否齐全?分辨率是否足够? |
常用分析类型
透射/反射谱
T = fdtd.getresult("monitor", "T")
plt.plot(wavelengths * 1e6, np.abs(T)**2)
plt.xlabel("Wavelength (μm)")
plt.ylabel("Transmission")
近场/远场分布
E = np.abs(Ex**2 + Ey**2 + Ez**2) # |E|^2 intensity
I_1d = np.sum(I, axis=1) # Quasi-2D: 沿 y 求和 -> 1D profile
plt.plot(x * 1e6, I_1d / I_1d.max())
衍射效率
P_total = np.sum(I, axis=(0, 1, 2))
P_central = np.sum(I_central_region, axis=(0, 1, 2))
efficiency = P_central / P_total
宽带波长索引
# 频率线性递增 → 波长递减
wl_short_idx = n_freq - 1 # 最短波长(高频端)
wl_long_idx = 0 # 最长波长(低频端)
输出
*_analysis.py— 分析脚本(可反复迭代)pic/*.png— 结果图表(dpi ≥ 150)- 可选:更新
REPORT.md— 结果摘要和图表说明
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.
- 6d ago First seen · 126 lines · 109 tokens per session scan A 3e5b52a93cf0
LumericalFDTD-analysis is a skill published in the GitHub repository Lex669/LumericalFDTD-skill (23 stars, last pushed 16d ago), licensed MIT. It adds 109 tokens to every session and 1,116 once invoked, about $0.0005 per session on Opus 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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