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/internscience/chemclaw/geometry-optimizernpx skills add InternScience/ChemClaw --skill geometry-optimizergit clone --depth 1 https://github.com/InternScience/ChemClawWhat 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 | $0.00050 | $0.03479 |
| Opus 5 | $0.00025 | $0.01740 |
| Sonnet 5 | $0.00010 | $0.00696 |
| Haiku 4.5 | $0.00005 | $0.00348 |
Grade B, and why
geometry-optimizer scanned grade B with 1 finding 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 2d 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.
Asks for rootmediumPrivilege escalation
A mod that escalates privileges can change anything on the machine, not only the project.
sudo apt install cmake gfortran libblas-dev liblapack-dev How it starts
The opening of the file, as written. The whole thing — 456 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Geometry Optimizer
geometry-optimizer 是一个用于 分子三维几何结构优化 的化学类 skill。
它基于 GFN-xTB 半经验量子化学方法，对用户提供的分子初始结构进行快速、可落地的本地优化，输出优化后的坐标、能量、收敛状态等结果。
核心功能
- ✅ SMILES → 3D → 优化：自动从 SMILES 生成初始 3D 构象并进行 xTB 优化
- ✅ XYZ 文件输入：直接对已有 3D 坐标文件进行优化
- ✅ GFN2-xTB 方法：默认使用高精度的 GFN2-xTB 半经验方法
- ✅ 完整结果输出：优化后坐标、最终能量、梯度、收敛状态、日志文件
- ✅ 批量处理：支持 JSON 批量输入，多分子连续优化
适用场景
当用户有以下需求时，应调用本 skill：
| 用户需求 | 示例 |
|---|---|
| 优化分子 3D 结构 | "帮我优化这个分子的 3D 结构" |
| SMILES 转 3D 并优化 | "把这个 SMILES 生成 3D 后优化" |
| xTB 几何优化 | "用 xTB 做一下 geometry optimization" |
| 获取优化后坐标 | "给我一个预优化后的 xyz 坐标" |
| 半经验快速优化 | "用半经验方法快速优化一下分子结构" |
| DFT 预优化 | "在做 DFT 前先用 xTB 预优化" |
| XYZ/SDF 结构优化 | "对这个 XYZ 结构做几何优化" |
不适用场景
以下情况不应调用本 skill：
| 场景 | 原因 | 建议 |
|---|---|---|
| 高精度 DFT / ab initio 优化 | xTB 是半经验方法，精度有限 | 使用 Gaussian、ORCA、Psi4 等 |
| 过渡态搜索、IRC、频率分析 | 当前不支持 | 使用专用量化软件 |
| 晶体/周期性体系优化 | xTB 不支持 PBC | 使用 VASP、Quantum ESPRESSO |
| 蛋白质/超大体系 | 计算成本高，可能需要特殊处理 | 使用分子力学或专用工具 |
| 发表级精确结果 | 半经验方法适合预优化/筛选 | 使用高精度方法复核 |
输入格式
1. SMILES（推荐）
python scripts/main_script.py --smiles "CCO" --name "乙醇"
- 自动使用 RDKit 生成初始 3D 构象
- 自动推断电荷和未成对电子数
- 适用于只有二维分子表达式的场景
2. XYZ 文件
python scripts/main_script.py --input-xyz molecule.xyz --output-dir ./results
- 直接使用已有 3D 坐标
- 适合从实验结构或其他软件导出的坐标
3. 批量 JSON 输入
python scripts/main_script.py --input input.json --output output.json --output-dir ./results
input.json 格式：
[
{"name": "乙醇", "smiles": "CCO"},
{"name": "水", "smiles": "O"},
{"name": "自定义", "input_xyz": "path/to/molecule.xyz"}
]
输出格式
JSON 结果
{
"status": "completed",
"backend_used": "xtb",
"total": 1,
"success": 1,
"partial_success": 0,
"error": 0,
"results": [
{
"name": "乙醇",
"input_type": "smiles",
"smiles": "CCO",
"canonical_smiles": "CCO",
"status": "success",
"backend_used": "xtb",
"method": "gfn2",
"charge": 0,
"uhf": 0,
"solvent": null,
"converged": true,
"energy_hartree": -11.394338789631,
"energy_kcal_mol": -7150.050139542559,
"final_gradient": 0.000195893782,
"num_atoms": 9,
"optimized_xyz_path": "./test_output/optimized.xyz",
"log_path": "./test_output/xtbopt.log",
"runtime_seconds": 0.26,
"warnings": [],
"message": "Geometry optimization completed. Converged."
}
]
}
What ships with it
11 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.
- README.md 4.0 KB
- references/xtb_documentation.md 2.1 KB
- requirements.txt 17 B
- scripts/backends/__init__.py 42 B runs code
- scripts/backends/xtb_backend.py 11 KB runs code
- scripts/main_script.py 6.6 KB runs code
- scripts/test_xtb_backend.py 7.2 KB runs code
- scripts/utils/__init__.py 39 B runs code
- scripts/utils/io_utils.py 3.1 KB runs code
- scripts/utils/smiles_utils.py 2.5 KB runs code
- scripts/utils/xtb_utils.py 7.5 KB runs code
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.
- 2d ago First seen · 456 lines · 50 tokens per session scan B bb8f32065f8b
geometry-optimizer is a skill published in the GitHub repository InternScience/ChemClaw (52 stars, last pushed 5mo ago), licensed MIT. It adds 50 tokens to every session and 3,479 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it B with 1 finding (asks for root). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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