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chem-react-ot

Generate transition state structures for chemical reactions using React-OT.

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価格未確認★ 161 GitHub スター登録情報の更新日 · 2026年9月6日agent-skill

概要

Generate transition state structures for chemical reactions using React-OT.

説明全文を読む

ソース文書であり、このサイトへの操作指示ではありません。コマンド実行前に権限を確認してください。

`chem-react-ot` — React-OT Transition State Generation

Goal

Generate transition state (TS) structures given reactant and product structures using the React-OT model (Optimal Transport). React-OT is a generative model that predicts TS geometries directly without requiring an initial guess path (like NEB).

Category: chemistry Environment: react-ot-agent

Key Features

Generative TS Prediction: Predicts 3D transition state structures from 3D reactants and products.
Fast Inference: Uses an ODE solver for generation, typically much faster than DFT-based NEB.
No Path Guess Required: Directly generates the TS structure.

Usage

1. Environment Setup

This skill requires the react-ot-agent conda environment. Ensure it is installed:

# Env: react-ot-agent
cd conda-envs/react-ot-agent
bash install.sh

2. Download Models

Before running the skill for the first time, download the pre-trained model weights:

# activate react-ot-agent first
conda activate react-ot-agent
python conda-envs/react-ot-agent/download_models.py

The checkpoint is saved to ~/.cache/react-ot/checkpoints/sb-pretrained.ckpt.

3. Generate Transition State

Run the generation script with reactant and product files (xyz, cif, pdb, etc. - anything ASE reads).

# Env: react-ot-agent
python .agents/skills/chem-react-ot/scripts/generate_ts.py \
    --reactants reactant.xyz \
    --products product.xyz \
    --output_dir results/ts_search

Arguments:

--reactants: Path to reactant structure file(s). Can be a single file with multiple molecules or a list of files.
--products: Path to product structure file(s).
--output_dir: Directory to save the generated TS structure (ts_generated.xyz) and trajectory (generation_traj.xyz).
--nfe: Number of function evaluations for the ODE solver (default: 10). Higher values might be more accurate but slower.
--checkpoint: Path to custom model checkpoint (optional, defaults to downloaded one).

Example

# Env: react-ot-agent
python .agents/skills/chem-react-ot/scripts/generate_ts.py \
    --reactants .agents/skills/chem-react-ot/examples/oxadiazole_isomerization/reactant.xyz \
    --products .agents/skills/chem-react-ot/examples/oxadiazole_isomerization/product.xyz \
    --output_dir .agents/skills/chem-react-ot/examples/oxadiazole_isomerization/output

Constraints

Environment: All scripts require the react-ot-agent conda environment.
Input Format: Reactant and product structures must be in any format readable by ASE (XYZ, CIF, PDB, etc.).
Atom Ordering: Reactant and product structures must have the same number of atoms with consistent atom ordering.
Model Checkpoint: The pre-trained checkpoint must be downloaded before first use (see step 2).

References

React-OT GitHub
Duan, C., Liu, G.-H., Du, Y. et al., "Optimal transport for generating transition states in chemical reactions", Nature Machine Intelligence, 2025. DOI

Author: Bowen Deng Contact: GitHub @learningmatter-mit

ソースを見る ↗

ファイルのメタデータ

name: chem-react-ot
description: Generate transition state structures for chemical reactions using React-OT.
category: [chemistry]

元のテキストを表示

---
name: chem-react-ot
description: Generate transition state structures for chemical reactions using React-OT.
category: [chemistry]
---

# `chem-react-ot` — React-OT Transition State Generation

## Goal

Generate transition state (TS) structures given reactant and product structures using the React-OT model (Optimal Transport). React-OT is a generative model that predicts TS geometries directly without requiring an initial guess path (like NEB).

**Category:** `chemistry`
**Environment:** `react-ot-agent`

## Key Features

- **Generative TS Prediction:** Predicts 3D transition state structures from 3D reactants and products.
- **Fast Inference:** Uses an ODE solver for generation, typically much faster than DFT-based NEB.
- **No Path Guess Required:** Directly generates the TS structure.

## Usage

### 1. Environment Setup

This skill requires the `react-ot-agent` conda environment. Ensure it is installed:

```bash
# Env: react-ot-agent
cd conda-envs/react-ot-agent
bash install.sh
```

### 2. Download Models

Before running the skill for the first time, download the pre-trained model weights:

```bash
# activate react-ot-agent first
conda activate react-ot-agent
python conda-envs/react-ot-agent/download_models.py
```

The checkpoint is saved to `~/.cache/react-ot/checkpoints/sb-pretrained.ckpt`.

### 3. Generate Transition State

Run the generation script with reactant and product files (xyz, cif, pdb, etc. - anything ASE reads).

```bash
# Env: react-ot-agent
python .agents/skills/chem-react-ot/scripts/generate_ts.py \
    --reactants reactant.xyz \
    --products product.xyz \
    --output_dir results/ts_search
```

**Arguments:**

- `--reactants`: Path to reactant structure file(s). Can be a single file with multiple molecules or a list of files.
- `--products`: Path to product structure file(s).
- `--output_dir`: Directory to save the generated TS structure (`ts_generated.xyz`) and trajectory (`generation_traj.xyz`).
- `--nfe`: Number of function evaluations for the ODE solver (default: 10). Higher values might be more accurate but slower.
- `--checkpoint`: Path to custom model checkpoint (optional, defaults to downloaded one).

## Example

```bash
# Env: react-ot-agent
python .agents/skills/chem-react-ot/scripts/generate_ts.py \
    --reactants .agents/skills/chem-react-ot/examples/oxadiazole_isomerization/reactant.xyz \
    --products .agents/skills/chem-react-ot/examples/oxadiazole_isomerization/product.xyz \
    --output_dir .agents/skills/chem-react-ot/examples/oxadiazole_isomerization/output
```

## Constraints

- **Environment**: All scripts require the `react-ot-agent` conda environment.
- **Input Format**: Reactant and product structures must be in any format readable by ASE (XYZ, CIF, PDB, etc.).
- **Atom Ordering**: Reactant and product structures must have the same number of atoms with consistent atom ordering.
- **Model Checkpoint**: The pre-trained checkpoint must be downloaded before first use (see step 2).

## References

- [React-OT GitHub](https://github.com/deepprinciple/react-ot)
- Duan, C., Liu, G.-H., Du, Y. et al., "Optimal transport for generating transition states in chemical reactions", *Nature Machine Intelligence*, 2025. [DOI](https://doi.org/10.1038/s42256-025-01010-0)

---

**Author:** Bowen Deng
**Contact:** [GitHub @learningmatter-mit](https://github.com/learningmatter-mit)

ソースを確認

価格と実行コスト

Skill の入手: 価格未確認
実行: 実行要件は未確認です。Agent・API・サービス料金を提供元で確認してください。
ライセンス: MIT
価格未確認: 価格は未確認です。既存のソースとインストールリンクは利用できます。

無料で入手できても実行が無料とは限りません。価格は安全評価ではありません。価格情報を送る →

スキルのソースを記録済み

手順のパスを記録しています。実行テスト、安全保証、互換性認証ではありません。

インストール前にレビュー: 自動インストールを避ける

ライセンス: MIT

Dependency or permission surface needs review
Permission surface may require sandboxing
The script's handling of multiple reactant/product files is not fully documented; the example only shows single files, while the description mentions support for lists.
The model weight download step relies on an external URL without explicit checksum verification, which could be a supply chain risk if the source is compromised.
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
Stars/forks activity: 161 stars, 24 forks; issue activity unavailable in current metadata
Dependency/runtime risk: command execution surface, credential or environment access
Permission surface: secrets or environment access, shell or command execution

完全な監査を開く

ツール一覧はメタデータであり、互換性のテスト結果ではありません。プロンプトは提案です。

小さなタスクから始める

1ソースを読み、入力、出力、依存関係、権限を確認します。
2Agent に計画を求め、設定と費用を承認してから隔離環境でテストします。
3出力と変更ファイルを確認し、実行した結果だけを報告します。再現用にソースの版を保存します。

依存関係、API キー、外部サービスの料金をソースで確認してください。公開リポジトリでも全サービスが無料とは限りません。

出典と利用上の注意

登録済み

メタデータと審査情報は参考です。人気、ソースの発見、実行成功は別の事実です。

ソースリポジトリ: learningmatter-mit/AtomisticSkills
ライセンス: MIT
バージョン: 1.0.0
最終 GitHub プッシュ: 2026年9月3日
登録情報の更新日: 2026年9月6日
手順のパス: .agents/skills/chem-react-ot/SKILL.md @ d1f7ecfda2cd

登録されたバージョンです。ソースのリリース情報を確認してください。

品質

66/100

有望

信頼

56/100

Do not auto-install

監査

73/100

要レビュー

完全な監査を開く評価レポートを見る

Dependency or permission surface needs review
Permission surface may require sandboxing
The script's handling of multiple reactant/product files is not fully documented; the example only shows single files, while the description mentions support for lists.
The model weight download step relies on an external URL without explicit checksum verification, which could be a supply chain risk if the source is compromised.
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
Stars/forks activity: 161 stars, 24 forks; issue activity unavailable in current metadata
Dependency/runtime risk: command execution surface, credential or environment access
Permission surface: secrets or environment access, shell or command execution

Verified installs: —
成果: —

コピーはインストールではありません。件数は成功報告に基づき、品質全体を保証しません。

Agent 接続

Registry API 経由で判断、信頼、監査、ユースケース、インストールのシグナルを提供し、UI をスクレイピングせずに Agent が順位付けできます。

Install API を開く LLM テキスト形式 Manifest を開く自動解決プラン

詳細情報

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}

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Registry により登録

申請可能

この掲載は公開ソースから登録されており、メンテナー申請が承認されるまで公式として表示されません。

作成者: learningmatter-mit
ソース: learningmatter-mit/AtomisticSkills
インデックス作成者: OpenAgentSkill コミュニティインデックス

帰属は公開リポジトリまたは作成者プロフィールにリンクされています。作成者は掲載を申請して所有権シグナルを更新できます。

このスキルを申請

所有者の申請

このスキル掲載を申請

この Registry により登録掲載は learningmatter-mit に帰属していますが、まだ公式として表示されていません。申請すると、確認済み所有者シグナルが追加され、今後の公開、インストール、監査更新の信頼性が高まります。

共有キット

クリエイター被リンクキット

README にエビデンスバッジを追加

開発者がリポジトリを評価する場所で、正規掲載、現在の信頼・監査シグナル、実際の Agent-Proven エビデンスを表示します。

[![Listed on OpenAgentSkill](https://www.openagentskill.com/api/badge/learningmatter-mit-chem-react-ot?metric=listed&label=Listed)](https://www.openagentskill.com/skills/learningmatter-mit-chem-react-ot?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[![OpenAgentSkill Trust](https://www.openagentskill.com/api/badge/learningmatter-mit-chem-react-ot?metric=trust&label=Trust)](https://www.openagentskill.com/skills/learningmatter-mit-chem-react-ot?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[![OpenAgentSkill Audit](https://www.openagentskill.com/api/badge/learningmatter-mit-chem-react-ot?metric=audit&label=Audit)](https://www.openagentskill.com/skills/learningmatter-mit-chem-react-ot/audit)
[![Agent Proven](https://www.openagentskill.com/api/badge/learningmatter-mit-chem-react-ot?metric=proven&label=Agent%20Proven)](https://www.openagentskill.com/skills/learningmatter-mit-chem-react-ot?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)

バッジをプレビュー監査を開くクリエイターキット

コミュニティシグナル

このスキルが Agent ワークフローに役立つかを共有してください。集約されたフィードバックがランキングを改善します。

概要

chem-react-ot — React-OT Transition State Generation