Agent skill

Reactions Standardization

by VectorSpaceLab in VectorSpaceLab/AREX-Skill

A skill your agent uses for RDKit reaction SMARTS/RXN workflows, product sanitization, MolStandardize cleanup/normalization/fragment/tautomer handling, R-group decomposition, stereochemistry/CIP…

BSD-3-ClauseAuto-check passedResearch & Science

Install Reactions Standardization

skills CLI

$ npx skills add VectorSpaceLab/AREX-Skill --skill reactions-standardization -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI

$ gh skill install VectorSpaceLab/AREX-Skill reactions-standardization --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy

$ git clone --depth 1 https://github.com/VectorSpaceLab/AREX-Skill.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/repositories/repo-skills/rdkit/sub-skills/reactions-standardization .claude/skills/reactions-standardization && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Paste into Claude Code

Install the "reactions-standardization" agent skill from https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/rdkit/sub-skills/reactions-standardization into .claude/skills/reactions-standardization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "reactions-standardization", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/rdkit/sub-skills/reactions-standardization

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add VectorSpaceLab/AREX-Skill --skill reactions-standardization -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install VectorSpaceLab/AREX-Skill reactions-standardization --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/VectorSpaceLab/AREX-Skill.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/repositories/repo-skills/rdkit/sub-skills/reactions-standardization .agents/skills/reactions-standardization && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "reactions-standardization" agent skill from https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/rdkit/sub-skills/reactions-standardization into .agents/skills/reactions-standardization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "reactions-standardization", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add VectorSpaceLab/AREX-Skill --skill reactions-standardization -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install VectorSpaceLab/AREX-Skill reactions-standardization --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/VectorSpaceLab/AREX-Skill.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/repositories/repo-skills/rdkit/sub-skills/reactions-standardization .cursor/skills/reactions-standardization && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "reactions-standardization" agent skill from https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/rdkit/sub-skills/reactions-standardization into .cursor/skills/reactions-standardization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "reactions-standardization", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/VectorSpaceLab/AREX-Skill.git --path skills/repositories/repo-skills/rdkit/sub-skills/reactions-standardization

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add VectorSpaceLab/AREX-Skill --skill reactions-standardization -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install VectorSpaceLab/AREX-Skill reactions-standardization --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/VectorSpaceLab/AREX-Skill.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/repositories/repo-skills/rdkit/sub-skills/reactions-standardization .gemini/skills/reactions-standardization && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "reactions-standardization" agent skill from https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/rdkit/sub-skills/reactions-standardization into .gemini/skills/reactions-standardization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "reactions-standardization", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install VectorSpaceLab/AREX-Skill reactions-standardization

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add VectorSpaceLab/AREX-Skill --skill reactions-standardization -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/VectorSpaceLab/AREX-Skill.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/repositories/repo-skills/rdkit/sub-skills/reactions-standardization .github/skills/reactions-standardization && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "reactions-standardization" agent skill from https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/rdkit/sub-skills/reactions-standardization into .github/skills/reactions-standardization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "reactions-standardization", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add VectorSpaceLab/AREX-Skill --skill reactions-standardization -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install VectorSpaceLab/AREX-Skill reactions-standardization --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/VectorSpaceLab/AREX-Skill.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/repositories/repo-skills/rdkit/sub-skills/reactions-standardization .opencode/skills/reactions-standardization && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "reactions-standardization" agent skill from https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/rdkit/sub-skills/reactions-standardization into .opencode/skills/reactions-standardization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "reactions-standardization", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: reactions-standardization
GitHub stars: 330
Token cost: ~1.2k tokens
SKILL.md length: 420 words
Files: 5 (incl. scripts, references)
Skills in repo: 159
Repo updated: Sep 3, 2026
First seen: Oct 7, 2026
Licence: BSD-3-Clause

At a glance

A skill your agent uses for RDKit reaction SMARTS/RXN workflows, product sanitization, MolStandardize cleanup/normalization/fragment/tautomer handling, R-group decomposition, stereochemistry/CIP…

Works in 6 steps: Parse molecules in molecule-io-core,… → For reaction SMARTS, build the reaction,… → Treat RunReactants() output as… → …
RDKit reaction SMARTS/RXN workflows
SKILL.md covers Route here, Route elsewhere, Start with these references and Core workflow, plus 2 more sections
Runs Python scripts from its folder; calls python

What it does

Reactions Standardization is an agent skill from VectorSpaceLab/AREX-Skill. Use for RDKit reaction SMARTS/RXN workflows, product sanitization, MolStandardize cleanup/normalization/fragment/tautomer handling, R-group decomposition, stereochemistry/CIP practical workflows, and medicinal chemistry transformations. Route base molecule parsing to molecule-io-core and optional MMPA/Fraggle contrib workflows to contrib-utilities.

Its SKILL.md is about 1.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files, including scripts and reference files (for example `references/reactions.md`, `references/standardization-rgroups-stereo.md` and `references/troubleshooting.md`).

It sits in Research & Science, covering Drug discovery and cheminformatics and Database schema design. It works with RDKit. The repository describes itself as: A Skill Library for Automated Machine Learning. The licence is BSD-3-Clause.

When your agent uses it

RDKit reaction SMARTS/RXN workflows
Product sanitization
MolStandardize cleanup/normalization/fragment/tautomer handling
R-group decomposition

Example prompts

“/reactions-standardization”

Requirements

Python 3

Workflow steps

6 steps, taken from the first numbered list in SKILL.md.

Parse molecules in molecule-io-core, then pass checked Mol objects into reaction or standardization code.
For reaction SMARTS, build the reaction, inspect template counts, call Validate(), and match the exact reactant tuple arity required by…
Treat RunReactants() output as unsanitized candidate products: copy or select products deliberately, run Chem.SanitizeMol, and report…
Standardize before comparing analogs or calculating descriptors: choose whether the task needs Cleanup, FragmentParent, ChargeParent…
For R-group decomposition, start with a chemically meaningful core, prefer labeled attachment points when labels matter, and always…
For stereochemistry-sensitive workflows, keep isomericSmiles=True, use mapped reaction atoms, assign CIP labels after final sanitization…

What it can do on your machine

Read from SKILL.md and the folder at commit ac3fe1a. It shows what the files ask for, not the result of running them.

Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships 1 file in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
- python
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Reactions Standardization loads about 1.2k tokens when it runs, and up to ~5.5k if it reads all its reference files. Until then it costs about 94 tokens; SKILL.md has 420 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~94
When it runs · the whole SKILL.md, loaded when a task matches: ~1.2k
With references · SKILL.md plus every file in references/, read only if the agent opens them: ~5.5k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from VectorSpaceLab/AREX-Skill at commit ac3fe1a, republished under its BSD-3-Clause licence (© VectorSpaceLab). 420 words, ~1,232 tokens.

Download SKILL.mdSave it as .claude/skills/reactions-standardization/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.

name: reactions-standardization
description: Use for RDKit reaction SMARTS/RXN workflows, product sanitization, MolStandardize cleanup/normalization/fragment/tautomer handling, R-group decomposition, stereochemistry/CIP practical workflows, and medicinal chemistry transformations. Route base molecule parsing to molecule-io-core and optional MMPA/Fraggle contrib workflows to contrib-utilities.
disable-model-invocation: true
metadata.disco-role: operating
license: BSD 3-Clause

RDKit Reactions and Standardization

Use this sub-skill when a task asks an agent to transform molecules with reaction SMARTS, clean medicinal chemistry structures, choose parent fragments/charge forms, enumerate or canonicalize tautomers, decompose analog series into R-groups, or preserve/debug stereochemistry through these workflows.

Route here

Build and run reaction SMARTS/RXN workflows with rdkit.Chem.rdChemReactions or AllChem.ReactionFromSmarts.
Validate reaction definitions, atom mapping, reactant counts, agents, product templates, and product sanitization.
Use rdkit.Chem.MolStandardize.rdMolStandardize for cleanup, normalization, reionization, uncharging, fragment parents, charge parents, and tautomer enumeration.
Run rdkit.Chem.rdRGroupDecomposition.RGroupDecompose against labeled or auto-labeled cores and interpret unmatched molecules.
Preserve, assign, or inspect stereochemistry and CIP labels after transformations with Chem.FindPotentialStereo and rdCIPLabeler.AssignCIPLabels.
Implement medicinal chemistry transformations such as neutralization, salt stripping, parent selection, scaffold analog decomposition, and small reaction-based substitutions.

Route elsewhere

Base molecule parsing, suppliers, None checks, and generic sanitization basics: molecule-io-core.
Descriptors, fingerprints, similarity, and clustering after standardization: descriptors-fingerprints.
Drawing molecules or reactions and coordinate generation: conformers-drawing.
Optional contributed MMPA, Fraggle, SA/NP scoring, and other Contrib/ utilities: contrib-utilities.
RDKit source checkout build/test work for these modules: repo-development.

Start with these references

references/reactions.md for reaction SMARTS construction, running reactions, product handling, and stereochemistry behavior in reactions.
references/standardization-rgroups-stereo.md for MolStandardize, R-group decomposition, tautomer, uncharging, fragment-parent, and CIP/stereo recipes.
references/troubleshooting.md for invalid SMARTS, unsanitized products, unmatched cores, and parameter mistakes.
scripts/standardize_react_smoke.py for a tiny standalone cleanup plus reaction SMARTS smoke test.

Show full SKILL.md (196 more words)Show less

Core workflow

Parse molecules in molecule-io-core, then pass checked Mol objects into reaction or standardization code.
For reaction SMARTS, build the reaction, inspect template counts, call Validate(), and match the exact reactant tuple arity required by the reaction.
Treat RunReactants() output as unsanitized candidate products: copy or select products deliberately, run Chem.SanitizeMol, and report failures with the product index and SMILES when possible.
Standardize before comparing analogs or calculating descriptors: choose whether the task needs Cleanup, FragmentParent, ChargeParent, Uncharger, or tautomer canonicalization rather than applying every transform blindly.
For R-group decomposition, start with a chemically meaningful core, prefer labeled attachment points when labels matter, and always inspect unmatched indices before trusting the R-group table.
For stereochemistry-sensitive workflows, keep isomericSmiles=True, use mapped reaction atoms, assign CIP labels after final sanitization, and document whether a transform preserves, creates, destroys, or inverts a stereocenter.

Minimal examples

python

from rdkit import Chem
from rdkit.Chem import rdChemReactions

rxn = rdChemReactions.ReactionFromSmarts("[C:1]=[O:2]>>[C:1][O:2]")
products = rxn.RunReactants((Chem.MolFromSmiles("CC=O"),))
product = products[0][0]
Chem.SanitizeMol(product)
smiles = Chem.MolToSmiles(product, isomericSmiles=True)

python

from rdkit import Chem
from rdkit.Chem.MolStandardize import rdMolStandardize

mol = Chem.MolFromSmiles("CC(=O)[O-].[Na+]")
parent = rdMolStandardize.FragmentParent(mol)
uncharged = rdMolStandardize.Uncharger().uncharge(parent)

Bundled check

Run the bundled helper in an environment where RDKit is importable:

bash

python scripts/standardize_react_smoke.py --smiles "CC(=O)[O-].[Na+]" --reactant "CC=O"

It asserts that cleanup and fragment-parent selection produce valid molecules, builds a tiny reaction SMARTS, sanitizes the first product, and prints canonical SMILES outputs. Use --bad-reaction to confirm invalid reaction SMARTS are reported cleanly.

Files

SKILL.md and 4 other files (scripts, references) in skills/repositories/repo-skills/rdkit/sub-skills/reactions-standardization of VectorSpaceLab/AREX-Skill.

SKILL.md
references/reactions.md
references/standardization-rgroups-stereo.md
references/troubleshooting.md
scripts/standardize_react_smoke.py

Open the folder on GitHubat commit ac3fe1a

Compare with similar skills

Reactions Standardization next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Reactions Standardization compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Reactions Standardization this skillVectorSpaceLab/AREX-Skill	330	—	~1.2k	Automated safety check: Pass	BSD-3-Clause	1 mo ago
Bio Molecular StandardizationGPTomics/bioSkills	1.2k	1 repos	~4.5k	Automated safety check: Pass	MIT	1 mo ago
DiffDock Molecular DockingK-Dense-AI/scientific-agent-skills	48k	1 repos	~3k	Automated safety check: Notes	MIT	4 days ago
Edu Chem Reactionwy51ai/edulab	1.4k	—	~1.2k	Automated safety check: Pass	Apache-2.0	11 days ago
Biopipelineslocbp-uzh/biopipelines	109	—	~2.4k	Automated safety check: Pass	MIT	9 days ago
RDKit Cheminformatics Practicesaiming-lab/AutoResearchClaw	15k	—	~708	Automated safety check: Pass	MIT	1 mo ago

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Questions about Reactions Standardization

What does Reactions Standardization do?

A skill your agent uses for RDKit reaction SMARTS/RXN workflows, product sanitization, MolStandardize cleanup/normalization/fragment/tautomer handling, R-group decomposition, stereochemistry/CIP…. Reactions Standardization is an agent skill from VectorSpaceLab/AREX-Skill. Use for RDKit reaction SMARTS/RXN workflows, product sanitization, MolStandardize cleanup/normalization/fragment/tautomer handling, R-group decomposition, stereochemistry/CIP practical workflows, and medicinal chemistry transformations.

When should I use Reactions Standardization?

Reactions Standardization fits situations like: RDKit reaction SMARTS/RXN workflows; product sanitization; molStandardize cleanup/normalization/fragment/tautomer handling; R-group decomposition.

How do I install Reactions Standardization in Claude Code?

Run `npx skills add VectorSpaceLab/AREX-Skill --skill reactions-standardization -a claude-code`. Or copy the skill folder (skills/repositories/repo-skills/rdkit/sub-skills/reactions-standardization in VectorSpaceLab/AREX-Skill) into .claude/skills/reactions-standardization in your project. Claude Code loads it when a task matches its description.

How do I install Reactions Standardization in Codex?

Run `npx skills add VectorSpaceLab/AREX-Skill --skill reactions-standardization -a codex`. Or copy the skill folder (skills/repositories/repo-skills/rdkit/sub-skills/reactions-standardization in VectorSpaceLab/AREX-Skill) into .agents/skills/reactions-standardization in your project. Codex loads it when a task matches its description.

Can I use Reactions Standardization in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add VectorSpaceLab/AREX-Skill --skill reactions-standardization -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/reactions-standardization, .gemini/skills/reactions-standardization, .github/skills/reactions-standardization and .opencode/skills/reactions-standardization in your project.

What does Reactions Standardization need to run?

Going by SKILL.md and its folder, Reactions Standardization needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3.

Does Reactions Standardization access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Reactions Standardization safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Reactions Standardization use?

Reactions Standardization is published under the BSD-3-Clause licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Reactions Standardization use?

About 1.2k tokens (SKILL.md is roughly 4.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 4.3k tokens, read only when the agent opens those files.

What are the alternatives to Reactions Standardization?

Skills that share tags, products or a category with Reactions Standardization: Bio Molecular Standardization (GPTomics/bioSkills, 1.2k stars), DiffDock Molecular Docking (K-Dense-AI/scientific-agent-skills, 48k stars), Edu Chem Reaction (wy51ai/edulab, 1.4k stars) and Biopipelines (locbp-uzh/biopipelines, 109 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Reactions Standardization?

VectorSpaceLab (a GitHub organization) maintains it in VectorSpaceLab/AREX-Skill, which has 330 GitHub stars. The repository holds 159 skills in this directory. The repository was last updated on September 3, 2026.

Source: VectorSpaceLab/AREX-Skill on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Reactions Standardization

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

Workflow steps

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

RDKit Reactions and Standardization

Route here

Route elsewhere

Start with these references

Core workflow

Minimal examples

Bundled check

Files

Compare with similar skills

Similar skills

More from VectorSpaceLab/AREX-Skill

Related

Questions about Reactions Standardization