Agent skill

Chem Bond Dissociation

by learningmatter-mit in learningmatter-mit/AtomisticSkills

Calculate homolytic and heterolytic bond dissociation energies (BDEs) for all single bonds in a molecule using MLIPs with RDKit fragmentation.

MITAuto-check passedResearch & Science

Install Chem Bond Dissociation

skills CLI

$ npx skills add learningmatter-mit/AtomisticSkills --skill chem-bond-dissociation -a claude-code

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

GitHub CLI

$ gh skill install learningmatter-mit/AtomisticSkills chem-bond-dissociation --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/learningmatter-mit/AtomisticSkills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/chem-bond-dissociation .claude/skills/chem-bond-dissociation && 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 "chem-bond-dissociation" agent skill from https://github.com/learningmatter-mit/AtomisticSkills/tree/main/skills/chem-bond-dissociation into .claude/skills/chem-bond-dissociation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "chem-bond-dissociation", 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/learningmatter-mit/AtomisticSkills/tree/main/skills/chem-bond-dissociation

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 learningmatter-mit/AtomisticSkills --skill chem-bond-dissociation -a codex

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

GitHub CLI

$ gh skill install learningmatter-mit/AtomisticSkills chem-bond-dissociation --agent codex

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

Manual copy

$ git clone --depth 1 https://github.com/learningmatter-mit/AtomisticSkills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/chem-bond-dissociation .agents/skills/chem-bond-dissociation && 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 "chem-bond-dissociation" agent skill from https://github.com/learningmatter-mit/AtomisticSkills/tree/main/skills/chem-bond-dissociation into .agents/skills/chem-bond-dissociation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "chem-bond-dissociation", 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 learningmatter-mit/AtomisticSkills --skill chem-bond-dissociation -a cursor

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

GitHub CLI

$ gh skill install learningmatter-mit/AtomisticSkills chem-bond-dissociation --agent cursor

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

Manual copy

$ git clone --depth 1 https://github.com/learningmatter-mit/AtomisticSkills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/chem-bond-dissociation .cursor/skills/chem-bond-dissociation && 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 "chem-bond-dissociation" agent skill from https://github.com/learningmatter-mit/AtomisticSkills/tree/main/skills/chem-bond-dissociation into .cursor/skills/chem-bond-dissociation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "chem-bond-dissociation", 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/learningmatter-mit/AtomisticSkills.git --path skills/chem-bond-dissociation

--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 learningmatter-mit/AtomisticSkills --skill chem-bond-dissociation -a gemini-cli

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

GitHub CLI

$ gh skill install learningmatter-mit/AtomisticSkills chem-bond-dissociation --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/learningmatter-mit/AtomisticSkills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/chem-bond-dissociation .gemini/skills/chem-bond-dissociation && 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 "chem-bond-dissociation" agent skill from https://github.com/learningmatter-mit/AtomisticSkills/tree/main/skills/chem-bond-dissociation into .gemini/skills/chem-bond-dissociation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "chem-bond-dissociation", 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 learningmatter-mit/AtomisticSkills chem-bond-dissociation

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 learningmatter-mit/AtomisticSkills --skill chem-bond-dissociation -a github-copilot

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

Manual copy

$ git clone --depth 1 https://github.com/learningmatter-mit/AtomisticSkills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/chem-bond-dissociation .github/skills/chem-bond-dissociation && 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 "chem-bond-dissociation" agent skill from https://github.com/learningmatter-mit/AtomisticSkills/tree/main/skills/chem-bond-dissociation into .github/skills/chem-bond-dissociation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "chem-bond-dissociation", 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 learningmatter-mit/AtomisticSkills --skill chem-bond-dissociation -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 learningmatter-mit/AtomisticSkills chem-bond-dissociation --agent opencode

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

Manual copy

$ git clone --depth 1 https://github.com/learningmatter-mit/AtomisticSkills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/chem-bond-dissociation .opencode/skills/chem-bond-dissociation && 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 "chem-bond-dissociation" agent skill from https://github.com/learningmatter-mit/AtomisticSkills/tree/main/skills/chem-bond-dissociation into .opencode/skills/chem-bond-dissociation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "chem-bond-dissociation", 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: chem-bond-dissociation
GitHub stars: 176
Token cost: ~2.5k tokens
SKILL.md length: 822 words
Files: 61 (incl. scripts)
Skills in repo: 129
Repo updated: Oct 7, 2026
First seen: Oct 7, 2026
Licence: MIT

At a glance

Calculate homolytic and heterolytic bond dissociation energies (BDEs) for all single bonds in a molecule using MLIPs with RDKit fragmentation.

Works in 6 steps: Prerequisites → Choosing a Foundation Potential → Calculation Workflow → …
Tasks that involve Drug discovery and cheminformatics
SKILL.md covers Goal, Background, 1. Prerequisites and 2. Choosing a Foundation…, plus 5 more sections

What it does

Chem Bond Dissociation is an agent skill from learningmatter-mit/AtomisticSkills. Calculate homolytic and heterolytic bond dissociation energies (BDEs) for all single bonds in a molecule using MLIPs with RDKit fragmentation.

Its SKILL.md is about 2.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 62 other files, including scripts (for example `examples/README.md`, `examples/ethanol_mace_off23_small/README.md` and `examples/ethanol_mace_off23_small/bde_results.json`).

It sits in Research & Science, covering Drug discovery and cheminformatics. It works with RDKit. The repository describes itself as: Integrating AtomisticSkills into Agentic IDEs (Cursor, Claude Code, Codex, Google Antigravity, Hermes Agent, etc). The licence is MIT.

When your agent uses it

Tasks that involve Drug discovery and cheminformatics

Example prompts

“/chem-bond-dissociation”

Requirements

Python 3

Workflow steps

6 steps, taken from the step headings in SKILL.md.

Prerequisites
Choosing a Foundation Potential
Calculation Workflow
Output Files
Examples
Constraints

What it can do on your machine

Read from SKILL.md and the folder at commit 6257444. 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/, which the agent can run.
From the folder's file list and the shell code blocks in SKILL.md.
Network
Links to these hosts (documentation or services it may open):
- bde.ml.nrel.gov
- github.com
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

Chem Bond Dissociation loads about 2.5k tokens when it runs. Until then it costs about 41 tokens; SKILL.md has 822 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~41
When it runs · the whole SKILL.md, loaded when a task matches: ~2.5k

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 learningmatter-mit/AtomisticSkills at commit 6257444, republished under its MIT licence (© learningmatter-mit). 822 words, ~2,475 tokens.

Download SKILL.mdSave it as .claude/skills/chem-bond-dissociation/SKILL.md (or your agent's skills folder). This skill also uses 60 other files; get the full folder from GitHub.

name: chem-bond-dissociation
description: Calculate homolytic and heterolytic bond dissociation energies (BDEs) for all single bonds in a molecule using MLIPs with RDKit fragmentation.
metadata.category: chemistry
metadata.venv: fairchem, mlip

Bond Dissociation Energy Skill

Goal

Calculate the homolytic and/or heterolytic bond dissociation energy (BDE) for each single bond in a molecule using Machine Learning Interatomic Potentials (MLIPs).

Homolytic BDE (radical fragments): $$\text{BDE}_\text{homo}(A{-}B) = E(A\bullet) + E(B\bullet) - E(A{-}B)$$

Heterolytic BDE (ionic fragments, minimum over both polarity variants): $$\text{BDE}_\text{hetero}(A{-}B) = \min!\bigl(E(A^+)+E(B^-),; E(A^-)+E(B^+)\bigr) - E(A{-}B)$$

[!IMPORTANT] This skill computes BDEs by relaxing both the intact molecule and fragments with an MLIP. For purpose-trained GNN models that predict BDE directly from SMILES (MAE ~0.6 kcal/mol), consider ALFABET or BonDNet instead.

Background

BDE is a fundamental thermodynamic quantity that determines:

Drug metabolism: CYP450 enzymes abstract H from the weakest C–H bond
Electrolyte stability: Which bonds break first under electrochemical voltage
Combustion chemistry: Rate-determining bond-breaking steps in fuel oxidation
Polymer degradation: Weakest links in polymer backbone chains

A 2024 study (Zubatyuk et al., JCTC) demonstrated that MACE potentials achieve BDE RMSE of 1.37 kcal/mol for aliphatic C–H bonds in drug-like molecules, outperforming semi-empirical methods and ALFABET for BDE ranking.

1. Prerequisites

Environment: mlip (includes RDKit, ASE, and MACE; commands run through venv/run mlip ...)
Input: SMILES string or structure file (.sdf, .mol2)
RDKit: Required for bond identification and molecular fragmentation

2. Choosing a Foundation Potential

Refer to the foundation-potentials skill for model selection.

[!IMPORTANT] Model requirements by cleavage mode:

Mode Recommended model supports_charge_spin Validated?
homolytic MACE-OFF23-small/medium/large Not required ✅
heterolytic or both MACE-OMOL-extra-large (env: mlip) ✅ Required ✅
heterolytic or both MACE-MH-1 with omol head (env: mlip) ✅ Required ✅
heterolytic or both FairChem uma-s-1p1 with --task_name omol (env: fairchem) ✅ Required ✅

Setting charge/spin on MACE models: use atoms.info["charge"] and atoms.info["spin"] (the calculator's default info_keys maps "charge" → total_charge / "spin" → total_spin). Both MACE-OMOL and MACE-MH use joint_embedding to condition the network on these scalars.

If you request --cleavage both with a model that does not support charge/spin, the skill will log a warning and silently fall back to homolytic-only. Using --cleavage heterolytic with an unsupported model raises an error.

Note on single-atom fragments: When a bond produces a bare H (or other single atom), heterolytic BDE is automatically skipped — neither MACE nor FairChem UMA has signed single-atom energies (only neutral H, C, N, O… are in the reference tables).

Mode	Recommended model	`supports_charge_spin`	Validated?
`homolytic`	`MACE-OFF23-small/medium/large`	Not required	✅
`heterolytic` or `both`	`MACE-OMOL-extra-large` (env: `mlip`)	✅ Required	✅
`heterolytic` or `both`	`MACE-MH-1` with omol head (env: `mlip`)	✅ Required	✅
`heterolytic` or `both`	FairChem `uma-s-1p1` with `--task_name omol` (env: `fairchem`)	✅ Required	✅

3. Calculation Workflow

Step 1: Provide a molecule

bash

# SMILES input (most common)
--smiles "CCO"

# Or from a structure file
--structure molecule.sdf

Step 2: Run BDE calculation

Homolytic only (default, no charge/spin needed):

bash

${CLAUDE_SKILL_DIR}/../../venv/run mlip python ${CLAUDE_SKILL_DIR}/scripts/calculate_bde.py \
    --smiles CCO \
    --all_bonds \
    --cleavage homolytic \
    --model_type mace \
    --model_name MACE-OFF23-small \
    --output_dir research/my_folder/bde_results

Both homolytic and heterolytic (MACE-OMOL):

bash

${CLAUDE_SKILL_DIR}/../../venv/run mlip python ${CLAUDE_SKILL_DIR}/scripts/calculate_bde.py \
    --smiles CCO \
    --all_bonds \
    --cleavage both \
    --model_type mace \
    --model_name MACE-OMOL-extra-large \
    --output_dir research/my_folder/bde_results_both

Both homolytic and heterolytic (FairChem UMA omol):

bash

${CLAUDE_SKILL_DIR}/../../venv/run fairchem python ${CLAUDE_SKILL_DIR}/scripts/calculate_bde.py \
    --smiles CCO \
    --all_bonds \
    --cleavage both \
    --model_type fairchem \
    --model_name uma-s-1p1 \
    --task_name omol \
    --output_dir research/my_folder/bde_results_both

Heterolytic only with FairChem UMA:

bash

${CLAUDE_SKILL_DIR}/../../venv/run fairchem python ${CLAUDE_SKILL_DIR}/scripts/calculate_bde.py \
    --smiles CCO \
    --all_bonds \
    --cleavage heterolytic \
    --model_type fairchem \
    --model_name uma-s-1p1 \
    --task_name omol \
    --output_dir research/my_folder/bde_hetero

Key Parameters

Argument	Default	Description
`--smiles`	—	SMILES string of the molecule
`--structure`	—	Path to structure file (`.sdf`, `.mol2`)
`--bond`	—	Specific bond as atom indices `"i-j"` (0-indexed)
`--all_bonds`	`True`	Compute BDE for all single bonds
`--include_h_bonds`	`False`	Include X–H bonds
`--cleavage`	`homolytic`	`homolytic`, `heterolytic`, or `both`
`--model_type`	`mace`	MLIP backend (`mace`, `fairchem`)
`--model_name`	auto	Model checkpoint (default: `MACE-OFF23-small` for homolytic; `uma-s-1p1` for hetero/both)
`--task_name`	—	Task head for multi-task models (e.g. `omol` for FairChem UMA)
`--fmax`	`0.01`	Force convergence for relaxation (eV/Å)
`--output_dir`	required	Output directory

Show full SKILL.md (351 more words)Show less

4. Output Files

bde_results.json — Full results including:
- metadata: model name, cleavage mode, supports_charge_spin, SMILES, etc.
- intact_energy_eV: Energy of the relaxed intact molecule
- bonds: List of per-bond results:
  - bde_eV, bde_kJ_mol, bde_kcal_mol: Homolytic BDE (if computed)
  - heterolytic_bde_eV, heterolytic_bde_kJ_mol, heterolytic_bde_kcal_mol: Best heterolytic BDE (if computed)
  - heterolytic_best_variant: Which polarity won ("frag1+ / frag2-" or "frag1- / frag2+")
  - heterolytic_variants: Raw results for both polarity variants
- weakest_bond_homolytic, weakest_bond_heterolytic: Summary of weakest bonds
- bonds_ranked_by_homolytic_bde, bonds_ranked_by_heterolytic_bde: Sorted tables
intact_relaxed.xyz: Relaxed intact molecule
frag_bond{N}_homo_{1,2}.xyz: Homolytic radical fragments
frag_bond{N}_hetero_pos_neg_{1,2}.xyz: Heterolytic cation/anion fragments (variant A)
frag_bond{N}_hetero_neg_pos_{1,2}.xyz: Heterolytic anion/cation fragments (variant B)

5. Examples

Example	Model	Cleavage	Notes
`examples/ethanol_mace_off23_small/`	MACE-OFF23-small	`homolytic`	Standard homolytic BDE for ethanol; includes H bonds
`examples/methanol_mace_omol_both/`	MACE-OMOL-extra-large	`both`	Homo + heterolytic for methanol; C–O hetero = 90 vs homo = 143 kcal/mol
`examples/methanol_uma_omol_both/`	FairChem UMA omol	`both`	Homo + heterolytic for methanol; C–O hetero = 157 vs homo = 126 kcal/mol

Ethanol — Homolytic BDE (MACE-OFF23)

bash

${CLAUDE_SKILL_DIR}/../../venv/run mlip python ${CLAUDE_SKILL_DIR}/scripts/calculate_bde.py \
    --smiles CCO \
    --all_bonds \
    --include_h_bonds \
    --cleavage homolytic \
    --model_type mace \
    --model_name MACE-OFF23-small \
    --output_dir ${CLAUDE_SKILL_DIR}/examples/ethanol_mace_off23_small

Methanol — Both Homo and Heterolytic BDE (FairChem UMA omol)

bash

${CLAUDE_SKILL_DIR}/../../venv/run fairchem python ${CLAUDE_SKILL_DIR}/scripts/calculate_bde.py \
    --smiles CO \
    --all_bonds \
    --include_h_bonds \
    --cleavage both \
    --model_type fairchem \
    --model_name uma-s-1p1 \
    --task_name omol \
    --output_dir ${CLAUDE_SKILL_DIR}/examples/methanol_uma_omol_both

Experimental BDEs for ethanol (Blanksby & Ellison, 2003):

Bond	Experimental BDE (kcal/mol)
O–H	~104
C–H (methyl)	~101
C–H (methylene)	~95
C–C	~85
C–O	~92

6. Constraints

Radical spin states: For homolytic BDE, MLIPs are generally "electron-agnostic" and treat fragments as neutral regardless of spin state. BDE ranking is typically more reliable than absolute values.
Ionic states: Heterolytic BDE requires a charge/spin-aware model (supports_charge_spin=True). Validated: MACE-OMOL, MACE-MH (omol head), and FairChem UMA omol. These models use atoms.info["charge"] and atoms.info["spin"] to condition on the ionic state. Models without this flag raise an error for --cleavage heterolytic.
Ring bonds: Breaking bonds in rings produces a single open-chain diradical. The script will warn and skip ring bonds.
Accuracy: Expect ~2–5 kcal/mol error for homolytic BDEs with MACE-OFF23. Heterolytic accuracy is less benchmarked with current MLIPs.
Environments:
- mlip for MACE models
- fairchem for FairChem/UMA models

References

Blanksby & Ellison, "Bond Dissociation Energies of Organic Molecules", Acc. Chem. Res. 2003, 36, 255.
St. John et al., "Prediction of organic homolytic bond dissociation enthalpies at near chemical accuracy with sub-second computational cost", Nat. Commun. 2020, 11, 2328. (ALFABET)
Zubatyuk et al., "A Transferable MACE Potential for Open- and Closed-Shell Drug-Like Molecules", J. Chem. Theory Comput. 2024.

Author: Bowen Deng Contact: GitHub @learningmatter-mit

Files

SKILL.md and 60 other files (scripts) in skills/chem-bond-dissociation of learningmatter-mit/AtomisticSkills.

SKILL.md
examples/README.md
examples/ethanol_mace_off23_small/README.md
examples/ethanol_mace_off23_small/bde_results.json
examples/ethanol_mace_off23_small/frag_bond0_1.xyz
examples/ethanol_mace_off23_small/frag_bond0_2.xyz
examples/ethanol_mace_off23_small/frag_bond1_1.xyz
examples/ethanol_mace_off23_small/frag_bond1_2.xyz
examples/ethanol_mace_off23_small/frag_bond2_1.xyz
examples/ethanol_mace_off23_small/frag_bond2_2.xyz
examples/ethanol_mace_off23_small/frag_bond3_1.xyz
examples/ethanol_mace_off23_small/frag_bond3_2.xyz
examples/ethanol_mace_off23_small/frag_bond4_1.xyz
examples/ethanol_mace_off23_small/frag_bond4_2.xyz
examples/ethanol_mace_off23_small/frag_bond5_1.xyz
examples/ethanol_mace_off23_small/frag_bond5_2.xyz
examples/ethanol_mace_off23_small/frag_bond6_1.xyz
examples/ethanol_mace_off23_small/frag_bond6_2.xyz
examples/ethanol_mace_off23_small/frag_bond7_1.xyz
… and 42 more

Open the folder on GitHubat commit 6257444

Compare with similar skills

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148 GitHub starsUsed in 1 repo~2.3k tokens
Research & ScienceAuto-check passed
RDKit Cheminformatics Practices
aiming-lab/AutoResearchClaw
Reference guide for working with molecules in RDKit: reading SMILES and SDF files, computing descriptors and fingerprints, and searching substructures.
15k GitHub stars~708 tokensUpdated 1 mo ago
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Questions about Chem Bond Dissociation

What does Chem Bond Dissociation do?

Calculate homolytic and heterolytic bond dissociation energies (BDEs) for all single bonds in a molecule using MLIPs with RDKit fragmentation. Chem Bond Dissociation is an agent skill from learningmatter-mit/AtomisticSkills. Calculate homolytic and heterolytic bond dissociation energies (BDEs) for all single bonds in a molecule using MLIPs with RDKit fragmentation.

When should I use Chem Bond Dissociation?

Chem Bond Dissociation fits situations like: tasks that involve Drug discovery and cheminformatics.

How do I install Chem Bond Dissociation in Claude Code?

Run `npx skills add learningmatter-mit/AtomisticSkills --skill chem-bond-dissociation -a claude-code`. Or copy the skill folder (skills/chem-bond-dissociation in learningmatter-mit/AtomisticSkills) into .claude/skills/chem-bond-dissociation in your project. Claude Code loads it when a task matches its description.

How do I install Chem Bond Dissociation in Codex?

Run `npx skills add learningmatter-mit/AtomisticSkills --skill chem-bond-dissociation -a codex`. Or copy the skill folder (skills/chem-bond-dissociation in learningmatter-mit/AtomisticSkills) into .agents/skills/chem-bond-dissociation in your project. Codex loads it when a task matches its description.

Can I use Chem Bond Dissociation 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 learningmatter-mit/AtomisticSkills --skill chem-bond-dissociation -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/chem-bond-dissociation, .gemini/skills/chem-bond-dissociation, .github/skills/chem-bond-dissociation and .opencode/skills/chem-bond-dissociation in your project.

What does Chem Bond Dissociation need to run?

SKILL.md names no scripts, command-line tools or credentials: Chem Bond Dissociation is instructions for the agent only. Our summary lists: Python 3.

Does Chem Bond Dissociation access the network?

SKILL.md names 2 domains. As links in the text: bde.ml.nrel.gov and github.com. This is read from the text; nothing was executed.

Is Chem Bond Dissociation 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 Chem Bond Dissociation use?

Chem Bond Dissociation is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Chem Bond Dissociation use?

About 2.5k tokens (SKILL.md is roughly 9.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Chem Bond Dissociation?

Skills that share tags, products or a category with Chem Bond Dissociation: DiffDock Molecular Docking (K-Dense-AI/scientific-agent-skills, 48k stars), Edu Chem Reaction (wy51ai/edulab, 1.4k stars), Biopipelines (locbp-uzh/biopipelines, 109 stars) and RDKit Conformer Generator (jinzhezenggroup/computational-chemistry-agent-skills, 148 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Chem Bond Dissociation?

learningmatter-mit (a GitHub organization) maintains it in learningmatter-mit/AtomisticSkills, which has 176 GitHub stars. The repository holds 129 skills in this directory. The repository was last updated on October 7, 2026.

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

Install Chem Bond Dissociation

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

Bond Dissociation Energy Skill

Goal

Background

1. Prerequisites

2. Choosing a Foundation Potential

3. Calculation Workflow

Step 1: Provide a molecule

Step 2: Run BDE calculation

Key Parameters

4. Output Files

5. Examples

Ethanol — Homolytic BDE (MACE-OFF23)

Methanol — Both Homo and Heterolytic BDE (FairChem UMA omol)

6. Constraints

References

Files

Compare with similar skills

Similar skills

More from learningmatter-mit/AtomisticSkills

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Questions about Chem Bond Dissociation