DiffDock Molecular Docking
K-Dense-AI/scientific-agent-skills
Predicts how small molecules bind to a protein with DiffDock, covering batch docking, pose ranking by confidence and checks on the results; not for binding affinity.
Generate molecular conformers with RDKit ETKDG, relax with MLIPs, and rank by energy with Boltzmann weighting.
Install Chem Conformer Search
$ npx skills add learningmatter-mit/AtomisticSkills --skill chem-conformer-search -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install learningmatter-mit/AtomisticSkills chem-conformer-search --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/learningmatter-mit/AtomisticSkills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/chem-conformer-search .claude/skills/chem-conformer-search && rm -rf skills-srcUse ~/.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/
Install the "chem-conformer-search" agent skill from https://github.com/learningmatter-mit/AtomisticSkills/tree/main/skills/chem-conformer-search into .claude/skills/chem-conformer-search/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "chem-conformer-search", 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 install https://github.com/learningmatter-mit/AtomisticSkills/tree/main/skills/chem-conformer-searchType 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.
$ npx skills add learningmatter-mit/AtomisticSkills --skill chem-conformer-search -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install learningmatter-mit/AtomisticSkills chem-conformer-search --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/learningmatter-mit/AtomisticSkills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/chem-conformer-search .agents/skills/chem-conformer-search && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "chem-conformer-search" agent skill from https://github.com/learningmatter-mit/AtomisticSkills/tree/main/skills/chem-conformer-search into .agents/skills/chem-conformer-search/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "chem-conformer-search", 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.
$ npx skills add learningmatter-mit/AtomisticSkills --skill chem-conformer-search -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install learningmatter-mit/AtomisticSkills chem-conformer-search --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/learningmatter-mit/AtomisticSkills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/chem-conformer-search .cursor/skills/chem-conformer-search && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "chem-conformer-search" agent skill from https://github.com/learningmatter-mit/AtomisticSkills/tree/main/skills/chem-conformer-search into .cursor/skills/chem-conformer-search/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "chem-conformer-search", 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 https://github.com/learningmatter-mit/AtomisticSkills.git --path skills/chem-conformer-search--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add learningmatter-mit/AtomisticSkills --skill chem-conformer-search -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install learningmatter-mit/AtomisticSkills chem-conformer-search --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/learningmatter-mit/AtomisticSkills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/chem-conformer-search .gemini/skills/chem-conformer-search && rm -rf skills-srcUse ~/.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/
Install the "chem-conformer-search" agent skill from https://github.com/learningmatter-mit/AtomisticSkills/tree/main/skills/chem-conformer-search into .gemini/skills/chem-conformer-search/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "chem-conformer-search", 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.
$ gh skill install learningmatter-mit/AtomisticSkills chem-conformer-searchInstalls 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).
$ npx skills add learningmatter-mit/AtomisticSkills --skill chem-conformer-search -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/learningmatter-mit/AtomisticSkills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/chem-conformer-search .github/skills/chem-conformer-search && rm -rf skills-srcUse ~/.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/
Install the "chem-conformer-search" agent skill from https://github.com/learningmatter-mit/AtomisticSkills/tree/main/skills/chem-conformer-search into .github/skills/chem-conformer-search/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "chem-conformer-search", 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.
$ npx skills add learningmatter-mit/AtomisticSkills --skill chem-conformer-search -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install learningmatter-mit/AtomisticSkills chem-conformer-search --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/learningmatter-mit/AtomisticSkills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/chem-conformer-search .opencode/skills/chem-conformer-search && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "chem-conformer-search" agent skill from https://github.com/learningmatter-mit/AtomisticSkills/tree/main/skills/chem-conformer-search into .opencode/skills/chem-conformer-search/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "chem-conformer-search", 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-conformer-search- GitHub stars
- 175
- Token cost
- ~1.3k tokens
- SKILL.md length
- 522 words
- Files
- 13 (incl. scripts)
- Skills in repo
- 129
- Repo updated
- First seen
- Licence
- MIT
At a glance
Generate molecular conformers with RDKit ETKDG, relax with MLIPs, and rank by energy with Boltzmann weighting.
- Works in 7 steps: Prerequisites → Methodology → Usage → …
- Tasks that involve Drug discovery and cheminformatics
- SKILL.md covers Goal, 1. Prerequisites, 2. Methodology and 3. Usage, plus 4 more sections
- Runs Python scripts from its folder
What it does
Chem Conformer Search is an agent skill from learningmatter-mit/AtomisticSkills. Generate molecular conformers with RDKit ETKDG, relax with MLIPs, and rank by energy with Boltzmann weighting.
Its SKILL.md is about 1.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 16 other files, including scripts (for example `examples/aspirin/README.md`, `examples/aspirin/conformer_results.json` and `examples/ibuprofen_kmeans/README.md`).
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-conformer-search”
Requirements
- Python 3
Workflow steps
7 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit 7f2d86d. 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.
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):
doi.orggithub.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 Conformer Search loads about 1.3k tokens when it runs. Until then it costs about 33 tokens; SKILL.md has 522 words of instructions outside code blocks.
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 7f2d86d, republished under its MIT licence (© learningmatter-mit). 522 words, ~1,316 tokens.
Download SKILL.mdSave it as
.claude/skills/chem-conformer-search/SKILL.md (or your agent's skills folder). This skill also uses 12 other files; get the full folder from GitHub.- name
- chem-conformer-search
- description
- Generate molecular conformers with RDKit ETKDG, relax with MLIPs, and rank by energy with Boltzmann weighting.
- metadata.category
- chemistry
- metadata.venv
- mlip
Molecular Conformer Search & Ranking
Goal
Generate a diverse ensemble of low-energy conformers for a given molecule. The workflow combines:
- Stochastic sampling using RDKit's ETKDG algorithm (Experimental Torsion Distance Geometry).
- High-accuracy relaxation using Machine Learning Interatomic Potentials (MLIPs) to get near-DFT quality geometries and energies.
- Deduplication and Boltzmann weighting to identify the most relevant conformers at finite temperature.
[!IMPORTANT] This skill is optimized for organic molecules and uses
MACE-OFF23models by default. For inorganic clusters, switch toMACE-OMATorMatGLmodels.
Recommended Models
- MACE-OFF23:
MACE-OFF23-small(default),MACE-OFF23-medium— trained on organic molecules (Env:mlip) - MACE-MH:
MACE-MH-1with headomol— multi-head model with molecular head (Env:mlip) - UMA:
uma-s-1p1with headomol— general molecular model (Env:fairchem)
1. Prerequisites
- Environment:
mlip(recommended as it includes bothmaceandrdkit; commands run throughvenv/run mlip ...). - Input: SMILES string or a structure file (
.xyz,.sdf,.mol2,.pdb).
2. Methodology
- Generation: Generate
Ninitial conformers using RDKit'sEmbedMultipleConfswith ETKDGv3. - Relaxation: Optimize the geometry of each conformer using the selected MLIP (fmax = 0.01 eV/Å).
- Deduplication/Clustering: Filter redundant conformers by simple RMSD thresholding (default), Hierarchical clustering, or K-Means clustering. Only the lowest-energy conformer in each cluster is kept.
- Ranking: Sort unique conformers by energy.
- Boltzmann Weighting: Calculate population probability $P_i$ at temperature $T$: $$P_i = \frac{e^{-(E_i - E_{min}) / k_B T}}{\sum_j e^{-(E_j - E_{min}) / k_B T}}$$
3. Usage
Basic Usage (SMILES)
Generate 30 conformers for a molecule (e.g., aspirin) and relax with MACE-OFF23:
${CLAUDE_SKILL_DIR}/../../venv/run mlip python ${CLAUDE_SKILL_DIR}/scripts/conformer_search.py \
--smiles "CC(=O)Oc1ccccc1C(=O)O" \
--num_conformers 30 \
--output_dir research/aspirin_conformersAdvanced Usage (Structure File + Options)
${CLAUDE_SKILL_DIR}/../../venv/run mlip python ${CLAUDE_SKILL_DIR}/scripts/conformer_search.py \
--structure my_molecule.sdf \
--num_conformers 100 \
--rms_threshold 0.5 \
--dedup_threshold 0.1 \
--temperature 298.15 \
--model_type mace \
--model_name MACE-OFF23-small \
--device cuda \
--output_dir research/my_molecule_searchKey Parameters
| Argument | Default | Description |
|---|---|---|
--smiles | - | SMILES string of the molecule |
--structure | - | Path to input structure file (alternative to SMILES) |
--num_conformers | 50 | Number of initial conformers to generate with RDKit |
--rms_threshold | 0.2 | RDKit pruning threshold (Å) to discard similar initial conformers |
--clustering | rmsd | Method to filter conformers: rmsd, hierarchical, or kmeans |
--dedup_threshold | 0.1 | Post-relaxation RMSD threshold (Å) to merge identical conformers or cut for hierarchical |
--num_clusters | 5 | Number of clusters if --clustering kmeans is used |
--energy_threshold | 0.5 | Max energy above global minimum (eV) to keep before RMSD comparison. Set to 0 to disable |
--fmax | 0.01 | Force convergence criterion for relaxation (eV/Å) |
--temperature | 298.15 | Temperature (K) for Boltzmann weighting |
--model_type | mace | MLIP backend (mace, matgl, fairchem) |
--model_name | MACE-OFF23-small | Specific model checkpoint to use |
Show full SKILL.md (155 more words)Show less
4. Output Files
The output directory will contain:
conformer_results.json: A summary file containing:- List of unique conformers with their energies, relative energies, and Boltzmann weights.
- Paths to the corresponding XYZ files.
- Metadata (model used, parameters).
conf_000.xyz,conf_001.xyz, ...: The relaxed structures of the unique conformers, sorted by energy (000 is the global minimum found).
5. Examples
See examples/aspirin for a complete example run on Acetylsalicylic acid.
6. Constraints
- Environment: Use the environment matching the chosen model:
mlip(MACE or MatGL) orfairchem(FairChem/UMA). All include RDKit. - Input: Either
--smilesor--structuremust be provided, but not both. - Molecule Type: Optimized for organic molecules. For inorganic clusters, switch to
MACE-OMATorMatGLmodels. - Non-periodic: All conformers are treated as non-periodic (isolated molecules).
7. References
- Riniker, S.; Landrum, G. A., "Better Informed Distance Geometry: Using What We Know To Improve Conformation Generation", J. Chem. Inf. Model., 2015, 55, 2562. DOI
Author: Bowen Deng Contact: GitHub @learningmatter-mit
© learningmatter-mit, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 12 other files (scripts) in skills/chem-conformer-search of learningmatter-mit/AtomisticSkills.
- SKILL.md
- examples/aspirin/README.md
- examples/aspirin/conf_000.xyz
- examples/aspirin/conf_001.xyz
- examples/aspirin/conformer_results.json
- examples/ibuprofen_kmeans/README.md
- examples/ibuprofen_kmeans/conf_000.xyz
- examples/ibuprofen_kmeans/conf_001.xyz
- examples/ibuprofen_kmeans/conf_002.xyz
- examples/ibuprofen_kmeans/conf_003.xyz
- examples/ibuprofen_kmeans/conf_004.xyz
- examples/ibuprofen_kmeans/conformer_results.json
- scripts/conformer_search.py
Open the folder on GitHubat commit 7f2d86d
Compare with similar skills
Chem Conformer Search 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Chem Conformer Search this skilllearningmatter-mit/AtomisticSkills | 175 | — | ~1.3k | Automated safety check: Pass | MIT | |
| DiffDock Molecular DockingK-Dense-AI/scientific-agent-skills | 48k | 1 repos | ~3k | Automated safety check: Notes | MIT | |
| Edu Chem Reactionwy51ai/edulab | 1.4k | — | ~1.2k | Automated safety check: Pass | Apache-2.0 | |
| Biopipelineslocbp-uzh/biopipelines | 109 | — | ~2.4k | Automated safety check: Pass | MIT | |
| RDKit Cheminformatics Practicesaiming-lab/AutoResearchClaw | 15k | — | ~708 | Automated safety check: Pass | MIT | |
| Rowanlamm-mit/scienceclaw | 244 | 4 repos | ~3.1k | Automated safety check: Warn | Proprietary |
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Related
Works with
Categories
Questions about Chem Conformer Search
What does Chem Conformer Search do?
Generate molecular conformers with RDKit ETKDG, relax with MLIPs, and rank by energy with Boltzmann weighting. Chem Conformer Search is an agent skill from learningmatter-mit/AtomisticSkills. Generate molecular conformers with RDKit ETKDG, relax with MLIPs, and rank by energy with Boltzmann weighting.
When should I use Chem Conformer Search?
Chem Conformer Search fits situations like: tasks that involve Drug discovery and cheminformatics.
How do I install Chem Conformer Search in Claude Code?
Run `npx skills add learningmatter-mit/AtomisticSkills --skill chem-conformer-search -a claude-code`. Or copy the skill folder (skills/chem-conformer-search in learningmatter-mit/AtomisticSkills) into .claude/skills/chem-conformer-search in your project. Claude Code loads it when a task matches its description.
How do I install Chem Conformer Search in Codex?
Run `npx skills add learningmatter-mit/AtomisticSkills --skill chem-conformer-search -a codex`. Or copy the skill folder (skills/chem-conformer-search in learningmatter-mit/AtomisticSkills) into .agents/skills/chem-conformer-search in your project. Codex loads it when a task matches its description.
Can I use Chem Conformer Search 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-conformer-search -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-conformer-search, .gemini/skills/chem-conformer-search, .github/skills/chem-conformer-search and .opencode/skills/chem-conformer-search in your project.
What does Chem Conformer Search need to run?
Going by SKILL.md and its folder, Chem Conformer Search needs Python for the scripts in its folder. Our summary lists: Python 3.
Does Chem Conformer Search access the network?
SKILL.md names 2 domains. As links in the text: doi.org and github.com. This is read from the text; nothing was executed.
Is Chem Conformer Search 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 Conformer Search use?
Chem Conformer Search 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 Conformer Search use?
About 1.3k tokens (SKILL.md is roughly 5.3k 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 Conformer Search?
Skills that share tags, products or a category with Chem Conformer Search: 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 Cheminformatics Practices (aiming-lab/AutoResearchClaw, 15k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Chem Conformer Search?
learningmatter-mit (a GitHub organization) maintains it in learningmatter-mit/AtomisticSkills, which has 175 GitHub stars. The repository holds 129 skills in this directory. The repository was last updated on October 6, 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.