Agent skill

Docking Tools

Molecular docking workflow guide and reusable pipeline template for AutoDock Vina, Open Babel, and PyMOL.

Apache-2.0Auto-check passedResearch & Science

Install Docking Tools

skills CLI

$ npx skills add DrugClaw/DrugClaw --skill docking-tools -a claude-code

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

GitHub CLI

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

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 DrugClaw/DrugClaw --skill docking-tools -a codex

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

GitHub CLI

$ gh skill install DrugClaw/DrugClaw docking-tools --agent codex

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

Manual copy

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

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

GitHub CLI

$ gh skill install DrugClaw/DrugClaw docking-tools --agent cursor

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

Manual copy

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

--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 DrugClaw/DrugClaw --skill docking-tools -a gemini-cli

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

GitHub CLI

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

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 DrugClaw/DrugClaw --skill docking-tools -a github-copilot

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

Manual copy

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

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

Manual copy

$ git clone --depth 1 https://github.com/DrugClaw/DrugClaw.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/pharma/docking-tools .opencode/skills/docking-tools && 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 "docking-tools" agent skill from https://github.com/DrugClaw/DrugClaw/tree/main/skills/pharma/docking-tools into .opencode/skills/docking-tools/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "docking-tools", 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: docking-tools
GitHub stars: 125
Token cost: ~2.1k tokens
SKILL.md length: 666 words
Files: 4
Skills in repo: 25
Repo updated: Mar 23, 2026
First seen: Oct 7, 2026
Licence: Apache-2.0

At a glance

Molecular docking workflow guide and reusable pipeline template for AutoDock Vina, Open Babel, and PyMOL.

Works in 3 steps: co-crystal ligand coordinates → active-site residue coordinates → whole-structure bounding box
Tasks that involve Drug discovery and cheminformatics
SKILL.md covers Runtime Requirements, Preferred Workflow, Fast Start and Manifest Guidance, plus 4 more sections
Runs Python scripts from its folder; calls python3

What it does

Docking Tools is an agent skill from DrugClaw/DrugClaw. Molecular docking workflow guide and reusable pipeline template for AutoDock Vina, Open Babel, and PyMOL.

Its SKILL.md is about 2.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files (for example `templates/README.md`, `templates/docking_manifest.example.json` and `templates/docking_workflow.py`).

It sits in Research & Science, covering Drug discovery and cheminformatics. The repository describes itself as: 💊 AI Research Assistant for Accelerated Drug Discovery. 🦞. The licence is Apache-2.0.

When your agent uses it

Tasks that involve Drug discovery and cheminformatics

Example prompts

“/docking-tools”

Requirements

Python 3
Docker

Workflow steps

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

co-crystal ligand coordinates
active-site residue coordinates
whole-structure bounding box

What it can do on your machine

Read from SKILL.md and the folder at commit 960a6e0. 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 script files (Python), which the agent can run.
Shell commands in SKILL.md call:
- python3
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

Docking Tools loads about 2.1k tokens when it runs. Until then it costs about 30 tokens; SKILL.md has 666 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~30
When it runs · the whole SKILL.md, loaded when a task matches: ~2.1k

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); files beside SKILL.md are not scanned.

SKILL.md

The full file from DrugClaw/DrugClaw at commit 960a6e0, republished under its Apache-2.0 licence (© DrugClaw). 666 words, ~2,089 tokens.

Download SKILL.mdSave it as .claude/skills/docking-tools/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.

name: docking-tools
description: Molecular docking workflow guide and reusable pipeline template for AutoDock Vina, Open Babel, and PyMOL.
source: drugclaw
updated_at: 2026-03-10

Docking Tools

Use this skill when the user asks to:

dock a ligand, compound, or drug against a receptor
estimate binding poses or affinities
inspect a binding site or ligand contacts
render docking poses or interaction figures
batch-screen ligands and summarize docking rankings

DrugClaw does not ship a native docking engine module. This skill packages a reusable non-GUI docking workflow into a CLI template under templates/.

Runtime Requirements

The workflow assumes the runtime provides:

obabel
vina
pymol
pdbfixer for receptor cleanup and protonation
Python modules used by the fuller docking and downstream chemistry workflow: openbabel, deepchem, pdbfixer, pyscf, rdkit, psutil, rsa, bs4, requests, pandas, matplotlib, seaborn, sklearn, Bio

Check first:

bash

which obabel vina pymol pdbfixer || true
vina --version || true
obabel -V || true
python3 - <<'PY'
mods = ["openbabel", "deepchem", "pdbfixer", "pyscf", "rdkit", "psutil", "rsa", "bs4", "requests", "pandas", "matplotlib", "seaborn", "sklearn", "Bio"]
for name in mods:
    try:
        __import__(name)
        print(f"{name}: ok")
    except Exception as exc:
        print(f"{name}: missing ({exc})")
PY

If these tools are missing, say so immediately. Prefer the unified science sandbox image documented in docker/drug-sandbox.Dockerfile and docs/operations/science-runtime.md.

Preferred Workflow

Use the bundled template instead of rebuilding the pipeline ad hoc.

Bundled assets:

templates/docking_workflow.py
templates/docking_manifest.example.json
templates/README.md

The template ports these usable desktop-tool capabilities into DrugClaw:

ligand download from PubChem, ChEMBL, ZINC, TCMSP, local DrugBank exports, and the online DrugBank discovery API
receptor download from RCSB PDB, AlphaFold DB
SMILES and sequence-driven structure generation
receptor preprocessing with pdbfixer -> obabel
ligand preprocessing with 2D-to-3D generation, forcefield minimization, and biomolecule fallbacks
automatic search-box inference from co-crystal ligands, active residues, or bounding boxes
batch AutoDock Vina docking
PDBQT-to-PDB complex assembly while preserving ligand coordinates
CSV, heatmap, evaluation note, and paper-style markdown report generation
optional PyMOL rendering for top hits
optional heuristic ML rescoring when descriptors are available
optional downstream DeepChem featurization or PySCF sanity checks outside the core docking pipeline
optional chemistry post-processing with ADMET, ligand-only QSAR models, structure-aware affinity scoring, and virtual-screen reranking through chem-tools
direct handoff from docked complexes into chem-tools/templates/protein_ligand_affinity.py for structure-aware affinity scoring

Scope boundary:

port the computational workflow
do not port the original GUI, installer wizard, or license/device-fingerprint logic

Fast Start

From the skill directory or a copied template workspace:

bash

python3 templates/docking_workflow.py init-manifest -o docking_manifest.json
python3 templates/docking_workflow.py doctor --manifest docking_manifest.json
python3 templates/docking_workflow.py run --manifest docking_manifest.json

doctor now fails on dependencies that the current manifest actually requires. Use --strict when you also want optional plotting and chemistry extras audited. If the manifest uses drugbank ligands or chem_postprocess, the sibling chem-tools/templates bundle must also be present; doctor now checks that explicitly.

Incremental execution:

bash

python3 templates/docking_workflow.py fetch --manifest docking_manifest.json
python3 templates/docking_workflow.py prepare --manifest docking_manifest.json
python3 templates/docking_workflow.py box --manifest docking_manifest.json
python3 templates/docking_workflow.py dock --manifest docking_manifest.json
python3 templates/docking_workflow.py analyze --manifest docking_manifest.json
python3 templates/docking_workflow.py render --manifest docking_manifest.json --top-n 5

Show full SKILL.md (308 more words)Show less

Manifest Guidance

Use templates/docking_manifest.example.json as the base.

Supported input styles include:

ligand source: smiles, local, pubchem, chembl, zinc, tcmsp, drugbank, auto
receptor source: local, pdb, alphafold, peptide, protein, protein_sequence, nucleic, nucleic_sequence, auto

For drugbank ligands, set either settings.drugbank_catalog to a local DrugBank CSV, TSV, JSON, or XML export, or configure settings.drugbank_api_key / settings.drugbank_api_token for online lookup. The fetch stage will save both the exported structure and a per-drug JSON property file under inputs/ligands/.

Manual box override example:

json

{
  "box": {
    "mode": "manual",
    "center": [10.5, -3.2, 22.1],
    "size": [24, 24, 24]
  }
}

If box is omitted, the template tries:

co-crystal ligand coordinates
active-site residue coordinates
whole-structure bounding box

Optional chemistry post-processing block:

json

{
  "chem_postprocess": {
    "enabled": true,
    "run_admet": true,
    "run_virtual_screen": true,
    "affinity_model": "./models/affinity.joblib",
    "structure_affinity_model": "./models/protein_affinity.joblib",
    "bioactivity_model": "./models/bioactivity.joblib",
    "affinity_direction": "higher-better",
    "top_n": 25,
    "weights": {
      "affinity": 0.35,
      "activity": 0.35,
      "admet": 0.20,
      "docking": 0.10
    }
  }
}

When this block is enabled, analyze also writes ligand-level chemistry outputs under results/analysis/chem/.

Working Principles

Create a dedicated working directory such as ./docking/.
Keep the manifest, generated configs, logs, and renders together for reproducibility.
Tell the user whether the search box came from prior knowledge, co-crystal geometry, active residues, or a geometric fallback.
Treat docking scores as ranking heuristics, not experimental truth.
When the pipeline falls back from protein-specific cleanup to generic conversion, report that explicitly.

Output Layout

The template writes:

inputs/
prepared/
configs/
results/docking/
results/complexes/
results/renders/
results/analysis/
metadata/session.json
metadata/history.jsonl

Key deliverables:

results/analysis/docking_summary.csv
results/analysis/binding_energy_matrix.csv
results/analysis/ligand_best_scores.csv
results/analysis/binding_energy_heatmap.png
results/analysis/evaluation.md
results/analysis/paper_report.md
results/analysis/ml_scores.csv when the ML stage is available
results/analysis/chem/ when chemistry post-processing is enabled
inputs/ligands/*.drugbank.json when DrugBank-backed ligands are used

Failure Modes

obabel missing: cannot prepare receptor or ligand
vina missing: cannot score poses
pdbfixer missing: protein receptor cleanup falls back poorly; say so explicitly
no settings.drugbank_catalog and no settings.drugbank_api_key / settings.drugbank_api_token: DrugBank ligands cannot be resolved
no plausible box definition: ask for catalytic residues, a co-crystal ligand, or approximate binding-site coordinates
PyMOL missing: still return text results plus the generated .pml scripts
chemistry models missing: keep docking outputs and skip the optional reranking stage explicitly
structure-affinity model missing: keep docking outputs, ligand-only chemistry outputs, and skip structure-aware scoring explicitly

Recommended Response Pattern

text

I used the bundled docking workflow template to prepare the receptor and ligand, generate the docking box, run AutoDock Vina, and save the artifacts in `docking/`.
The top-ranked pose reports `-8.1 kcal/mol` in `results/analysis/docking_summary.csv`.
I also generated `evaluation.md`, `paper_report.md`, and a PyMOL render script for the top hits.
This is a docking ranking result, not a measured binding affinity; the main uncertainty is the search-box definition.

Files

SKILL.md and 3 other files in skills/pharma/docking-tools of DrugClaw/DrugClaw.

SKILL.md
templates/README.md
templates/docking_manifest.example.json
templates/docking_workflow.py

Open the folder on GitHubat commit 960a6e0

Compare with similar skills

Docking Tools 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.

Docking Tools compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Docking Tools this skillDrugClaw/DrugClaw	125	—	~2.1k	Automated safety check: Pass	Apache-2.0	6 mo ago
MolecodeAtomFlow-AI/MoleCode	305	—	~1.9k	Automated safety check: Pass	MIT	4 mo ago
Drug DiscoveryTommy-yw/RunbookHermes	546	1 repos	~2.3k	Automated safety check: Pass	MIT	4 mo ago
DiffDock Molecular DockingK-Dense-AI/scientific-agent-skills	48k	1 repos	~3k	Automated safety check: Notes	MIT	3 days ago
Biomedical Analysis Dispatchxjtulyc/MedgeClaw	617	1 repos	~2k	Automated safety check: Pass	None	7 mo ago
Edu Chem Reactionwy51ai/edulab	1.4k	—	~1.2k	Automated safety check: Pass	Apache-2.0	10 days ago

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Questions about Docking Tools

What does Docking Tools do?

Molecular docking workflow guide and reusable pipeline template for AutoDock Vina, Open Babel, and PyMOL. Docking Tools is an agent skill from DrugClaw/DrugClaw. Molecular docking workflow guide and reusable pipeline template for AutoDock Vina, Open Babel, and PyMOL.

When should I use Docking Tools?

Docking Tools fits situations like: tasks that involve Drug discovery and cheminformatics.

How do I install Docking Tools in Claude Code?

Run `npx skills add DrugClaw/DrugClaw --skill docking-tools -a claude-code`. Or copy the skill folder (skills/pharma/docking-tools in DrugClaw/DrugClaw) into .claude/skills/docking-tools in your project. Claude Code loads it when a task matches its description.

How do I install Docking Tools in Codex?

Run `npx skills add DrugClaw/DrugClaw --skill docking-tools -a codex`. Or copy the skill folder (skills/pharma/docking-tools in DrugClaw/DrugClaw) into .agents/skills/docking-tools in your project. Codex loads it when a task matches its description.

Can I use Docking Tools 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 DrugClaw/DrugClaw --skill docking-tools -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/docking-tools, .gemini/skills/docking-tools, .github/skills/docking-tools and .opencode/skills/docking-tools in your project.

What does Docking Tools need to run?

Going by SKILL.md and its folder, Docking Tools needs Python for the scripts in its folder and the command-line tools its instructions call (python3). Our summary lists: Python 3; Docker.

Does Docking Tools 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 Docking Tools 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. Review the folder before installing.

What licence does Docking Tools use?

Docking Tools is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Docking Tools use?

About 2.1k tokens (SKILL.md is roughly 8.4k 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 Docking Tools?

Skills that share tags, products or a category with Docking Tools: Molecode (AtomFlow-AI/MoleCode, 305 stars), Drug Discovery (Tommy-yw/RunbookHermes, 546 stars), DiffDock Molecular Docking (K-Dense-AI/scientific-agent-skills, 48k stars) and Biomedical Analysis Dispatch (xjtulyc/MedgeClaw, 617 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Docking Tools?

DrugClaw (a GitHub organization) maintains it in DrugClaw/DrugClaw, which has 125 GitHub stars. The repository holds 25 skills in this directory. The repository was last updated on March 23, 2026.

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

Install Docking Tools

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

Docking Tools

Runtime Requirements

Preferred Workflow

Fast Start

Manifest Guidance

Working Principles

Output Layout

Failure Modes

Recommended Response Pattern

Files

Compare with similar skills

Similar skills

More from DrugClaw/DrugClaw

Related

Questions about Docking Tools