bio-applied-docking

bio-applied-docking is a skill for Claude Code, Codex from Pavel-Kravchenko/Bioinformatics. It costs 76 tokens per session (2,243 once invoked), scanned A, original, no licence file.

A molecular-docking workflow that predicts how a small molecule, called a ligand, may fit into a protein structure, called a receptor. It prepares molecular files, runs AutoDock Vina, and ranks the resulting binding poses by score and structural similarity.

In plain words
What is it for?
Use it for virtual screening, testing a known crystal-structure ligand again, and converting PDB or SMILES molecules into docking-ready PDBQT files.
Why use it?
It provides a repeatable way to explore possible protein–molecule interactions before laboratory testing. This can reduce manual file conversion and pose inspection.

Skill for Claude CodeCodex

Which agent this was written for is unclear — body not stored (licence); the path alone says nothing.

Good fit Use it for virtual screening, testing a known crystal-structure ligand again, and converting PDB or SMILES molecules into docking-ready PDBQT files.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/pavel-kravchenko/bioinformatics/bio-applied-docking
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add Pavel-Kravchenko/Bioinformatics --skill bio-applied-docking
Clone the repo
git clone --depth 1 https://github.com/Pavel-Kravchenko/Bioinformatics

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for bio-applied-docking

README.md
[![agentmods](https://agentmods.dev/badge/skills/pavel-kravchenko/bioinformatics/bio-applied-docking/github.svg)](https://agentmods.dev/skills/pavel-kravchenko/bioinformatics/bio-applied-docking)
Your own site
<a href="https://agentmods.dev/skills/pavel-kravchenko/bioinformatics/bio-applied-docking"><img src="https://agentmods.dev/badge/skills/pavel-kravchenko/bioinformatics/bio-applied-docking/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for bio-applied-docking

Your own site · 80×15
<a href="https://agentmods.dev/skills/pavel-kravchenko/bioinformatics/bio-applied-docking"><img src="https://agentmods.dev/badge/skills/pavel-kravchenko/bioinformatics/bio-applied-docking.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 76 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,243 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe.
Origin unknown No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00076 $0.02243
Opus 5 $0.00038 $0.01122
Sonnet 5 $0.00015 $0.00449
Haiku 4.5 $0.00008 $0.00224

Measured 9d ago against content hash 7518be2527b5, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

bio-applied-docking scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Runs shell commandslowCapability

Expected in a hook, worth knowing in a rule or an instructions file.

subprocess.run(["obabel", sdf_path, "-O", out_path, "--partialcharge", "gasteiger"],
Skills/bio-applied-docking/SKILL.md · 174 lines

The source is not reproduced here

No licence file

A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.

Read it on GitHub

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 9d ago First seen · 174 lines · 76 tokens per session scan A 7518be2527b5

Subscribe to this mod's changes

bio-applied-docking is a skill published in the GitHub repository Pavel-Kravchenko/Bioinformatics (5 stars, last pushed 2mo ago), with no licence file. It adds 76 tokens to every session and 2,243 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 1 finding (runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.