alphafold-database SKILL.md skillA

alphafold-database from aicodedecode/awesome-muse-skills is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.

Install it, pinned
mdr add aicodedecode/awesome-muse-skills/alphafold-database@git:20260927.806f3e1

Pins git:20260927.806f3e1 in mdr.lock. Pin the fingerprint instead.

Audit grade
A, 17 of 17 checks passed
Kind
SKILL.md skill
Repository
aicodedecode/awesome-muse-skills
Path
skills-imported/alphafold-database/SKILL.md
Versions recorded
1
Latest version
git:20260927.806f3e1, committed Sep 27, 2026
Size
15,806 bytes
Repository stars
25
License
MIT

Access AlphaFold's 200M+ AI-predicted protein structures. Retrieve structures by UniProt ID, download PDB/mmCIF files, analyze confidence metrics (pLDDT, PAE), for drug discovery and structural biology.

Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.

What the file says

# AlphaFold Database

## Overview

AlphaFold DB is a public repository of AI-predicted 3D protein structures for over 200 million proteins, maintained by DeepMind and EMBL-EBI. Access structure predictions with confidence metrics, download coordinate files, retrieve bulk datasets, and integrate predictions into computational workflows.

## When to Use This Skill

This skill should be used when working with AI-predicted protein structures in scenarios such as:

- Retrieving protein structure predictions by UniProt ID or protein name
- Downloading PDB/mmCIF coordinate files for structural analysis
- Analyzing prediction confidence metrics (pLDDT, PAE) to assess reliability
- Accessing bulk proteome datasets via Google Cloud Platform
- Comparing predicted structures with experimental data
- Performing structure-based drug discovery or protein engineering
- Building structural models for proteins lacking experimental structures
- Integrating AlphaFold predictions into computational pipelines

## Core Capabilities

### 1. Searching and Retrieving Predictions

**Using Biopython (Recommended):**

The Biopython library provides the simplest interface for retrieving AlphaFold structures:
…

Read the whole file at its exact version.

How to install

The exact contents, by fingerprint
mdr add aicodedecode/awesome-muse-skills/alphafold-database@sha256:9c9f982059f68ffb

The line at the top of this page pins the label git:20260927.806f3e1, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.

Badge

mdr badge

[![mdr](https://markdownregistry.com/badge/art_ae6v25h5n4amire4.svg)](https://markdownregistry.com/a/art_ae6v25h5n4amire4)

2 badge image fetches in 30 days. What the badge shows.

Versions

The registry has recorded 1 version of this file, committed on Sep 27, 2026.

versioncommittedcommitsizeaudit
git:20260927.806f3e1 latest2026-09-27 806f3e1 15,806 BA view

Audit of the latest version

A  17 of 17 checks passed. Fixed automatic checks with no AI involved, so the same checks give the same answer every run.
  • pass: Frontmatter block present
  • pass: Frontmatter declares a name
  • pass: Frontmatter declares a description
  • pass: Size between 200 bytes and 200 KB (15806 bytes)
  • pass: No zero-width or bidi control characters
  • pass: No instruction hidden inside an HTML comment
  • pass: No link to an exfiltration or paste host
  • pass: No credential-shaped string
  • pass: No instruction to send local credentials anywhere
  • pass: No text hidden with inline styles
  • pass: No prompt-injection phrasing
  • pass: No curl or wget piped into a shell
  • pass: No recursive delete of root, home or parent
  • pass: No instruction to read or print local credentials
  • pass: No base64 blob over 200 characters
  • pass: No link to a raw IP address
  • pass: No script tag

Source

GitHub

aicodedecode/awesome-muse-skills · 25 stars · license MIT · pushed 2026-10-10 · branch main

API

GET https://markdownregistry.com/api/v1/artifacts/art_ae6v25h5n4amire4
GET https://markdownregistry.com/api/v1/resolve?ref=aicodedecode/awesome-muse-skills/alphafold-database
GET https://markdownregistry.com/api/v1/blob/9c9f982059f68ffbfe0b35c4e536f570bf701e0f99a4a835e4c1bb60d3009bd8

Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.

Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.

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Every file in aicodedecode/awesome-muse-skills

Other files named alphafold-database

alphafold-database SKILL.md skill
fridrichmethod/awesome-skills · skills/alphafold-database/SKILL.md · Access AlphaFold's 200M+ AI-predicted protein structures. Retrieve structures by UniProt ID, download PDB/mmCIF files…
git:20260517.81511a7 · audit A · 15 stars
alphafold-database SKILL.md skill
marielynneblock/arcanum-artifex · skills/scientific/alphafold-database/SKILL.md · Access AlphaFold 200M+ AI-predicted protein structures. Retrieve structures by UniProt ID, download PDB/mmCIF files…
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