alphafold-database SKILL.md skillA
alphafold-database from marielynneblock/arcanum-artifex is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add marielynneblock/arcanum-artifex/alphafold-database@git:20260710.0115f49Pins git:20260710.0115f49 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- marielynneblock/arcanum-artifex
- Path
skills/scientific/alphafold-database/SKILL.md- Versions recorded
- 5
- Latest version
- git:20260710.0115f49, committed Jul 10, 2026
- First version recorded
- Apr 6, 2026
- Size
- 16,400 bytes
- Repository stars
- 4
- License
- none declared
Access AlphaFold 200M+ AI-predicted protein structures. Retrieve structures by UniProt ID, download PDB/mmCIF files, analyse 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 - Analysing 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
mdr add marielynneblock/arcanum-artifex/alphafold-database@sha256:c6183a7835a9e541The line at the top of this page pins the label git:20260710.0115f49, 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.
[](https://markdownregistry.com/a/art_iwqyytiouwt362ct)
5 badge image fetches in 30 days. What the badge shows.
Versions
The registry has recorded 5 versions of this file, between Apr 6, 2026 and Jul 10, 2026, about one every 24 days.
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| git:20260710.0115f49 latest | 2026-07-10 | 0115f49 | 16,400 B | A | view · diff |
| git:20260710.d1b3aa8 | 2026-07-10 | d1b3aa8 | 16,400 B | A | view · diff |
| git:20260710.ffb3400 | 2026-07-10 | ffb3400 | 16,400 B | A | view · diff |
| git:20260515.b861afb | 2026-05-15 | b861afb | 16,400 B | A | view · diff |
| git:20260406.05dff34 | 2026-04-06 | 05dff34 | 16,401 B | A | view |
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (16400 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
marielynneblock/arcanum-artifex · 4 stars · license none declared · pushed 2026-09-19 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_iwqyytiouwt362ct GET https://markdownregistry.com/api/v1/resolve?ref=marielynneblock/arcanum-artifex/alphafold-database GET https://markdownregistry.com/api/v1/blob/c6183a7835a9e541edeceb11d5fa432e9760097cbc08b5e991c6ae324fdfb9f1
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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