alphafold2 SKILL.md skillA

alphafold2 from aipoch/open-science is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.

Install it, pinned
mdr add aipoch/open-science/alphafold2@git:20260814.c9a70d8

Pins git:20260814.c9a70d8 in mdr.lock. Pin the fingerprint instead.

Audit grade
A, 17 of 17 checks passed
Kind
SKILL.md skill
Repository
aipoch/open-science
Path
resources/skills/alphafold2/SKILL.md
Versions recorded
2
Latest version
git:20260814.c9a70d8, committed Aug 14, 2026
First version recorded
Jul 14, 2026
Size
5,391 bytes
Repository stars
5,279
License
Apache-2.0

Predict protein structure for monomers and multimers with AlphaFold2 via the ColabFold runner (Mirdita et al. 2022, github.com/sokrypton/ColabFold; AlphaFold2 Jumper et al. 2021). Reach for this skill to fold a sequence or complex with the AF2/AF2-Multimer evoformer, to validate designed sequences by self-consistency pLDDT, ipTM, and RMSD, or to run a quick MSA-backed prediction using the public MMseqs2 server.

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

# AlphaFold2 (ColabFold runner)

This skill wraps AlphaFold2 and AlphaFold2-Multimer through `colabfold_batch`,
which replaces DeepMind's local-database MSA pipeline with a call to the public
MMseqs2 server — so a prediction is one command and one FASTA, not a 2 TB
database mount. AF2 remains the reference monomer predictor and the multimer
model is still a strong protein–protein validator, but it does not handle
ligands or nucleic acids; for those, route to `boltz`, `chai1`, or `openfold3`.
The ColabFold code is MIT (github.com/sokrypton/ColabFold) and the AlphaFold2
code is Apache-2.0 (github.com/google-deepmind/alphafold); the AF2 model
parameters are CC-BY-4.0 with DeepMind's terms of use.

## Running it

```bash
colabfold_batch input.fasta out \
  --num-recycle 3 \
  --model-type alphafold2_multimer_v3
```

The input is a plain FASTA. For a complex, put every chain on one sequence
line separated by `:` — `colabfold_batch` builds a paired MSA per segment and
runs the multimer model when it sees the colon (so the explicit `--model-type
alphafold2_multimer_v3` above is belt-and-braces). For monomers omit
`--model-type` and the colon. `--templates` and `--amber` add PDB templates
…

Read the whole file at its exact version.

How to install

The exact contents, by fingerprint
mdr add aipoch/open-science/alphafold2@sha256:984cfa7956ac50d8

The line at the top of this page pins the label git:20260814.c9a70d8, 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_lujtoe2qmnbaormy.svg)](https://markdownregistry.com/a/art_lujtoe2qmnbaormy)

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

Versions

The registry has recorded 2 versions of this file, between Jul 14, 2026 and Aug 14, 2026, about one every 31 days.

versioncommittedcommitsizeaudit
git:20260814.c9a70d8 latest2026-08-14 c9a70d8 5,391 BA view · diff
git:20260714.a2a32822026-07-14 a2a3282 4,965 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 (5391 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

aipoch/open-science · 5,279 stars · license Apache-2.0 · pushed 2026-10-19 · branch main

API

GET https://markdownregistry.com/api/v1/artifacts/art_lujtoe2qmnbaormy
GET https://markdownregistry.com/api/v1/resolve?ref=aipoch/open-science/alphafold2
GET https://markdownregistry.com/api/v1/blob/984cfa7956ac50d878e3714563af881f8430b2281f1a927887a5f18304b81cee

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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