esm-protein-language-model SKILL.md skillA
esm-protein-language-model from jaechang-hits/sciagent-skills is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add jaechang-hits/sciagent-skills/esm-protein-language-model@git:20260528.0e69cedPins git:20260528.0e69ced in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- jaechang-hits/sciagent-skills
- Path
skills/proteomics-protein-engineering/esm-protein-language-model/SKILL.md- Versions recorded
- 3
- Latest version
- git:20260528.0e69ced, committed May 28, 2026
- First version recorded
- Feb 18, 2026
- Size
- 16,139 bytes
- Repository stars
- 381
- License
- a license file GitHub does not identify
Protein language models (ESM3, ESM C) for sequence generation, structure prediction, inverse folding, and embeddings. Design novel proteins, extract ML features, or fold sequences. Local GPU or EvolutionaryScale Forge API. Use AlphaFold for traditional folding; RDKit for small molecules.
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
# ESM — Protein Language Models ## Overview ESM (Evolutionary Scale Modeling) provides pretrained protein language models for generative protein design and representation learning. ESM3 is a multimodal generative model conditioned on sequence, structure, and function simultaneously. ESM C is an efficient embedding model optimized for extracting protein representations for downstream ML tasks. ## When to Use - Generating novel protein sequences conditioned on desired structure or function - Extracting fixed-length embeddings from protein sequences for classification, clustering, or regression - Predicting 3D structure from amino acid sequence - Inverse folding: designing sequences that fold into a target structure - Annotating proteins with functional keywords (GO terms, EC numbers) - Comparing protein similarity via embedding distance instead of sequence alignment - Chain-of-thought protein design: iterative refinement of sequence/structure/function - For **traditional physics-based structure prediction**, use AlphaFold instead - For **sequence alignment and homology search**, use BLAST/HMMER via BioPython instead ## Prerequisites …
Read the whole file at its exact version.
How to install
mdr add jaechang-hits/sciagent-skills/esm-protein-language-model@sha256:a864e2dd0eb4eb29The line at the top of this page pins the label git:20260528.0e69ced, 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_pbg7v2tna65fkj67)
2 badge image fetches in 30 days. What the badge shows.
Versions
The registry has recorded 3 versions of this file, between Feb 18, 2026 and May 28, 2026, about one every 49 days.
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| git:20260528.0e69ced latest | 2026-05-28 | 0e69ced | 16,139 B | A | view · diff |
| git:20260428.81ea2d2 | 2026-04-28 | 81ea2d2 | 16,132 B | A | view · diff |
| git:20260218.8df1694 | 2026-02-18 | 8df1694 | 16,244 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 (16139 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
jaechang-hits/sciagent-skills · 381 stars · license a license file GitHub does not identify · pushed 2026-10-16 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_pbg7v2tna65fkj67 GET https://markdownregistry.com/api/v1/resolve?ref=jaechang-hits/sciagent-skills/esm-protein-language-model GET https://markdownregistry.com/api/v1/blob/a864e2dd0eb4eb296dc3ebeb89cf0c4a96f51ed61b987d5928aeb8cb99ccab2f
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.