Alphafold Database Fetch And Analyze
google-deepmind/science-skills
Retrieve and analyze AlphaFold predicted structures for a protein.
Access UniProt for protein sequence and annotation retrieval.
$ npx skills add adaptyvbio/protein-design-skills --skill uniprot -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install adaptyvbio/protein-design-skills uniprot --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/adaptyvbio/protein-design-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/uniprot .claude/skills/uniprot && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "uniprot" agent skill from https://github.com/adaptyvbio/protein-design-skills/tree/main/skills/uniprot into .claude/skills/uniprot/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "uniprot", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/adaptyvbio/protein-design-skills/tree/main/skills/uniprotType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add adaptyvbio/protein-design-skills --skill uniprot -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install adaptyvbio/protein-design-skills uniprot --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/adaptyvbio/protein-design-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/uniprot .agents/skills/uniprot && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "uniprot" agent skill from https://github.com/adaptyvbio/protein-design-skills/tree/main/skills/uniprot into .agents/skills/uniprot/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "uniprot", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add adaptyvbio/protein-design-skills --skill uniprot -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install adaptyvbio/protein-design-skills uniprot --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/adaptyvbio/protein-design-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/uniprot .cursor/skills/uniprot && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "uniprot" agent skill from https://github.com/adaptyvbio/protein-design-skills/tree/main/skills/uniprot into .cursor/skills/uniprot/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "uniprot", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/adaptyvbio/protein-design-skills.git --path skills/uniprot--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add adaptyvbio/protein-design-skills --skill uniprot -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install adaptyvbio/protein-design-skills uniprot --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/adaptyvbio/protein-design-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/uniprot .gemini/skills/uniprot && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "uniprot" agent skill from https://github.com/adaptyvbio/protein-design-skills/tree/main/skills/uniprot into .gemini/skills/uniprot/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "uniprot", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install adaptyvbio/protein-design-skills uniprotInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add adaptyvbio/protein-design-skills --skill uniprot -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/adaptyvbio/protein-design-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/uniprot .github/skills/uniprot && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "uniprot" agent skill from https://github.com/adaptyvbio/protein-design-skills/tree/main/skills/uniprot into .github/skills/uniprot/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "uniprot", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add adaptyvbio/protein-design-skills --skill uniprot -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install adaptyvbio/protein-design-skills uniprot --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/adaptyvbio/protein-design-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/uniprot .opencode/skills/uniprot && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "uniprot" agent skill from https://github.com/adaptyvbio/protein-design-skills/tree/main/skills/uniprot into .opencode/skills/uniprot/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "uniprot", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
uniprotAccess UniProt for protein sequence and annotation retrieval.
Uniprot is an agent skill from adaptyvbio/protein-design-skills. Access UniProt for protein sequence and annotation retrieval. Use this skill when: (1) Looking up protein sequences by accession, (2) Finding functional annotations, (3) Getting domain boundaries, (4) Finding homologs and variants, (5) Cross-referencing to PDB structures. For structure retrieval, use pdb. For sequence design, use proteinmpnn.
Its SKILL.md is about 1.3k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Research & Science, covering Protein structure and design. It works with UniProt. The repository describes itself as: Claude Code skills for protein design. The licence is MIT.
Read from SKILL.md and the folder at commit 59dd633. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Shell commands in SKILL.md call:
curlFrom the folder's file list and the shell code blocks in SKILL.md.
Hosts in commands or code, which the agent is likely to contact:
rest.uniprot.orguniprot.orgFrom URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Uniprot loads about 1.3k tokens when it runs. Until then it costs about 88 tokens; SKILL.md has 107 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from adaptyvbio/protein-design-skills at commit 59dd633, republished under its MIT licence (© adaptyvbio). 107 words, ~1,268 tokens.
.claude/skills/uniprot/SKILL.md (or your agent's skills folder).Note: This skill uses the UniProt REST API directly. No Modal deployment needed - all operations run locally via HTTP requests.
# FASTA format
curl "https://rest.uniprot.org/uniprotkb/P00533.fasta"
# JSON format with annotations
curl "https://rest.uniprot.org/uniprotkb/P00533.json"import requests
def get_uniprot_sequence(accession):
"""Fetch sequence from UniProt."""
url = f"https://rest.uniprot.org/uniprotkb/{accession}.fasta"
response = requests.get(url)
if response.ok:
lines = response.text.strip().split('\n')
header = lines[0]
sequence = ''.join(lines[1:])
return header, sequence
return None, Nonedef get_uniprot_entry(accession):
"""Fetch full UniProt entry as JSON."""
url = f"https://rest.uniprot.org/uniprotkb/{accession}.json"
response = requests.get(url)
return response.json() if response.ok else None
entry = get_uniprot_entry("P00533")
print(f"Protein: {entry['proteinDescription']['recommendedName']['fullName']['value']}")def get_domains(accession):
"""Extract domain annotations."""
entry = get_uniprot_entry(accession)
domains = []
for feature in entry.get('features', []):
if feature['type'] == 'Domain':
domains.append({
'name': feature.get('description', ''),
'start': feature['location']['start']['value'],
'end': feature['location']['end']['value']
})
return domains
# Example: EGFR domains
domains = get_domains("P00533")
# [{'name': 'Kinase', 'start': 712, 'end': 979}, ...]def search_uniprot(query, organism=None, limit=10):
"""Search UniProt by query."""
url = "https://rest.uniprot.org/uniprotkb/search"
params = {
"query": query,
"format": "json",
"size": limit
}
if organism:
params["query"] += f" AND organism_id:{organism}"
response = requests.get(url, params=params)
return response.json()['results']
# Search for human EGFR
results = search_uniprot("EGFR", organism=9606)# Use UniProt BLAST
# https://www.uniprot.org/blastdef get_pdb_references(accession):
"""Get PDB structures for UniProt entry."""
entry = get_uniprot_entry(accession)
pdbs = []
for xref in entry.get('uniProtKBCrossReferences', []):
if xref['database'] == 'PDB':
pdbs.append({
'pdb_id': xref['id'],
'method': xref.get('properties', [{}])[0].get('value', ''),
'chains': xref.get('properties', [{}])[1].get('value', '')
})
return pdbs
# Example: PDB structures for EGFR
pdbs = get_pdb_references("P00533")# 1. Find protein by name
results = search_uniprot("insulin receptor", organism=9606)
# 2. Get accession
accession = results[0]['primaryAccession'] # e.g., P06213
# 3. Get domains
domains = get_domains(accession)
# 4. Find PDB structure
pdbs = get_pdb_references(accession)
# 5. Download best structure for designdef get_sequence_variants(accession):
"""Get natural variants from UniProt."""
entry = get_uniprot_entry(accession)
variants = []
for feature in entry.get('features', []):
if feature['type'] == 'Natural variant':
variants.append({
'position': feature['location']['start']['value'],
'original': feature.get('alternativeSequence', {}).get('originalSequence', ''),
'variant': feature.get('alternativeSequence', {}).get('alternativeSequences', [''])[0],
'description': feature.get('description', '')
})
return variants| Endpoint | Description |
|---|---|
/uniprotkb/{id}.fasta | FASTA sequence |
/uniprotkb/{id}.json | Full entry JSON |
/uniprotkb/search | Search entries |
/uniprotkb/stream | Batch download |
Entry not found: Check accession format (e.g., P00533) Rate limits: Add delay between requests Large downloads: Use stream endpoint with pagination
Next: Use sequence with esm for embeddings or chai / boltz for structure.
© adaptyvbio, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in skills/uniprot of adaptyvbio/protein-design-skills.
Open the folder on GitHubat commit 59dd633
We found 2 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 2 other GitHub owners. This page covers the copy in adaptyvbio/protein-design-skills, which our catalogue first saw on October 7, 2026.
Uniprot next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Uniprot this skilladaptyvbio/protein-design-skills | 164 | 2 repos | ~1.3k | Automated safety check: Pass | MIT | |
| Alphafold Database Fetch And Analyzegoogle-deepmind/science-skills | 3.2k | 2 repos | ~1.2k | Automated safety check: Pass | Apache-2.0 | |
| Bio DB ToolsDrugClaw/DrugClaw | 125 | — | ~1.4k | Automated safety check: Pass | Apache-2.0 | |
| Ggetdavila7/claude-code-templates | 32k | 10 repos | ~6.3k | Automated safety check: Pass | MIT | |
| Alphafold Databasedavila7/claude-code-templates | 32k | 10 repos | ~4k | Automated safety check: Pass | MIT | |
| Uniprot Databasegoogle-deepmind/science-skills | 3.2k | 1 repos | ~3.1k | Automated safety check: Pass | Apache-2.0 |
google-deepmind/science-skills
Retrieve and analyze AlphaFold predicted structures for a protein.
DrugClaw/DrugClaw
Query public biology databases and APIs including UniProt, RCSB PDB, AlphaFold DB, ClinVar, dbSNP, gnomAD, Ensembl, GEO, InterPro, KEGG, OpenTargets, Reactome, and STRING.
davila7/claude-code-templates
CLI/Python toolkit for rapid bioinformatics queries. An agent skill from davila7/claude-code-templates.
davila7/claude-code-templates
Access AlphaFold's 200M+ AI-predicted protein structures. An agent skill from davila7/claude-code-templates.
google-deepmind/science-skills
Access protein metadata, function, taxonomy, and sequences across UniProtKB, UniParc, and UniRef.
ynulihao/AgentSkillOS
A skill your agent uses when working with scientific research tools and workflows across bioinformatics, cheminformatics, genomics, structural biology, proteomics, and drug discovery.
adaptyvbio/protein-design-skills
Validate protein designs using AlphaFold2 structure prediction.
adaptyvbio/protein-design-skills
End-to-end binder design using BindCraft hallucination. An agent skill from adaptyvbio/protein-design-skills.
adaptyvbio/protein-design-skills
Guidance for choosing the right protein binder design tool. An agent skill from adaptyvbio/protein-design-skills.
adaptyvbio/protein-design-skills
All-atom protein design using BoltzGen diffusion model. An agent skill from adaptyvbio/protein-design-skills.
adaptyvbio/protein-design-skills
Structure prediction using Chai-1, a foundation model for molecular structure.
adaptyvbio/protein-design-skills
End-to-end guidance for protein design pipelines. An agent skill from adaptyvbio/protein-design-skills.
Works with
Categories
Access UniProt for protein sequence and annotation retrieval. Uniprot is an agent skill from adaptyvbio/protein-design-skills. Access UniProt for protein sequence and annotation retrieval.
Uniprot fits situations like: looking up protein sequences by accession; finding functional annotations; getting domain boundaries; finding homologs and variants.
Run `npx skills add adaptyvbio/protein-design-skills --skill uniprot -a claude-code`. Or copy the skill folder (skills/uniprot in adaptyvbio/protein-design-skills) into .claude/skills/uniprot in your project. Claude Code loads it when a task matches its description.
Run `npx skills add adaptyvbio/protein-design-skills --skill uniprot -a codex`. Or copy the skill folder (skills/uniprot in adaptyvbio/protein-design-skills) into .agents/skills/uniprot in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add adaptyvbio/protein-design-skills --skill uniprot -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/uniprot, .gemini/skills/uniprot, .github/skills/uniprot and .opencode/skills/uniprot in your project.
Going by SKILL.md and its folder, Uniprot needs the command-line tools its instructions call (curl). Our summary lists: Python 3.
SKILL.md names 2 domains. In commands or code: rest.uniprot.org and uniprot.org; the agent is likely to contact these when it follows the instructions. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Uniprot is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
About 1.3k tokens (SKILL.md is roughly 5.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Uniprot: Alphafold Database Fetch And Analyze (google-deepmind/science-skills, 3.2k stars), Bio DB Tools (DrugClaw/DrugClaw, 125 stars), Gget (davila7/claude-code-templates, 32k stars) and Alphafold Database (davila7/claude-code-templates, 32k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
adaptyvbio (a GitHub organization) maintains it in adaptyvbio/protein-design-skills, which has 164 GitHub stars. The repository holds 24 skills in this directory. The repository was last updated on June 11, 2026.
Source: adaptyvbio/protein-design-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.