uniprot

uniprot is a skill for Claude Code, Codex from zongtingwei/Bioclaw_Skills_Hub. It costs 79 tokens per session (1,414 once invoked), scanned A, original, MIT.

A connection to UniProt, a public database of protein sequences and biological annotations.

In plain words
What is it for?
Use it to retrieve sequences, functions, domains, related proteins, variants, and links to 3D structures in the Protein Data Bank.
Why use it?
It avoids manually searching database pages or parsing downloaded records when you need reliable protein information.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to retrieve sequences, functions, domains, related proteins, variants, and links to 3D structures in the Protein Data Bank.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/zongtingwei/bioclaw_skills_hub/uniprot
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add zongtingwei/Bioclaw_Skills_Hub --skill uniprot
Clone the repo
git clone --depth 1 https://github.com/zongtingwei/Bioclaw_Skills_Hub

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for uniprot

README.md
[![agentmods](https://agentmods.dev/badge/skills/zongtingwei/bioclaw_skills_hub/uniprot/github.svg)](https://agentmods.dev/skills/zongtingwei/bioclaw_skills_hub/uniprot)
Your own site
<a href="https://agentmods.dev/skills/zongtingwei/bioclaw_skills_hub/uniprot"><img src="https://agentmods.dev/badge/skills/zongtingwei/bioclaw_skills_hub/uniprot/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for uniprot

Your own site · 80×15
<a href="https://agentmods.dev/skills/zongtingwei/bioclaw_skills_hub/uniprot"><img src="https://agentmods.dev/badge/skills/zongtingwei/bioclaw_skills_hub/uniprot.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 79 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,414 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00079 $0.01414
Opus 5 $0.00039 $0.00707
Sonnet 5 $0.00016 $0.00283
Haiku 4.5 $0.00008 $0.00141

Measured 12d ago against content hash fc2f9e8779f0, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

uniprot scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

curl "https://rest.uniprot.org/uniprotkb/P00533.fasta"
skills/protein-design/skills/uniprot/SKILL.md · 208 lines

How it starts

The opening of the file, as written. The whole thing — 208 lines — stays where its author put it; the contents beside it link to each section on GitHub.

UniProt Database Access

Note: This skill uses the UniProt REST API directly. No Modal deployment needed - all operations run locally via HTTP requests.

Fetching Sequences

By Accession

# FASTA format
curl "https://rest.uniprot.org/uniprotkb/P00533.fasta"

# JSON format with annotations
curl "https://rest.uniprot.org/uniprotkb/P00533.json"

Using Python

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, None

Getting Annotations

Full Entry

def 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']}")

Domain Boundaries

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}, ...]

Searching UniProt

By Gene Name

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)

Read the full file on GitHub · 208 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 12d ago First seen · 208 lines · 79 tokens per session scan A fc2f9e8779f0

Subscribe to this mod's changes

uniprot is a skill published in the GitHub repository zongtingwei/Bioclaw_Skills_Hub (26 stars, last pushed 5mo ago), licensed MIT. It adds 79 tokens to every session and 1,414 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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