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.
npx skills add AndyZhuang/Opentest --skill uniprot-databasegit clone --depth 1 https://github.com/AndyZhuang/OpentestWrote 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.
[](https://agentmods.dev/skills/andyzhuang/opentest/uniprot-database)<a href="https://agentmods.dev/skills/andyzhuang/opentest/uniprot-database"><img src="https://agentmods.dev/badge/skills/andyzhuang/opentest/uniprot-database/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.
<a href="https://agentmods.dev/skills/andyzhuang/opentest/uniprot-database"><img src="https://agentmods.dev/badge/skills/andyzhuang/opentest/uniprot-database.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00066 | $0.01805 |
| Opus 5 | $0.00033 | $0.00903 |
| Sonnet 5 | $0.00013 | $0.00361 |
| Haiku 4.5 | $0.00007 | $0.00180 |
Grade A, and why
uniprot-database 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 6d 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.
- `api_examples.md` - Code examples in multiple languages (Python, curl, R) This is a copy
89% identical to uniprot-database — 6 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 195 lines — stays where its author put it; the contents beside it link to each section on GitHub.
UniProt Database
Overview
UniProt is the world's leading comprehensive protein sequence and functional information resource. Search proteins by name, gene, or accession, retrieve sequences in FASTA format, perform ID mapping across databases, access Swiss-Prot/TrEMBL annotations via REST API for protein analysis.
When to Use This Skill
This skill should be used when:
- Searching for protein entries by name, gene symbol, accession, or organism
- Retrieving protein sequences in FASTA or other formats
- Mapping identifiers between UniProt and external databases (Ensembl, RefSeq, PDB, etc.)
- Accessing protein annotations including GO terms, domains, and functional descriptions
- Batch retrieving multiple protein entries efficiently
- Querying reviewed (Swiss-Prot) vs. unreviewed (TrEMBL) protein data
- Streaming large protein datasets
- Building custom queries with field-specific search syntax
Core Capabilities
1. Searching for Proteins
Search UniProt using natural language queries or structured search syntax.
Common search patterns:
# Search by protein name
query = "insulin AND organism_name:\"Homo sapiens\""
# Search by gene name
query = "gene:BRCA1 AND reviewed:true"
# Search by accession
query = "accession:P12345"
# Search by sequence length
query = "length:[100 TO 500]"
# Search by taxonomy
query = "taxonomy_id:9606" # Human proteins
# Search by GO term
query = "go:0005515" # Protein binding
Use the API search endpoint: https://rest.uniprot.org/uniprotkb/search?query={query}&format={format}
Supported formats: JSON, TSV, Excel, XML, FASTA, RDF, TXT
2. Retrieving Individual Protein Entries
Retrieve specific protein entries by accession number.
Accession number formats:
- Classic: P12345, Q1AAA9, O15530 (6 characters: letter + 5 alphanumeric)
- Extended: A0A022YWF9 (10 characters for newer entries)
Retrieve endpoint: https://rest.uniprot.org/uniprotkb/{accession}.{format}
Example: https://rest.uniprot.org/uniprotkb/P12345.fasta
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.
- 6d ago First seen · 195 lines · 66 tokens per session scan A 4992d5c2dd3a
uniprot-database is a skill published in the GitHub repository AndyZhuang/Opentest (22 stars, last pushed 6mo ago), licensed MIT. It adds 66 tokens to every session and 1,805 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). It is 89% identical to uniprot-database, differing in 6 lines, and is treated as a copy.
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