synthetic-sciences/openscience is an AI workbench that carries out scientific research by reading papers, forming hypotheses, writing and running code, conducting experiments, analyzing results, and preparing reports. Researchers use it for work in machine learning, biology, physics, and chemistry with remote or local models. Catalogue add-ons extend its scientific workflows through skills and instructions.
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 agentmods add skills/synthetic-sciences/openscience/ensembl-databasenpx skills add synthetic-sciences/openscience --skill ensembl-databasegit clone --depth 1 https://github.com/synthetic-sciences/openscienceWrote 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/synthetic-sciences/openscience/ensembl-database)<a href="https://agentmods.dev/skills/synthetic-sciences/openscience/ensembl-database"><img src="https://agentmods.dev/badge/skills/synthetic-sciences/openscience/ensembl-database.svg" alt="Measured on agentmods" 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 | $0.00045 | $0.01951 |
| Opus 5 | $0.00023 | $0.00975 |
| Sonnet 5 | $0.00009 | $0.00390 |
| Haiku 4.5 | $0.00005 | $0.00195 |
Grade A, and why
ensembl-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 yesterday.
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.
response = requests.get( Copies of this mod
7 near-identical copies found in the catalogue:
- ensembl-database — 97% identical, 3 lines differ
- ensembl-database — 97% identical, 3 lines differ
- ensembl-database — 92% identical, 7 lines differ
- ensembl-database — 84% identical, 6 lines differ
- ensembl-database — 84% identical, 6 lines differ
- ensembl-database — 84% identical, 6 lines differ
- ensembl-database — 84% identical, 6 lines differ
How it starts
The opening of the file, as written. The whole thing — 311 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Ensembl Database
Overview
Access and query the Ensembl genome database, a comprehensive resource for vertebrate genomic data maintained by EMBL-EBI. The database provides gene annotations, sequences, variants, regulatory information, and comparative genomics data for over 250 species. Current release is 115 (September 2025).
When to Use This Skill
This skill should be used when:
- Querying gene information by symbol or Ensembl ID
- Retrieving DNA, transcript, or protein sequences
- Analyzing genetic variants using the Variant Effect Predictor (VEP)
- Finding orthologs and paralogs across species
- Accessing regulatory features and genomic annotations
- Converting coordinates between genome assemblies (e.g., GRCh37 to GRCh38)
- Performing comparative genomics analyses
- Integrating Ensembl data into genomic research pipelines
Core Capabilities
1. Gene Information Retrieval
Query gene data by symbol, Ensembl ID, or external database identifiers.
Common operations:
- Look up gene information by symbol (e.g., "BRCA2", "TP53")
- Retrieve transcript and protein information
- Get gene coordinates and chromosomal locations
- Access cross-references to external databases (UniProt, RefSeq, etc.)
Using the ensembl_rest package:
from ensembl_rest import EnsemblClient
client = EnsemblClient()
# Look up gene by symbol
gene_data = client.symbol_lookup(
species='human',
symbol='BRCA2'
)
# Get detailed gene information
gene_info = client.lookup_id(
id='ENSG00000139618', # BRCA2 Ensembl ID
expand=True
)
Direct REST API (no package):
import requests
server = "https://rest.ensembl.org"
# Symbol lookup
response = requests.get(
f"{server}/lookup/symbol/homo_sapiens/BRCA2",
headers={"Content-Type": "application/json"}
)
gene_data = response.json()
2. Sequence Retrieval
Fetch genomic, transcript, or protein sequences in various formats (JSON, FASTA, plain text).
Operations:
- Get DNA sequences for genes or genomic regions
- Retrieve transcript sequences (cDNA)
- Access protein sequences
- Extract sequences with flanking regions or modifications
What ships with it
2 files 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.
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.
- yesterday First seen · 311 lines · 45 tokens per session scan A 81cb271b1ad0
ensembl-database is a skill published in the GitHub repository synthetic-sciences/openscience (3,473 stars, last pushed today), licensed Apache-2.0. It adds 45 tokens to every session and 1,951 once invoked, about $0.0002 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 2026-09-03.
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