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 GPTomics/bioSkills --skill biomart-queriesgit clone --depth 1 https://github.com/GPTomics/bioSkillsWrote 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/gptomics/bioskills/biomart-queries)<a href="https://agentmods.dev/skills/gptomics/bioskills/biomart-queries"><img src="https://agentmods.dev/badge/skills/gptomics/bioskills/biomart-queries/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/gptomics/bioskills/biomart-queries"><img src="https://agentmods.dev/badge/skills/gptomics/bioskills/biomart-queries.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 | $0.00142 | $0.03452 |
| Opus 5 | $0.00071 | $0.01726 |
| Sonnet 5 | $0.00028 | $0.00690 |
| Haiku 4.5 | $0.00014 | $0.00345 |
Grade A, and why
bio-biomart-queries 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 8d 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.
- CLI: `curl` against the XML endpoint works but is rarely used directly Copies of this mod
1 near-identical copy found in the catalogue:
- bio-biomart-queries — 97% identical, 12 lines differ
How it starts
The opening of the file, as written. The whole thing — 282 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Version Compatibility
Reference examples tested with: pybiomart 0.9+, R biomaRt 2.58+ (Bioconductor); Ensembl BioMart (release 110+)
Before using code patterns, verify installed versions match. If versions differ:
- Python:
pip show pybiomart - R:
packageVersion('biomaRt')
The BioMart XML query format is stable across Ensembl releases; the underlying mart names and attribute IDs can change between Ensembl releases. For published work, pin the Ensembl release via useEnsembl(version=110).
BioMart Queries
"Bulk-convert IDs / pull coordinate tables / extract ortholog wide tables" -> BioMart is the right answer for any Ensembl-rooted query producing >5,000 rows. It is a separate service from the Ensembl REST API, with separate rate behavior and a different query model (XML-based, batch-oriented). For one-off lookups (<100 records), Ensembl REST is more convenient; for bulk anything, BioMart wins.
The single most important fact: BioMart returns a flat table from a single query. There is no per-record loop, no rate-limit cascade, no async polling. One XML query in; one TSV out.
- Python:
pybiomart(https://github.com/jrderuiter/pybiomart) is the lightest client - R:
biomaRtBioconductor (Durinck et al. 2009 Nat Protoc 4:1184) is the canonical client - CLI:
curlagainst the XML endpoint works but is rarely used directly - Web:
https://www.ensembl.org/biomart/martviewfor interactive query design
Installation
pip install pybiomart pandas
# R:
# BiocManager::install('biomaRt')
BioMart hierarchy
| Level | Examples |
|---|---|
| Mart | ENSEMBL_MART_ENSEMBL (genes), ENSEMBL_MART_SNP (variants), ENSEMBL_MART_MOUSE (mouse-specific) |
| Dataset | hsapiens_gene_ensembl, mmusculus_gene_ensembl, etc. (per species) |
| Attribute | Fields to return: ensembl_gene_id, external_gene_name, chromosome_name, etc. |
| Filter | Constraints on the query: chromosome_name = 17, biotype = protein_coding, etc. |
A query is: pick a mart, pick a dataset, list attributes to return, list filters to constrain. BioMart returns a single TSV.
What ships with it
4 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.
- 8d ago First seen · 282 lines · 142 tokens per session scan A cdaecd800c89
bio-biomart-queries is a skill published in the GitHub repository GPTomics/bioSkills (1,201 stars, last pushed 27d ago), licensed MIT. It adds 142 tokens to every session and 3,452 once invoked, about $0.0007 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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