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 entrez-linkgit 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/entrez-link)<a href="https://agentmods.dev/skills/gptomics/bioskills/entrez-link"><img src="https://agentmods.dev/badge/skills/gptomics/bioskills/entrez-link/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/entrez-link"><img src="https://agentmods.dev/badge/skills/gptomics/bioskills/entrez-link.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 | $0.00089 | $0.04275 |
| Opus 5 | $0.00044 | $0.02138 |
| Sonnet 5 | $0.00018 | $0.00855 |
| Haiku 4.5 | $0.00009 | $0.00428 |
Grade A, and why
bio-entrez-link scanned grade A with 0 findings 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 9d 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
1 near-identical copy found in the catalogue:
- bio-entrez-link — 98% identical, 12 lines differ
How it starts
The opening of the file, as written. The whole thing — 353 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Version Compatibility
Reference examples tested with: BioPython 1.83+, Entrez Direct 21.0+
Before using code patterns, verify installed versions match. If versions differ:
- Python:
pip show biopythonthenhelp(Bio.Entrez.elink)to check signatures - CLI:
elink -versionthenelink -helpto confirm flags
If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying.
Entrez Link
"Find records linked to this record in another NCBI database" -> ELink walks the curated, weekly-maintained link tables between Entrez databases. A link is an asserted relationship (e.g. "this PubMed article describes this nucleotide sequence"), not a similarity hit.
ELink is the navigation layer of Entrez. The decision that matters most is which linkname to use — not which databases. A single (dbfrom, db) pair can have a dozen linkname variants distinguishing curation level, evidence type, and direction. Picking the wrong one is the difference between 5 high-confidence matches and 500 noisy automated assertions.
- Python:
Entrez.elink(dbfrom=..., db=..., id=..., linkname=...)(BioPython) - CLI:
elink -db pubmed -target gene -name pubmed_gene_rif(Entrez Direct) - R:
entrez_link(dbfrom=..., db=..., id=...)(rentrez)
Required Setup
from Bio import Entrez
Entrez.email = '[email protected]'
Entrez.api_key = 'optional_api_key' # raises rate to 10 req/sec
The linkname decision (most important)
For most (dbfrom, db) pairs NCBI exposes multiple link tables. The qualifiers in the name encode the curation level and the evidence source. Choose deliberately.
gene -> protein (representative example)
| linkname | Returns | When to use |
|---|---|---|
gene_protein |
All linked proteins (curated + automated) | Exploration; expect 10-1000x more hits |
gene_protein_refseq |
RefSeq proteins only | Reference-quality analyses; orthology |
gene_protein_swissprot |
Reviewed UniProt entries with NCBI cross-ref | Functional annotation; literature support |
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.
- 9d ago First seen · 353 lines · 89 tokens per session scan A e2277b5d2d25
bio-entrez-link is a skill published in the GitHub repository GPTomics/bioSkills (1,201 stars, last pushed 27d ago), licensed MIT. It adds 89 tokens to every session and 4,275 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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