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/thesecondfox/skill/bio-database-access-entrez-fetchnpx skills add thesecondfox/skill --skill bio-database-access-entrez-fetchgit clone --depth 1 https://github.com/thesecondfox/skillWrote 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/thesecondfox/skill/bio-database-access-entrez-fetch)<a href="https://agentmods.dev/skills/thesecondfox/skill/bio-database-access-entrez-fetch"><img src="https://agentmods.dev/badge/skills/thesecondfox/skill/bio-database-access-entrez-fetch.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 5.1 | $0.00047 | $0.02775 |
| Opus 5 | $0.00023 | $0.01388 |
| Sonnet 5 | $0.00009 | $0.00555 |
| Haiku 4.5 | $0.00005 | $0.00278 |
Grade A, and why
bio-entrez-fetch 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 5d 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.
How it starts
The opening of the file, as written. The whole thing — 335 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 <package>thenhelp(module.function)to check signatures
If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying.
Entrez Fetch
"Download a sequence from NCBI" → Retrieve a record by accession from an NCBI database and parse it into a usable object.
- Python:
Entrez.efetch()+SeqIO.read()(BioPython) - CLI:
efetch -db nucleotide -id NM_007294 -format fasta(Entrez Direct) - R:
entrez_fetch()(rentrez)
Retrieve records from NCBI databases using Biopython's Entrez module (EFetch, ESummary utilities).
Required Setup
from Bio import Entrez
Entrez.email = '[email protected]' # Required by NCBI
Entrez.api_key = 'your_api_key' # Optional, raises rate limit 3->10 req/sec
Core Functions
Entrez.efetch() - Retrieve Full Records
Fetch complete records in various formats from any NCBI database.
# Fetch GenBank record by ID
handle = Entrez.efetch(db='nucleotide', id='NM_007294', rettype='gb', retmode='text')
genbank_text = handle.read()
handle.close()
# Fetch FASTA sequence
handle = Entrez.efetch(db='nucleotide', id='NM_007294', rettype='fasta', retmode='text')
fasta_text = handle.read()
handle.close()
# Fetch multiple records
handle = Entrez.efetch(db='nucleotide', id='NM_007294,NM_000059', rettype='fasta', retmode='text')
Key Parameters:
| Parameter | Description | Example |
|---|---|---|
db |
Database name | 'nucleotide', 'protein', 'pubmed' |
id |
Record ID(s) | 'NM_007294' or '123,456,789' |
rettype |
Return type | 'fasta', 'gb', 'abstract' |
retmode |
Return mode | 'text', 'xml' |
retstart |
Start index | 0 |
retmax |
Max records | 20 |
WebEnv |
History server session | From esearch |
query_key |
History server query | From esearch |
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.
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.
- 5d ago First seen · 335 lines · 47 tokens per session scan A 5b573356e531
bio-entrez-fetch is a skill published in the GitHub repository thesecondfox/skill (3 stars, last pushed 5mo ago), licensed MIT. It adds 47 tokens to every session and 2,775 once invoked, about $0.0002 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 2026-08-31.
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