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 beita6969/ScienceClaw --skill gene-databasegit clone --depth 1 https://github.com/beita6969/ScienceClawWrote 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/beita6969/scienceclaw/gene-database)<a href="https://agentmods.dev/skills/beita6969/scienceclaw/gene-database"><img src="https://agentmods.dev/badge/skills/beita6969/scienceclaw/gene-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 5.1 | $0.00049 | $0.01451 |
| Opus 5 | $0.00024 | $0.00726 |
| Sonnet 5 | $0.00010 | $0.00290 |
| Haiku 4.5 | $0.00005 | $0.00145 |
Grade A, and why
gene-database 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 4d 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.
This is a copy
98% identical to gene-database — 3 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 — 178 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Gene Database
Overview
NCBI Gene is a comprehensive database integrating gene information from diverse species. It provides nomenclature, reference sequences (RefSeqs), chromosomal maps, biological pathways, genetic variations, phenotypes, and cross-references to global genomic resources.
When to Use This Skill
This skill should be used when working with gene data including searching by gene symbol or ID, retrieving gene sequences and metadata, analyzing gene functions and pathways, or performing batch gene lookups.
Quick Start
NCBI provides two main APIs for gene data access:
- E-utilities (Traditional): Full-featured API for all Entrez databases with flexible querying
- NCBI Datasets API (Newer): Optimized for gene data retrieval with simplified workflows
Choose E-utilities for complex queries and cross-database searches. Choose Datasets API for straightforward gene data retrieval with metadata and sequences in a single request.
Common Workflows
Search Genes by Symbol or Name
To search for genes by symbol or name across organisms:
- Use the
scripts/query_gene.pyscript with E-utilities ESearch - Specify the gene symbol and organism (e.g., "BRCA1 in human")
- The script returns matching Gene IDs
Example query patterns:
- Gene symbol:
insulin[gene name] AND human[organism] - Gene with disease:
dystrophin[gene name] AND muscular dystrophy[disease] - Chromosome location:
human[organism] AND 17q21[chromosome]
Retrieve Gene Information by ID
To fetch detailed information for known Gene IDs:
- Use
scripts/fetch_gene_data.pywith the Datasets API for comprehensive data - Alternatively, use
scripts/query_gene.pywith E-utilities EFetch for specific formats - Specify desired output format (JSON, XML, or text)
The Datasets API returns:
- Gene nomenclature and aliases
- Reference sequences (RefSeqs) for transcripts and proteins
- Chromosomal location and mapping
- Gene Ontology (GO) annotations
- Associated publications
What ships with it
5 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.
- 4d ago First seen · 178 lines · 49 tokens per session scan A a753c23abc6d
gene-database is a skill published in the GitHub repository beita6969/ScienceClaw (895 stars, last pushed 3mo ago), licensed MIT. It adds 49 tokens to every session and 1,451 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 98% identical to gene-database, differing in 3 lines, and is treated as a copy.
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