Ncbi Gene logo

Ncbi Gene

Organization
ai4protein
ncbi_gene

Query NCBI Gene via E-utilities/Datasets API. Search by symbol/ID, retrieve gene info (RefSeqs, GO, locations, phenotypes), batch lookups, for gene annotation and functional analysis.

Overview

Publisherai4protein
RepositoryVenusFactory2
Skill namencbi_gene
Stars
255
Forks
37
Bundled files
2
LicenseUnknown
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by ai4protein on GitHub. Read the source before you install it.

Installation

Install the Ncbi Gene AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/ai4protein/VenusFactory2/tree/main/src/agent/skills/ncbi_gene
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/ai4protein/VenusFactory2.git /tmp/VenusFactory2
mkdir -p .claude/skills
cp -r /tmp/VenusFactory2/src/agent/skills/ncbi_gene .claude/skills/ncbi_gene
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ncbi Gene in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Ncbi Gene on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Ncbi Gene is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

NCBI 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. In this project the agent exposes 3 download tools: fetch gene data by ID or symbol (Datasets API), and batch lookup by symbols. For finer control, ncbi_operations.py also provides E-utilities download/query functions (esearch, esummary, efetch) and additional batch operations. All download/query functions return rich JSON {status, file_info/content, content_preview, biological_metadata, execution_context}.

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

The skill provides:

  1. Project modules in src/tools/database/ncbi/: fetch_gene_data.py (Datasets API), query_gene.py (E-utilities), batch_gene_lookup.py (batch operations), ncbi_operations.py (query/download operations); gene download functions re-exported via package.
  2. References: references/api_reference.md, references/common_workflows.md

NCBI provides two main APIs:

  • Datasets API — Optimized for gene data retrieval; used by download_ncbi_gene_by_id and download_ncbi_gene_by_symbol tools
  • E-utilities — Full-featured API for complex queries; used by the esearch/esummary/efetch programmatic functions

Agent Tools (Download Only)

Tool nameArgumentsPurpose
download_ncbi_gene_by_idgene_id, out_pathDownload gene data by NCBI Gene ID (Datasets API) to JSON
download_ncbi_gene_by_symbolsymbol, taxon, out_pathDownload gene data by symbol and organism (Datasets API) to JSON
download_ncbi_batch_lookup_by_symbolsgene_symbols, organism, out_pathBatch lookup multiple genes by symbols to JSON

Also available as general NCBI tools (useful in gene workflows):

Tool nameArgumentsPurpose
download_ncbi_sequencencbi_id, out_path, db (optional)Download NCBI sequence by accession (FASTA)
download_ncbi_metadatancbi_id, out_path, db, rettype (optional)Download NCBI metadata (GenBank/XML)
download_ncbi_blastsequence, out_path, program, database, etc.Submit BLAST search and download XML

Project Modules (Programmatic Use)

CapabilityFunctionModulePurpose
Fetch by IDfetch_gene_by_id(gene_id, api_key)fetch_gene_data.pyDatasets API: gene data as dict
Fetch by symbolfetch_gene_by_symbol(symbol, taxon, api_key)fetch_gene_data.pyDatasets API: gene data as dict
Fetch multiplefetch_multiple_genes(gene_ids, api_key)fetch_gene_data.pyDatasets API: multiple genes at once
Taxon lookupget_taxon_id(taxon_name)fetch_gene_data.pyConvert name to NCBI taxon ID
E-util searchesearch(query, retmax, api_key)query_gene.pySearch Gene DB, returns Gene IDs
E-util summaryesummary(gene_ids, api_key)query_gene.pyGet document summaries by Gene IDs
E-util fetchefetch(gene_ids, retmode, api_key)query_gene.pyFetch full gene records (XML/text)
Search+summarizesearch_and_summarize(query, organism, max_results, api_key)query_gene.pyConvenience: search + display
Batch searchbatch_esearch(queries, organism, api_key)batch_gene_lookup.pySearch multiple symbols → ID map
Batch summarybatch_esummary(gene_ids, api_key, chunk_size)batch_gene_lookup.pySummaries in chunks
Batch by IDsbatch_lookup_by_ids(gene_ids, api_key)batch_gene_lookup.pyStructured gene data by IDs
Batch by symbolsbatch_lookup_by_symbols(gene_symbols, organism, api_key)batch_gene_lookup.pyStructured gene data by symbols
Query: by IDquery_ncbi_gene_by_id(gene_id)ncbi_operations.pyReturns rich JSON in memory
Query: by symbolquery_ncbi_gene_by_symbol(symbol, taxon)ncbi_operations.pyReturns rich JSON in memory
Query: esearchquery_ncbi_gene_esearch(query, retmax)ncbi_operations.pyReturns rich JSON in memory
Query: esummaryquery_ncbi_gene_esummary(gene_ids)ncbi_operations.pyReturns rich JSON in memory
Query: efetchquery_ncbi_gene_efetch(gene_ids, retmode)ncbi_operations.pyReturns rich JSON in memory
Query: batch searchquery_ncbi_batch_esearch(queries, organism)ncbi_operations.pyReturns rich JSON in memory
Query: batch by IDsquery_ncbi_batch_lookup_by_ids(gene_ids)ncbi_operations.pyReturns rich JSON in memory
Query: batch by symbolsquery_ncbi_batch_lookup_by_symbols(gene_symbols, organism)ncbi_operations.pyReturns rich JSON in memory
Download: by IDdownload_ncbi_gene_by_id(gene_id, out_path)ncbi_operations.pySave to file, return rich JSON
Download: by symboldownload_ncbi_gene_by_symbol(symbol, taxon, out_path)ncbi_operations.pySave to file, return rich JSON
Download: esearchdownload_ncbi_gene_esearch(query, out_path, retmax)ncbi_operations.pySave to file, return rich JSON
Download: esummarydownload_ncbi_gene_esummary(gene_ids, out_path)ncbi_operations.pySave to file, return rich JSON
Download: efetchdownload_ncbi_gene_efetch(gene_ids, out_path, retmode)ncbi_operations.pySave to file, return rich JSON
Download: batch searchdownload_ncbi_batch_esearch(queries, out_path, organism)ncbi_operations.pySave to file, return rich JSON
Download: batch by IDsdownload_ncbi_batch_lookup_by_ids(gene_ids, out_path)ncbi_operations.pySave to file, return rich JSON
Download: batch by symbolsdownload_ncbi_batch_lookup_by_symbols(gene_symbols, organism, out_path)ncbi_operations.pySave to file, return rich JSON

Core Capabilities

1. Download Gene by ID (Datasets API)

python
from src.tools.database.ncbi import download_ncbi_gene_by_id

result = download_ncbi_gene_by_id("672", "output/ncbi_gene_brca1.json")
# Returns rich JSON with gene metadata, RefSeqs, GO annotations, etc.

2. Download Gene by Symbol (Datasets API)

python
from src.tools.database.ncbi import download_ncbi_gene_by_symbol

result = download_ncbi_gene_by_symbol("BRCA1", "human", "output/ncbi_gene_brca1_by_symbol.json")
result = download_ncbi_gene_by_symbol("TP53", "Homo sapiens", "output/ncbi_gene_tp53.json")

3. Batch Lookup by Symbols

python
from src.tools.database.ncbi import download_ncbi_batch_lookup_by_symbols

result = download_ncbi_batch_lookup_by_symbols(
    ["BRCA1", "TP53", "EGFR"], "human", "output/ncbi_genes_batch.json"
)

4. E-utilities Workflow (programmatic)

python
from src.tools.database.ncbi.ncbi_operations import (
    query_ncbi_gene_esearch,
    download_ncbi_gene_esummary,
    download_ncbi_gene_efetch,
)

# Step 1: Search for gene IDs
esearch_result = query_ncbi_gene_esearch("BRCA1[gene] AND human[organism]", retmax=10)

# Step 2: Download summaries or full records
download_ncbi_gene_esummary(["672", "7157"], "output/gene_summaries.json")
download_ncbi_gene_efetch(["672"], "output/gene_full_record.xml")

5. Low-Level Direct Access (programmatic)

python
from src.tools.database.ncbi.fetch_gene_data import fetch_gene_by_id, fetch_gene_by_symbol
from src.tools.database.ncbi.query_gene import esearch, esummary, efetch
from src.tools.database.ncbi.batch_gene_lookup import batch_lookup_by_symbols

# Datasets API
gene_data = fetch_gene_by_id("672")
gene_data = fetch_gene_by_symbol("BRCA1", "human")

# E-utilities
gene_ids = esearch("insulin[gene] AND human[organism]")
summaries = esummary(gene_ids)
records = efetch(gene_ids, retmode="xml")

# Batch
results = batch_lookup_by_symbols(["BRCA1", "TP53"], "human")

Common Workflows

Workflow 1: Gene Annotation (download)

python
from src.tools.database.ncbi import (
    download_ncbi_gene_by_symbol,
    download_ncbi_batch_lookup_by_symbols,
)

# Single gene
download_ncbi_gene_by_symbol("BRCA1", "human", "output/brca1_annotation.json")

# Gene panel
download_ncbi_batch_lookup_by_symbols(
    ["BRCA1", "BRCA2", "TP53", "PTEN", "ATM"], "human", "output/cancer_panel.json"
)

Workflow 2: Gene Search and Retrieve (programmatic)

python
from src.tools.database.ncbi.ncbi_operations import (
    query_ncbi_gene_esearch,
    download_ncbi_gene_by_id,
)
import json

# Search by complex query
result = query_ncbi_gene_esearch("p53 AND human[organism]", retmax=5)
parsed = json.loads(result)

# Download details for each hit
if parsed.get("status") == "success":
    content = json.loads(parsed["content"])
    for gene_id in content.get("gene_ids", []):
        download_ncbi_gene_by_id(str(gene_id), f"output/gene_{gene_id}.json")

Workflow 3: Cross-Database Integration

python
from src.tools.database.ncbi import (
    download_ncbi_gene_by_id,
    download_ncbi_sequence,
    download_ncbi_metadata,
)

# Step 1: Get comprehensive gene info
download_ncbi_gene_by_id("672", "output/brca1_gene_info.json")

# Step 2: Download protein sequence
download_ncbi_sequence("NP_009225.1", "output/brca1_protein.fasta", db="protein")

# Step 3: Download GenBank metadata
download_ncbi_metadata("NP_009225.1", "output/brca1_metadata.gb", db="protein")

Search Query Patterns

Example E-utilities query patterns for NCBI Gene:

  • 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]
  • GO term: GO:0006915[biological process] (apoptosis)
  • Phenotype: diabetes[phenotype] AND mouse[organism]
  • Pathway: insulin signaling pathway[pathway]

API Access

Rate Limits:

  • Without API key: 3 requests/second for E-utilities, 5 requests/second for Datasets API
  • With API key: 10 requests/second for both APIs

Authentication: Register for a free NCBI API key at https://www.ncbi.nlm.nih.gov/account/ to increase rate limits.

Data Formats

NCBI Gene data can be retrieved in multiple formats:

FormatUse case
JSONModern applications, programmatic processing
XMLLegacy systems, detailed metadata
GenBankSequence data with annotations
FASTASequence analysis workflows

Best Practices

  1. Always specify organism when searching by gene symbol to avoid ambiguity
  2. Use Gene IDs for precise lookups when available
  3. Batch requests when working with multiple genes to minimize API calls
  4. Cache results locally to reduce redundant queries
  5. Include API key in environment for higher rate limits
  6. Handle errors gracefully with retry logic for transient failures

Resources

Helper Scripts

  • fetch_gene_data.py — NCBI Datasets API: fetch_gene_by_id(), fetch_gene_by_symbol(), fetch_multiple_genes()
  • query_gene.py — E-utilities: esearch(), esummary(), efetch(), search_and_summarize()
  • batch_gene_lookup.py — Batch: batch_esearch(), batch_esummary(), batch_lookup_by_ids(), batch_lookup_by_symbols()

Reference Documentation

  • references/api_reference.md — E-utilities and Datasets API documentation, endpoints, parameters, response formats
  • references/common_workflows.md — Additional examples and use case patterns

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Ncbi Gene AI skill do?

Query NCBI Gene via E-utilities/Datasets API. Search by symbol/ID, retrieve gene info (RefSeqs, GO, locations, phenotypes), batch lookups, for gene annotation and functional analysis.

Why use Ncbi Gene on TypingMind?

Because you install it once and use it with any model. Ncbi Gene is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Ncbi Gene in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/ai4protein/VenusFactory2/tree/main/src/agent/skills/ncbi_gene. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Ncbi Gene?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Ncbi Gene?

As many as you like. As long as a model supports skills, you can use Ncbi Gene with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Ncbi Gene AI skill free?

Yes. It is published on GitHub by ai4protein under the Unknown license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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