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Ena Database

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foryourhealth111-pixel
ena-database

Access European Nucleotide Archive via API/FTP. Retrieve DNA/RNA sequences, raw reads (FASTQ), genome assemblies by accession, for genomics and bioinformatics pipelines. Supports multiple formats.

Overview

Publisherforyourhealth111-pixel
RepositoryVibe-Skills
Skill nameena-database
Stars
3.3K
Forks
288
Bundled files
1
LicenseApache-2.0
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.

  • 1 bundled files

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

  • Open source

    Published by foryourhealth111-pixel on GitHub. Read the source before you install it.

Installation

Install the Ena Database 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.
  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/foryourhealth111-pixel/Vibe-Skills.git /tmp/Vibe-Skills
mkdir -p .claude/skills
cp -r /tmp/Vibe-Skills/bundled/skills/ena-database .claude/skills/ena-database
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ena Database 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 Ena Database 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 Ena Database 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.

ENA Database

Overview

The European Nucleotide Archive (ENA) is a comprehensive public repository for nucleotide sequence data and associated metadata. Access and query DNA/RNA sequences, raw reads, genome assemblies, and functional annotations through REST APIs and FTP for genomics and bioinformatics pipelines.

When to Use This Skill

This skill should be used when:

  • Retrieving nucleotide sequences or raw sequencing reads by accession
  • Searching for samples, studies, or assemblies by metadata criteria
  • Downloading FASTQ files or genome assemblies for analysis
  • Querying taxonomic information for organisms
  • Accessing sequence annotations and functional data
  • Integrating ENA data into bioinformatics pipelines
  • Performing cross-reference searches to related databases
  • Bulk downloading datasets via FTP or Aspera

Core Capabilities

1. Data Types and Structure

ENA organizes data into hierarchical object types:

Studies/Projects - Group related data and control release dates. Studies are the primary unit for citing archived data.

Samples - Represent units of biomaterial from which sequencing libraries were produced. Samples must be registered before submitting most data types.

Raw Reads - Consist of:

  • Experiments: Metadata about sequencing methods, library preparation, and instrument details
  • Runs: References to data files containing raw sequencing reads from a single sequencing run

Assemblies - Genome, transcriptome, metagenome, or metatranscriptome assemblies at various completion levels.

Sequences - Assembled and annotated sequences stored in the EMBL Nucleotide Sequence Database, including coding/non-coding regions and functional annotations.

Analyses - Results from computational analyses of sequence data.

Taxonomy Records - Taxonomic information including lineage and rank.

2. Programmatic Access

ENA provides multiple REST APIs for data access. Consult references/api_reference.md for detailed endpoint documentation.

Key APIs:

ENA Portal API - Advanced search functionality across all ENA data types

ENA Browser API - Direct retrieval of records and metadata

ENA Taxonomy REST API - Query taxonomic information

  • Access lineage, rank, and related taxonomic data

ENA Cross Reference Service - Access related records from external databases

CRAM Reference Registry - Retrieve reference sequences

Rate Limiting: All APIs have a rate limit of 50 requests per second. Exceeding this returns HTTP 429 (Too Many Requests).

3. Searching and Retrieving Data

Browser-Based Search:

  • Free text search across all fields
  • Sequence similarity search (BLAST integration)
  • Cross-reference search to find related records
  • Advanced search with Rulespace query builder

Programmatic Queries:

  • Use Portal API for advanced searches at scale
  • Filter by data type, date range, taxonomy, or metadata fields
  • Download results as tabulated metadata summaries or XML records

Example API Query Pattern:

python
import requests

# Search for samples from a specific study
base_url = "https://www.ebi.ac.uk/ena/portal/api/search"
params = {
    "result": "sample",
    "query": "study_accession=PRJEB1234",
    "format": "json",
    "limit": 100
}

response = requests.get(base_url, params=params)
samples = response.json()

4. Data Retrieval Formats

Metadata Formats:

  • XML (native ENA format)
  • JSON (via Portal API)
  • TSV/CSV (tabulated summaries)

Sequence Data:

  • FASTQ (raw reads)
  • BAM/CRAM (aligned reads)
  • FASTA (assembled sequences)
  • EMBL flat file format (annotated sequences)

Download Methods:

  • Direct API download (small files)
  • FTP for bulk data transfer
  • Aspera for high-speed transfer of large datasets
  • enaBrowserTools command-line utility for bulk downloads

5. Common Use Cases

Retrieve raw sequencing reads by accession:

python
# Download run files using Browser API
accession = "ERR123456"
url = f"https://www.ebi.ac.uk/ena/browser/api/xml/{accession}"

Search for all samples in a study:

python
# Use Portal API to list samples
study_id = "PRJNA123456"
url = f"https://www.ebi.ac.uk/ena/portal/api/search?result=sample&query=study_accession={study_id}&format=tsv"

Find assemblies for a specific organism:

python
# Search assemblies by taxonomy
organism = "Escherichia coli"
url = f"https://www.ebi.ac.uk/ena/portal/api/search?result=assembly&query=tax_tree({organism})&format=json"

Get taxonomic lineage:

python
# Query taxonomy API
taxon_id = "562"  # E. coli
url = f"https://www.ebi.ac.uk/ena/taxonomy/rest/tax-id/{taxon_id}"

6. Integration with Analysis Pipelines

Bulk Download Pattern:

  1. Search for accessions matching criteria using Portal API
  2. Extract file URLs from search results
  3. Download files via FTP or using enaBrowserTools
  4. Process downloaded data in pipeline

BLAST Integration: Integrate with EBI's NCBI BLAST service (REST/SOAP API) for sequence similarity searches against ENA sequences.

7. Best Practices

Rate Limiting:

  • Implement exponential backoff when receiving HTTP 429 responses
  • Batch requests when possible to stay within 50 req/sec limit
  • Use bulk download tools for large datasets instead of iterating API calls

Data Citation:

  • Always cite using Study/Project accessions when publishing
  • Include accession numbers for specific samples, runs, or assemblies used

API Response Handling:

  • Check HTTP status codes before processing responses
  • Parse XML responses using proper XML libraries (not regex)
  • Handle pagination for large result sets

Performance:

  • Use FTP/Aspera for downloading large files (>100MB)
  • Prefer TSV/JSON formats over XML when only metadata is needed
  • Cache taxonomy lookups locally when processing many records

Resources

This skill includes detailed reference documentation for working with ENA:

references/

api_reference.md - Comprehensive API endpoint documentation including:

  • Detailed parameters for Portal API and Browser API
  • Response format specifications
  • Advanced query syntax and operators
  • Field names for filtering and searching
  • Common API patterns and examples

Load this reference when constructing complex API queries, debugging API responses, or needing specific parameter details.

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 Ena Database AI skill do?

Access European Nucleotide Archive via API/FTP. Retrieve DNA/RNA sequences, raw reads (FASTQ), genome assemblies by accession, for genomics and bioinformatics pipelines. Supports multiple formats.

Why use Ena Database on TypingMind?

Because you install it once and use it with any model. Ena Database 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 Ena Database in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/foryourhealth111-pixel/Vibe-Skills/tree/main/bundled/skills/ena-database. 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 Ena Database?

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 Ena Database?

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

Is the Ena Database AI skill free?

Yes. It is published on GitHub by foryourhealth111-pixel under the Apache-2.0 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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