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Embl Ebi Ols

Google DeepMindOfficialPublished by Google DeepMind

  • Skill
  • Tool integration
  • Science and research
  • Apache-2.0
  • Low risk
  • Has scripts

From the author

Query and search the EMBL-EBI Ontology Lookup Service (OLS) for biomedical ontology terms, definitions, and hierarchies across 250+ ontologies (e.g., GO, DOID, HP). Use when the user asks to search for terms, retrieve details, navigate hierarchies (parents, children, ancestors), look up properties and individuals, get autocomplete suggestions, or access ontology metadata and statistics.
— the description by Google DeepMind

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

The embl-ebi-ols skill provides an interface to the EMBL-EBI Ontology Lookup Service (OLS), enabling users to programmatically access over 250 biomedical ontologies. It facilitates searching for terms, retrieving detailed metadata, and navigating hierarchical relationships such as parents, children, and ancestors. The skill includes a suite of utility scripts for interacting with the OLS API, supporting tasks ranging from simple term lookups to complex graph structure exploration across standard ontologies like GO, DOID, and HP.

What it does

  • Search for biomedical terms across 250+ ontologies
  • Retrieve detailed definitions and metadata for specific ontology terms
  • Navigate hierarchical structures including parents, children, and ancestors
  • Support both direct is-a relationships and transitive hierarchical relations
  • Provide autocomplete suggestions for partial term names
  • Access ontology-level statistics and metadata

When to use it

  • When you need to define a disease, phenotype, or biological term
  • When exploring the hierarchy or sub-types of a specific ontology term
  • When mapping user-provided strings to authoritative ontology IDs
  • When performing cross-ontology research or data annotation
  • When you need to identify root terms or property details within an ontology

Advantages

  • Enforces rate limiting to respect EBI's Terms of Use
  • Provides standardized utility scripts for consistent API interaction
  • Supports both OBO ID and IRI formats for flexible querying
  • Enables navigation of complex transitive relationships like part-of or develops-from
  • Facilitates precise entity resolution using exact match flags

Usage examples

“What is the definition of the GO term GO:0005634?”
The agent uses get_term.py to retrieve and display the definition and metadata for the specified Gene Ontology term.
“Find the parent terms for myocardial infarction in the Disease Ontology.”
The agent performs a two-step process: searching for the term to get its ID, then querying the OLS for its hierarchical parents.
“Give me autocomplete suggestions for 'diabet'.”
The agent uses suggest_ols.py to return a list of potential matches starting with the provided string.
“List the root terms for the Human Phenotype Ontology.”
The agent uses get_term.py with the --roots flag to retrieve the top-level terms for the HP ontology.

Install

  1. Download the skill as a ZIP:

    https://autogineer.com/agent-skills/google-deepmind/embl-ebi-ols/download
  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip embl-ebi-ols.zip -d .agents/skills

Documentation by Google DeepMind

EMBL-EBI Ontology Lookup Service (OLS)

Prerequisites

  1. uv: Read the uv skill and follow its Setup instructions to ensure uv is installed and on PATH.

  2. User Notification: If .licenses/embl_ebi_ols_LICENSE.txt does not already exist in the workspace root directory then (1) prominently notify the user to check the terms at https://www.ebi.ac.uk/ols4/api-docs, then (2) create the file recording the notification text and timestamp.

Core Rules

  • [!IMPORTANT] Use the Utility Scripts: You MUST ALWAYS use the provided utility script under scripts/ for all API interactions, including checking status. NEVER use curl or custom Python requests to query API directly.

  • Rate Limiting & Resilience: You MUST respect EBI's Terms of Use with a maximum 5 requests per second. The provided utility scripts automatically enforce this.

  • Notification: If this skill is used, ensure this is mentioned in the output.

When to Use — Quick Recipes

Use this skill whenever a user query matches one of these patterns:

  • Definition of a disease, phenotype, or term → get_term.py --obo_id <ID> --summary

  • Subtypes or children of a term → get_term.py --obo_id <ID> --relations children

  • Parent of a term → get_term.py --obo_id <ID> --relations parents

  • Ancestors / disease categories / classified under → get_term.py --obo_id <ID> --relations ancestors

  • Root terms of an ontology → get_term.py --ontology <id> --roots

  • Hierarchical parents (is-a + part-of) → get_term.py --obo_id <ID> --relations hierarchicalParents

  • Structures part of / hierarchical children → get_term.py --obo_id <ID> --relations hierarchicalChildren

  • Compare direct vs hierarchical parents → get_term.py --obo_id <ID> --relations parents,hierarchicalParents

  • Search for a term (e.g., "apoptosis" in GO) → search_ols.py --query "..." --ontology <id>

  • Find a GO term matching a function → search_ols.py --query "..." --ontology go --exact

  • Search in MONDO, CHEBI, CL, UBERON → search_ols.py --query "..." --ontology <id> --defining

  • Paginate search results / next page → search_ols.py --query "..." --rows N --start <offset>

  • Autocomplete a partial name → suggest_ols.py --query "..."

  • Ontology metadata (e.g., EFO info) → get_ontology.py --id <id>

  • OLS index statistics → get_stats.py

Multi-step queries (e.g., "What is the parent of myocardial infarction?"): When the user names a term but you don't know its OBO ID, complete in exactly 2 steps — do NOT search across multiple ontologies:

  1. Search in the single most appropriate ontology: search_ols.py --query "myocardial infarction" --ontology doid --exact --rows 1 --output /tmp/step1.json

  2. Get relations using the OBO ID from step 1: get_term.py --obo_id DOID:5844 --relations parents --output /tmp/step2.json

Ontology selection rule: ALWAYS use doid for common human diseases (e.g., diabetes, cancer), hp for phenotypes, go for gene functions, chebi for chemicals, uberon for anatomy, cl for cell types. Use mondo ONLY when cross-species context is explicitly mentioned or needed.

Utility Scripts

1. Search Terms Across Ontologies

Search for ontology terms by keyword and return clean JSON.

uv run scripts/search_ols.py --query "diabetes" \
  --rows 5 --output /tmp/ols_search_results.json 2>/dev/null

Important: --output is required for all scripts. Results are always written to the specified file. For larger output, you can limit --rows (e.g., 5-10) or paginate using --start.

Returned Fields: JSON results include iri, label, description, ontology_name, ontology_prefix, obo_id, short_form, type, is_defining_ontology, and exact_synonyms.

Pagination: Output includes a pagination block with start, rows, and has_more so you can decide whether to fetch more results.

Options:

  • --query: Search string (required). Searches labels, synonyms, descriptions, and identifiers.

  • --ontology: Filter by ontology ID (e.g., go, doid, efo, hp). Recommended when you know which ontology to search — avoids noise from 250+ ontologies.

  • --type: Filter by entity type: class, property, individual, or ontology.

  • --exact: Flag for exact label match only. Use this for entity resolution when mapping a user's string to a specific ontology term ID.

  • --defining: Only return terms from their defining (authoritative) ontology. E.g., GO:0005634 only from GO, not cross-referenced copies.

  • --obsolete: Flag to include obsolete terms in results.

  • --local: Only return terms in their defining ontology.

  • --childrenOf: Restrict to children of given term IRI(s), comma-separated.

  • --allChildrenOf: Restrict to all children including transitive relations (part of, develops from), comma-separated IRIs.

  • --queryFields: Comma-separated fields to search in (e.g., label,synonym,description).

  • --fieldList: Comma-separated fields to return.

  • --groupField: Group results by unique IRI.

  • --isLeaf: Only return leaf terms (no children).

  • --rows: Number of results to return (default 10).

  • --start: Pagination offset (default 0).

  • --output: File path to save results (required).

2. Autocomplete / Suggest

Get autocomplete suggestions for partial term names.

uv run scripts/suggest_ols.py --query "diabet" --rows 5 \
  --output /tmp/ols_suggest.json 2>/dev/null

Options:

  • --query: Partial term to autocomplete (required).

  • --ontology: Filter by ontology ID(s), comma-separated.

  • --rows: Number of suggestions (default 10).

  • --start: Pagination offset (default 0).

  • --output: File path to save results (default: stdout).

3. Get Term Details

Retrieve full details for a specific ontology term by its OBO ID or IRI.

uv run scripts/get_term.py --obo_id "GO:0005634" \
  --output /tmp/ols_term.json 2>/dev/null

Returned Fields: JSON includes iri, label, description, obo_id, synonyms, ontology_name, is_obsolete, is_defining_ontology, has_children, is_root, annotation, in_subset, and any requested relations.

Summary Mode: Use --summary to get a clean, human-readable block on stdout (Label, OBO ID, Ontology, Definition, Synonyms). The full JSON is always saved to the --output file.

uv run scripts/get_term.py --obo_id "GO:0005634" --summary \
  --output /tmp/nucleus_full.json

Options:

  • --obo_id: OBO-style identifier (e.g., GO:0005634, DOID:9351). Mutually exclusive with --iri. Auto-converts to IRI with double encoding.

  • --iri: Full IRI of the term. Mutually exclusive with --obo_id.

  • --ontology: Ontology ID (auto-derived from --obo_id if not provided).

  • --relations: Comma-separated list of relations to fetch.

    • Direct (is-a only): parents, children, ancestors, descendants

    • Hierarchical (is-a + transitive like "part of", "develops from"): hierarchicalParents, hierarchicalChildren, hierarchicalAncestors, hierarchicalDescendants

    • Graph: graph — full graph JSON for a term

    Note: Use hierarchical variants for anatomical/developmental ontologies (UBERON, CL) where transitive relations like "part of" and "develops from" are critical for navigating the hierarchy.

  • --roots: List root terms of the ontology (requires --ontology).

  • --preferred_roots: List preferred root terms (requires --ontology).

  • --summary: Human-readable summary on stdout, full JSON to --output.

  • --output: File path to save results (default: stdout).

4. Get Property Details

Retrieve details for an ontology property (relation type) with hierarchy.

uv run scripts/get_property.py --obo_id "BFO:0000051" --ontology go \
  --output /tmp/ols_property.json 2>/dev/null

Options:

  • --obo_id: OBO-style ID of the property. Mutually exclusive with --iri.

  • --iri: Full IRI of the property. Mutually exclusive with --obo_id.

  • --ontology: Ontology ID (required with --iri).

  • --relations: Comma-separated: parents, children, ancestors, descendants.

  • --roots: List root properties of the ontology (requires --ontology).

  • --output: File path to save results (default: stdout).

5. Get Individual Details

Retrieve details for an ontology individual (instance).

uv run scripts/get_individual.py --obo_id "IAO:0000103" --ontology iao --types \
  --output /tmp/ols_individual.json 2>/dev/null

Options:

  • --obo_id: OBO-style ID. Mutually exclusive with --iri.

  • --iri: Full IRI. Mutually exclusive with --obo_id.

  • --ontology: Ontology ID (required with --iri).

  • --types: Fetch the direct types (classes) of this individual.

  • --alltypes: Fetch all types including ancestor classes.

  • --output: File path to save results (default: stdout).

6. Get Ontology Information

List available ontologies or retrieve details for a specific one.

uv run scripts/get_ontology.py --id go \
  --output /tmp/ols_ontology.json 2>/dev/null

Options:

  • --id: Specific ontology ID (e.g., go, efo, doid). If omitted, lists all ontologies.

  • --page: Page number for pagination (default 0).

  • --size: Number of ontologies per page (default 20).

  • --output: File path to save results (default: stdout).

7. Get OLS Statistics

Retrieve index statistics (total ontologies, classes, properties, individuals).

uv run scripts/get_stats.py --output /tmp/ols_stats.json 2>/dev/null

Options:

  • --output: File path to save results (default: stdout).

Reference

Workflow

  1. Use suggest_ols.py for autocomplete when you have a partial term name.

  2. Search for terms using search_ols.py. Use --defining to prioritize authoritative definitions. Use --exact for entity resolution.

  3. If full details are needed, use get_term.py with the OBO ID or IRI. Use --summary for a concise view.

  4. To explore a term's hierarchy, use get_term.py --relations parents,children for is-a only, or --relations hierarchicalParents,hierarchicalChildren for "part of" etc.

  5. To explore from the top down, use get_term.py --ontology go --roots.

  6. For properties or individuals, use get_property.py or get_individual.py.

  7. To discover available ontologies, use get_ontology.py.

  8. To check OLS index status, use get_stats.py.

Files

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Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

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Needs: Needs Python

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Attribution and licence

Published by
Google DeepMind
Publisher
Google DeepMind (Official)
Source
google-deepmind/science-skills · skills/embl_ebi_ols · commit 4de6786
Licence
Apache License 2.0 (redistribution allowed)
  • LICENSE (added by AutoGineer from LICENSE)
  • ATTRIBUTION.md (written by AutoGineer)
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