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Embl Ebi Ols

  • 1.3k installs
  • 2.6k repo stars
  • Updated July 7, 2026
  • google-deepmind/science-skills

EMBL-EBI OLS is a Claude Code skill that gives coding agents reliable access to biomedical and life-science ontologies via the EMBL-EBI OLS4 API for developers who need standardized ontology terms in pipelines and apps.

About

EMBL-EBI OLS is a science-skills reference from google-deepmind/science-skills that documents the OLS4 REST API at https://www.ebi.ac.uk/ols4/api for ontology search, autocomplete, and term retrieval. The skill catalogs key endpoints including /search, /suggest, /select, /ontologies, and /ontologies/{id}/terms with double-encoded IRI lookup patterns. Developers reach for EMBL-EBI OLS when bioinformatics scripts, annotation pipelines, or agent tools must resolve GO, EFO, or other controlled vocabularies without hand-maintaining term lists. The skill focuses on correct API usage for full-text search, ontology browsing, and class detail retrieval in life-science coding workflows.

  • Full-text search across all public ontologies
  • Autocomplete suggestions via the suggest endpoint
  • Browse terms, parents, children, ancestors and descendants
  • Support for both strict is-a and hierarchical transitive relations
  • Returns graph JSON for any term

Embl Ebi Ols by the numbers

  • 1,262 all-time installs (skills.sh)
  • +168 installs in the week ending Aug 5, 2026 (Skillselion tracking)
  • Ranked #908 of 16,546 AI & Agent Building skills by installs in the Skillselion catalog
  • Security screen: LOW risk (skills.sh audit)
  • Data as of Aug 5, 2026 (Skillselion catalog sync)
npx skills add https://github.com/google-deepmind/science-skills --skill embl-ebi-ols

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Last updatedJuly 7, 2026
Repositorygoogle-deepmind/science-skills

How do you query EMBL-EBI ontology terms via API?

Give their coding agent reliable access to biomedical and life-science ontologies via the EMBL-EBI OLS API.

Who is it for?

Bioinformatics and life-science developers integrating standardized ontology lookup into agents, APIs, or annotation pipelines.

Skip if: Developers outside biomedical domains who do not need controlled vocabulary or ontology term resolution.

When should I use this skill?

A developer asks to search EMBL-EBI ontologies, autocomplete biomedical terms, or fetch OLS4 class details by IRI.

What you get

OLS4 API call patterns, ontology term mappings, and search/suggest integration code.

  • OLS4 API integration patterns
  • ontology term lookup code

Files

SKILL.mdMarkdownGitHub ↗

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 LICENSE_NOTIFICATION.txt does not already exist in this skill 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

  • API Reference: See

references/api_reference.md for common ontology IDs, OBO ID format, and key API endpoints.

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.

Related skills

FAQ

What API base URL does EMBL-EBI OLS use?

EMBL-EBI OLS uses the OLS4 REST API at https://www.ebi.ac.uk/ols4/api, exposing /search, /suggest, /select, /ontologies, and term endpoints for biomedical ontology access.

How does EMBL-EBI OLS help coding agents?

EMBL-EBI OLS gives coding agents reliable patterns to resolve life-science ontology terms via OLS4 search, suggest, and term-by-IRI endpoints instead of hardcoding stale vocabulary lists.

Is Embl Ebi Ols safe to install?

skills.sh reports 3 of 3 security scanners passed. Review the Security Audits panel on this page before installing in production.

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