### Embl Ebi Ols
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name: "embl-ebi-ols"
description: "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 fo..."
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Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionembl-ebi-olsExecute the skills CLI command in your project's root directory to begin installation:
Fetches embl-ebi-ols from google-deepmind/science-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate embl-ebi-ols. Access via /embl-ebi-ols in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
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| name | embl-ebi-ols |
| description | > 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. |
uv: Read the uv skill and follow its Setup instructions to ensure
uv is installed and on PATH.[!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.
Use this skill whenever a user query matches one of these patterns:
get_term.py --obo_id <ID> --summaryget_term.py --obo_id <ID> --relations childrenget_term.py --obo_id <ID> --relations parentsget_term.py --obo_id <ID> --relations ancestorsget_term.py --ontology <id> --rootsget_term.py --obo_id <ID> --relations hierarchicalParentsget_term.py --obo_id <ID> --relations hierarchicalChildrenget_term.py --obo_id <ID> --relations parents,hierarchicalParentssearch_ols.py --query "..." --ontology <id>search_ols.py --query "..." --ontology go --exactsearch_ols.py --query "..." --ontology <id> --definingsearch_ols.py --query "..." --rows N --start <offset>suggest_ols.py --query "..."get_ontology.py --id <id>get_stats.pyMulti-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:
- Search in the single most appropriate ontology:
search_ols.py --query "myocardial infarction" --ontology doid --exact --rows 1 --output /tmp/step1.json- Get relations using the OBO ID from step 1:
get_term.py --obo_id DOID:5844 --relations parents --output /tmp/step2.jsonOntology selection rule: ALWAYS use
doidfor common human diseases (e.g., diabetes, cancer),hpfor phenotypes,gofor gene functions,chebifor chemicals,uberonfor anatomy,clfor cell types. UsemondoONLY when cross-species context is explicitly mentioned or needed.
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:
--outputis 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.
parents, children, ancestors,
descendantshierarchicalParents, hierarchicalChildren, hierarchicalAncestors,
hierarchicalDescendantsgraph — full graph JSON for a termNote: 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).suggest_ols.py for autocomplete when you have a partial term name.search_ols.py. Use --defining to prioritize
authoritative definitions. Use --exact for entity resolution.get_term.py with the OBO ID or IRI. Use
--summary for a concise view.get_term.py --relations parents,children for is-a only, or --relations hierarchicalParents,hierarchicalChildren for "part of" etc.get_term.py --ontology go --roots.get_property.py or get_individual.py.get_ontology.py.get_stats.py.Prerequisites
Time Estimate
15-45 minutes depending on use case complexity
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
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embl-ebi-ols reduced setup friction for our internal harness; good balance of opinion and flexibility.
Registry listing for embl-ebi-ols matched our evaluation — installs cleanly and behaves as described in the markdown.
embl-ebi-ols fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Solid pick for teams standardizing on skills: embl-ebi-ols is focused, and the summary matches what you get after install.
We added embl-ebi-ols from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
I recommend embl-ebi-ols for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
embl-ebi-ols reduced setup friction for our internal harness; good balance of opinion and flexibility.
Keeps context tight: embl-ebi-ols is the kind of skill you can hand to a new teammate without a long onboarding doc.
We added embl-ebi-ols from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
embl-ebi-ols fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
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