Embl Ebi Ols

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.