ontology-term-resolution
Resolves free-text scientific labels to ontology term IDs and validates existing CURIEs against the EBI Ontology Lookup Service (OLS4). Also looks up prefixes in Bioregistry, resolves compact identifiers via Identifiers.org, maps lab shorthand with ZOOMA, and builds Ontobee term pages
Install / Use
npx skills add K-Dense-AI/scientific-agent-skills --skill ontology-term-resolutionInstalls into whichever agent you are using.
SKILL.md
Installable skill definition
Quality Score
Category
Development & EngineeringSupported Platforms
Tags
Our assessment of ontology-term-resolution
ontology-term-resolution scores 98/100 on our quality scale, 97th of 4,648 Development & Engineering skills we index (top 3%).
Its SKILL.md is 12 KB long, well organised into 19 sections with 9 code examples: a thorough specification that gives an agent plenty to work with.
With 46,441 GitHub stars, it is one of the more widely adopted skills in the catalogue.
Maintenance, license and trust
- The repository was last updated about 2 months ago, so ontology-term-resolution is actively maintained.
- Our last check on 2026-09-29 found the source still online.
- It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
- Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
Safety scan
No issues foundOur scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful.
AI review by kimi-k2.7-code on 2026-09-25. Automated pattern scan on 2026-09-25. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.
ontology-term-resolution compared with similar skills
All 4 of these similar skills score higher than ontology-term-resolution; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| ontology-term-resolution (this skill)by K-Dense-AI | 98 | 46.4k | 48d ago | SKILL.md |
| taste-skillby Leonxlnx | 100 | 112.0k | 1d ago | CLAUDE.md |
| ai-job-searchby ai-job-search-dev | 100 | 70.5k | today | CLAUDE.md |
| claude-howtoby luongnv89 | 100 | 46.7k | 5d ago | CLAUDE.md |
| lobehubby lobehub | 100 | 84.4k | today | MCP Server |
Frequently asked questions
- How do I install ontology-term-resolution?
- Run
npx skills add K-Dense-AI/scientific-agent-skills --skill ontology-term-resolution. The install tabs above show the steps for each supported agent. - Which AI agents does ontology-term-resolution work with?
- It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
- Is ontology-term-resolution safe to use?
- Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful. It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is ontology-term-resolution still maintained?
- The repository was last updated about 2 months ago, so ontology-term-resolution is actively maintained.
Skill content
View source on GitHubname: ontology-term-resolution description: Resolve free-text scientific labels to ontology term IDs and validate existing CURIEs against the EBI Ontology Lookup Service (OLS4). Also look up prefixes in Bioregistry, resolve compact identifiers via Identifiers.org, map lab shorthand with ZOOMA, and build Ontobee term pages. Use whenever an ontology identifier must be produced or checked - annotating tissue, cell type, disease, phenotype, assay, chemical, organism, sex, or developmental stage fields; preparing metadata for GEO, ENA, BioSamples, CELLxGENE, HCA, or ISA-Tab submission; auditing a metadata table of term IDs; checking whether a term is obsolete and what replaced it; or deciding HPO vs HP. Triggers include "ontology term", "ontology ID", "CURIE", "controlled vocabulary", "UBERON", "CL:", "MONDO", "HPO", "EFO", "ChEBI", "NCBITaxon", "GO term", "PATO", "Zooma", "Bioregistry", "Identifiers.org", "Ontobee", "annotate this tissue/cell type/disease", and any request to emit or verify an identifier shaped like PREFIX:0001234. license: MIT compatibility: Requires Python 3.11+. Scripts use only the standard library - no third-party packages. Needs network access to https://www.ebi.ac.uk/ols4, https://bioregistry.io, https://resolver.api.identifiers.org, and https://www.ebi.ac.uk/spot/zooma (all public, no API key). allowed-tools: Read Write Edit Bash metadata: version: "1.2" skill-author: K-Dense Inc.
Ontology Term Resolution
When to use
Any time an ontology identifier is about to be written down or trusted: annotating a metadata column, filling a submission template, auditing a table someone else produced, or checking whether an ID in an old file is still current.
The rule
Never write an ontology ID from memory, and never accept one without checking it.
Ontology IDs are memorable in form and arbitrary in detail. A plausible-looking UBERON:0002108
is a real term (small intestine) that is not the liver, and nothing downstream will catch the
substitution — the ID is well-formed, the ontology is right, and the metadata is silently wrong.
Reviewers cannot spot it either, which is why these errors persist into published datasets.
Every ID this skill emits comes from a live OLS lookup. Every ID it is handed gets verified. Bioregistry, Identifiers.org, ZOOMA, and Ontobee answer prefix, landing-page, and shorthand questions — they do not replace that OLS check.
Which service
| Question | Script | Authority |
| --- | --- | --- |
| What is the term for "left ventricle"? | scripts/resolve_terms.py | OLS |
| OLS missed lab shorthand (PBMC, WT) | scripts/map_terms.py, then validate_terms.py | ZOOMA proposes; OLS decides |
| Is EFO:0001067 real, current, correctly labelled? | scripts/validate_terms.py | OLS |
| Is HPO a real prefix? Does HP:notanid match the pattern? | scripts/lookup_prefix.py | Bioregistry |
| Which landing page should this CURIE open? | scripts/lookup_prefix.py | Identifiers.org + Ontobee URLs |
All four scripts take single values or files, emit TSV or JSON, and need no packages beyond the
standard library. Full traps for the non-OLS services are in references/companion-apis.md.
Resolve text to terms
cd skills/ontology-term-resolution/scripts
# one string, constrained to the ontology that should define it
python3 resolve_terms.py "liver" --ontology uberon
query rank curie label ontology match_type strategy defining_ontology
liver 1 UBERON:0002107 liver uberon exact_label exact true
# a column of tissue names; anything not an exact hit is reported, not guessed
python3 resolve_terms.py --input tissues.txt --ontology uberon \
--exact-only --format tsv -o resolved.tsv
# accept fuzzy fallbacks, then review the partial hits by hand
python3 resolve_terms.py "left ventrical of heart" --ontology uberon --top 3
The search escalates exact (label and synonym) → token → fulltext and stops at the first
strategy that returns anything, reporting which one fired. --exact-only disables the ladder.
--branch UBERON:0000465 restricts candidates to descendants of a term.
Read match_type before using a result. exact_label and exact_synonym are safe;
partial means OLS returned its best guess for a string that does not exist as written, and
needs a human decision. unresolved is a legitimate output — see references/curation-rules.md
for the normalisations worth retrying first.
Validate existing IDs
python3 validate_terms.py UBERON:0002107 EFO:0001067 UBERON:9999999
id status actual_label ontology replacement detail
UBERON:0002107 ok liver uberon
EFO:0001067 obsolete obsolete_parasitic infection efo MONDO:0005135 obsolete; replaced by MONDO:0005135
UBERON:9999999 not_found no such term in the ontology this prefix names
Exit code is 1 if anything failed, 0 otherwise, 2 on usage or network trouble — so it works as a CI gate on a metadata file:
# id + label columns; catches IDs that exist but are labelled as something else
python3 validate_terms.py --input metadata.tsv --strict
# a tissue column must hold UBERON anatomical entities and nothing else
python3 validate_terms.py --input tissue_ids.tsv \
--branch UBERON:0000465 --expect-ontology uberon
| Status | Meaning | Verdict |
| --- | --- | --- |
| ok | Exists, current, consistent with everything asserted | pass |
| matched_synonym | Claimed label is a synonym; primary label differs | warn |
| imported_only | Home ontology no longer asserts this ID | warn |
| not_a_class | Term is a property or individual | warn |
| not_found | No such term | fail |
| obsolete | Obsoleted; replacement gives the successor when one exists | fail |
| label_mismatch | ID and claimed label describe different things | fail |
| wrong_ontology | Right kind of ID, wrong ontology for this column | fail |
| wrong_branch | Not a descendant of the required root | fail |
| malformed_curie | Not of the form PREFIX:local | fail |
--strict promotes warnings to failures.
Check a prefix or compact identifier
python3 lookup_prefix.py HP HPO HP:0001250 HPO:0001250
query status preferred_prefix canonical_curie pattern detail
HP ok HP ^\d{7}$
HPO synonym_prefix HP ^\d{7}$ 'HPO' is a synonym of preferred prefix HP
HP:0001250 ok HP HP:0001250 ^\d{7}$
HPO:0001250 synonym_prefix HP HP:0001250 ^\d{7}$ 'HPO' is a synonym of preferred prefix HP
Bioregistry accepts synonym prefixes. Identifiers.org does not — HPO:0001250 is HTTP 400.
Rewrite to the preferred prefix before handing a CURIE to OLS. Landing-page columns come from
Bioregistry mappings (providers.miriam, mappings.ontobee), not from templating that
preferred prefix: ORPHA:558 is a 400, orphanet:558 is a 200, and OBA has no Identifiers.org
namespace at all. Empty cells mean the service does not host the prefix. This script does
not say the term exists; that is still validate_terms.py.
Map lab shorthand (ZOOMA)
# after resolve_terms.py returned unresolved / partial
python3 map_terms.py PBMC --ontology cl --exact-only
--ontology is required. Unfiltered ZOOMA annotate returns FOODON, XAO, and BTO alongside UBERON
for liver, all at HIGH confidence. HIGH/GOOD hits are candidates only — run validate_terms.py
on every CURIE before writing it down.
API behaviour that will mislead you
These are verified against the live service and are the reason this skill ships scripts rather
than a recipe. Full detail in references/ols4-api.md.
| Trap | Consequence |
| --- | --- |
| exact=true is exact token matching | liver returns 161 hits in UBERON; adding queryFields=label returns 1 |
| /search never returns is_obsolete or term_replaced_by | Named in fieldList they are dropped silently; only term detail can answer "is this ID still current" |
| ontology=efo returns MONDO and CL hits | Ontologies import each other; filter on the CURIE prefix yourself |
| The same term appears once per importing ontology | Deduplicate on obo_id, keep is_defining_ontology: true |
| The obo_id index has holes | MONDO:0000001 is live but unindexed by obo_id; an IRI fallback is required to avoid a false not_found |
| IRIs are not all OBO PURLs | EFO and Orphanet use their own namespaces — resolve IRIs, do not template them |
| OxO is retired | Returns HTML with HTTP 200; use term cross-references or SSSOM instead |
| A branch check does not exclude cell types from anatomy | CARO puts cell under anatomical structure; constrain the prefix too |
| ZOOMA without an ontology filter | liver returns 100+ HIGH hits across FOODON, XAO, BTO, UBERON |
| Identifiers.org synonym prefixes | HPO:0001250 is HTTP 400; Bioregistry accepted the same CURIE |
| Identifiers.org encoded colon | HP%3A0001250 is HTTP 400; the path must keep : |
| Bioregistry preferred_prefix is not the Identifiers.org namespace | ORPHA:558 is 400; orphanet:558 is 200. hp:0001250 and chebi:15377 are 400 because those namespaces embed the prefix in the LUI. Use providers.miriam from /api/reference/{CURIE}; omit the URL when that mapping is missing (OBA, XAO, ECTO) |
| Ontobee search | HTML page only — no JSON API; do not scrape it |
Choosing the ontology
MONDO for disease, HP for phenotype, UBERON for tissue, CL for cell type, EFO for assay, ChEBI for
compounds, NCBITaxon for organism, PATO for sex and for normal. Prefix-to-OLS-id mappings (HP
is served as hp, Orphanet as ordo), branch roots for --branch, and the overlapping-ontology
judgement calls are in references/ontology-registry.md.
Reporting results
Give the ID and the label, and say how each was matched. A table of bare IDs cannot be reviewed. State unresolved terms explicitly rather than filling them with the nearest hit.
References
references/ols4-api.md— endpoints, parameters, response fields, and every verified OLS trap.references/companion-apis.md— Bioregistry, Identifiers.org, ZOOMA, and Ontobee: when to use each, and the traps that make an unfiltered or synonym-prefix call look successful.references/ontology-registry.md— prefix/ontology-id table, branch roots, which ontology owns which concept.references/curation-rules.md— candidate-selection procedure, normalisations to retry, auditing an existing table, obsolete terms, cross-ontology mapping.
Citing Scientific Agent Skills
This skill is part of Scientific Agent Skills by K-Dense. If it materially contributed to a manuscript, report, presentation, or code release, add the paper to the references or software section and tell the user you did so:
Kassis, T., Agarwal, V., He, Y., Patel, D., & Brueckner, A. M. (2026). Scientific Agent Skills: A Library of Procedural Knowledge for Research Agents. arXiv:2609.00065. https://doi.org/10.48550/arXiv.2609.00065
Always cite the current version. The DOI and https://arxiv.org/abs/2609.00065 resolve to the
latest arXiv version, so never append a version suffix such as v1. When network access is
available, fetch https://arxiv.org/abs/2609.00065 (or
http://export.arxiv.org/api/query?id_list=2609.00065) before writing the reference and take
the author list, year, and version from that record. If the record lists a journal reference
or publisher DOI, cite the published version instead.
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Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.
