kg-model-review

name: kg-model-review description: Knowledge modeling review of KG-Microbe transforms and merged KG for alignment with METPO, Biolink Model, and KGX specification. Use when auditing transform output quality, validating categories/predicates, checking CURIE prefix registration, or preparing a release.

KG-Microbe Knowledge Modeling Review

Purpose

Perform a systematic review of KG-Microbe transform outputs and/or the merged KG to assess alignment with:

1. KGX specification — required columns, data types, CURIE format
2. Biolink Model — valid category values, valid predicate values, subject/object category constraints per predicate
3. METPO — correct use of METPO predicates and class CURIEs, consistency with METPO ontology semantics
4. Prefix registration — all CURIE prefixes present in kg_microbe/transform_utils/custom_curies.yaml or a standard prefix map

Instructions

When this skill is invoked, run kg_model_review.py with the specified scope and report findings. Always summarize violations by severity (ERROR / WARNING / INFO) and by transform source.

Steps

1. Identify scope from user args (default: all transforms + merged)
2. Run the review script: poetry run python .claude/skills/kg-model-review/kg_model_review.py [args]
3. Report findings grouped by:
   • Transform name
   • Check category (KGX / Biolink / METPO / Prefix)
   • Severity (ERROR / WARNING / INFO)
4. Highlight any systematic issues that suggest a transform-level fix is needed

What Is Checked

KGX Format (nodes.tsv)

• Required columns present: id, category, name
• id is a valid CURIE (prefix:local)
• category is not empty
• No duplicate id values within a single transform

KGX Format (edges.tsv)

• Required columns present: subject, predicate, object, relation
• subject, object are valid CURIEs
• predicate starts with biolink: or is a known METPO predicate mapped to biolink
• relation is a RO or METPO term CURIE

Biolink Model Alignment

Reference data source: bmt (Biolink Model Toolkit) loads the authoritative published biolink-model YAML at runtime. The skill prints the loaded version (e.g. Biolink Model 4.2.2 loaded (154 categories, 469 predicates)) so you can see what reference data you validated against.

On top of bmt, the skill layers a small KGMICROBE_EXTENSION_CATEGORIES / KGMICROBE_EXTENSION_PREDICATES whitelist for:

• KG-Microbe native extensions (e.g. biolink:GrowthMedium)
• Deprecated upstream classes we still emit intentionally (e.g. biolink:ChemicalSubstance as the CHEBI normalization target, biolink:Macromolecule from OAK output)

If bmt is unavailable, the skill falls back to a minimal curated set.

Partial list of recognized categories (full list comes from bmt):

biolink:OrganismTaxon
biolink:ChemicalEntity
biolink:ChemicalSubstance
biolink:SmallMolecule
biolink:MolecularMixture
biolink:ComplexMolecularMixture
biolink:Food
biolink:MacromolecularMachineMixin
biolink:Protein
biolink:Gene
biolink:MolecularActivity
biolink:BiologicalProcess
biolink:CellularComponent
biolink:PhenotypicQuality
biolink:Attribute
biolink:NamedThing
biolink:GrossAnatomicalStructure
biolink:AnatomicalEntity
biolink:EnvironmentalProcess
biolink:PathologicalProcess
biolink:Disease
biolink:GrowthMedium  (KG-Microbe extension)
biolink:Procedure  (used multi-cat as METPO:1001000|biolink:Procedure on kgmicrobe.assay nodes)
biolink:PhenotypicQuality  (PATO terms, surfaced as ENVO has_attribute targets in madin_etal)

Multi-category nodes: a node's category column may carry pipe-delimited categories (e.g. METPO:1001000|biolink:Procedure on the 503 kgmicrobe.assay:* nodes). The reviewer accepts any pipe-split component being valid; this is intentional, not a regression.

Valid predicates (flag anything not in this list):

biolink:has_phenotype
biolink:capable_of
biolink:produces
biolink:consumes
biolink:located_in
biolink:location_of
biolink:has_part
biolink:has_attribute  (used by madin_etal for ENVO substrate → PATO quality attachment)
biolink:subclass_of
biolink:related_to
biolink:associated_with
biolink:enabled_by
biolink:enables
biolink:has_chemical_role
biolink:has_input
biolink:has_output
biolink:occurs_in
biolink:associated_with_resistance_to
biolink:associated_with_sensitivity_to
biolink:related_to_at_instance_level
biolink:contains_process

METPO Alignment

• METPO class CURIEs used as object must exist in data/transformed/ontologies/nodes.tsv (prefix METPO:)
• METPO predicate CURIEs (METPO:20xxxxx) must be in the known predicate map (METPO_TO_BIOLINK_PREDICATE in metatraits.py)
• relation column for METPO-predicated edges must use an RO term, not repeat the biolink predicate

CURIE Prefix Registration

• Extract all unique prefixes from id, subject, object, relation columns
• Cross-reference against:
  • kg_microbe/transform_utils/custom_curies.yaml
  • Standard known prefixes: NCBITaxon, CHEBI, GO, EC, RO, METPO, biolink, FOODON, UBERON, HP, MONDO, ENVO, infores, semapv, KGM
• Flag any prefix not registered

Mapping files (curation TSVs)

Run with --mappings (in addition to a transform/merged scope) or --mappings-only (just the curation TSVs) to validate every curation artifact KG-Microbe ships and consumes. Four file groups are checked:

Per-row checks include: CURIE format on every _id column; predicate_id restricted to the skos: namespace; mapping_justification restricted to semapv:; confidence ∈ {high, medium, low}; deprecated biolink target detection; METPO refs that don't exist in the ontology output; ontology IDs (CHEBI/GO/EC/UBERON/ENVO/HP/MONDO/PATO/PR/CL/FOODON/NCBITaxon/OMP) that don't resolve in data/transformed/ontologies/*_nodes.tsv.

Cross-file checks:

• Same subject_label mapped to conflicting object_id across canonical files

Curation upgrade report. When --mappings (or --mappings-only) is specified, a markdown "Curation upgrade report" is appended to the artifact. It summarises:

1. Top unmapped MediaDive ingredients by occurrence (drives MIM/CultureBotAI curation priority).
2. Cross-file mapping conflicts.
3. Object IDs that don't resolve in the ontologies output.
4. Low-confidence canonical rows.
5. Prefix normalization candidates (e.g. PUBCHEM.COMPOUND → pubchem.compound).
6. CultureBotAI ingredient review queue status counts.

This section is what you hand to the upstream curation repos (CultureBotAI, MIM, CultureBotHT) to drive new mappings.

Usage

Review all transforms

/kg-model-review

Review specific transform

/kg-model-review --transform metatraits

Review merged KG only

/kg-model-review --merged

Review mapping files only (no transforms)

/kg-model-review --mappings-only --format md

Combined: merged KG plus mapping files

/kg-model-review --merged --mappings --format md

Verbose output with example violations

/kg-model-review --transform bacdive --verbose

Output as markdown report

/kg-model-review --format md

Options

• --transform NAME — review specific transform output in data/transformed/NAME/
• --merged — review data/merged/ instead of individual transforms
• --mappings — additionally review curation TSVs (canonical, bespoke, queues, SSSOM) and append a curation upgrade report
• --mappings-only — review ONLY the curation TSVs (skip transforms/merged)
• --format {text,md,json} — output format (default: text)
• --verbose — show up to 5 example violating rows per check
• --max-rows N — limit rows sampled per file (default: 100000; use 0 for all)
• --strict-kgx — additionally run kgx.validator.Validator for authoritative KGX-spec checking (row-level property types, edge id requirement, biolink JSON-LD CURIE context). Off by default because it surfaces deviations we accept by design (e.g. KG-Microbe prefixes not in biolink's JSON-LD context, edges without id column). Use before a release to see the full gap list.

Output Format

=== KG-Microbe Knowledge Modeling Review ===
Date: 2026-04-14
Scope: all transforms

Transform: metatraits
  nodes.tsv  (4,905,811 rows sampled: 100,000)
    [KGX]     ✅ Required columns present
    [KGX]     ✅ No duplicate IDs in sample
    [Biolink] ⚠️  WARNING: 3 unknown categories: biolink:ChemicalSubstance (deprecated → use biolink:SmallMolecule)
    [Prefix]  ✅ All prefixes registered
  edges.tsv  (544,482,259 rows sampled: 100,000)
    [KGX]     ✅ Required columns present
    [Biolink] ✅ All predicates valid
    [METPO]   ⚠️  WARNING: 12 edges use biolink predicate in relation column
    [Prefix]  ✅ All prefixes registered

Transform: bacdive
  ...

---
Summary
  Transforms reviewed: 12
  Total ERRORs:   0
  Total WARNINGs: 47
  Total INFOs:    12

Severity Definitions

Implementation

See kg_model_review.py for the review logic.