name: ontology-validator description: > Validate material sample annotations against ontology constraints — check that class names and property names exist in the ontology, verify domain and range consistency for object property relationships, assess annotation completeness (required, recommended, and optional properties), and flag unknown or misspelled terms. Use when verifying that CMSO or other ontology annotations are correct before publishing, checking whether all required properties are present for a class like Crystal Structure or Unit Cell, auditing relationship triples between instances, or catching annotation errors early in a FAIR data workflow, even if the user only says "is my annotation correct" or "what am I missing." allowed-tools: Read, Bash metadata: author: HeshamFS version: "1.1.0" security_tier: high security_reviewed: true tested_with: - claude-code - gemini-cli - vs-code-copilot eval_cases: 2 last_reviewed: "2026-03-26"

Ontology Validator

Goal

Validate that material sample annotations comply with ontology constraints: correct class names, valid properties, consistent domain/range relationships, and required fields present.

Requirements

• Python 3.8+
• No external dependencies (Python standard library only)
• Requires ontology-explorer's cmso_summary.json and ontology_registry.json

Inputs to Gather

Decision Guidance

What do you need to validate?
├── An annotation (classes and properties are correct)
│   └── schema_checker.py --ontology cmso --annotation '<json>'
├── Completeness of a class annotation
│   └── completeness_checker.py --ontology cmso --class <name> --provided <props>
└── Object property relationships
    └── relationship_checker.py --ontology cmso --relationships '<json>'

Script Outputs (JSON Fields)

Workflow

1. After mapping a sample with ontology-mapper, pass the annotations to schema_checker.py to verify correctness.
2. For a specific class, use completeness_checker.py to see what required/recommended properties are missing.
3. When building relationships between instances, use relationship_checker.py to ensure domain/range consistency.

Conversational Workflow Example

User: I annotated my sample as CrystalStructure with properties hasUnitCell and hasBasis.
      Is this correct and complete?

Agent: Let me validate your annotation and check completeness.

[Runs: completeness_checker.py --ontology cmso --class "Crystal Structure" --provided "has unit cell,has basis" --json]

Your annotation is partially complete:
- has unit cell: provided (required)
- has basis: not a direct property of Crystal Structure (it belongs to Unit Cell)
- **Missing required**: has space group

The "has basis" property belongs to the Unit Cell class, not Crystal Structure.
You should add "has space group" to Crystal Structure and move "has basis"
to the Unit Cell annotation.

CLI Examples

# Validate an annotation
python3 skills/ontology/ontology-validator/scripts/schema_checker.py \
  --ontology cmso \
  --annotation '{"class":"Unit Cell","properties":{"has Bravais lattice":"cF"}}' \
  --json

# Check completeness
python3 skills/ontology/ontology-validator/scripts/completeness_checker.py \
  --ontology cmso \
  --class "Crystal Structure" \
  --provided "has unit cell,has space group" \
  --json

# Validate relationships
python3 skills/ontology/ontology-validator/scripts/relationship_checker.py \
  --ontology cmso \
  --relationships '[{"subject_class":"Computational Sample","property":"has material","object_class":"Material"}]' \
  --json

Error Handling

Interpretation Guidance

• Errors indicate definite problems (unknown class/property, range mismatch)
• Warnings indicate potential issues (domain mismatch — may be intentional for subclasses)
• Completeness score: 0.0-1.0 ratio of provided vs. total tracked properties
• required_missing: must fix for valid annotation
• recommended_missing: should fix for quality
• unrecognized: may indicate typos or properties from a different ontology

Security

Input Validation

• --ontology is validated against registered ontology names in ontology_registry.json (fixed allowlist)
• --annotation JSON is parsed with json.loads() and validated as a dict with required class and properties keys
• --class names are validated against known classes in the ontology summary; unknown classes produce clear errors
• --provided property names are validated as comma-separated strings and matched against known properties
• --relationships JSON is parsed and validated as a non-empty list of dicts, each requiring subject_class, property, and object_class keys

File Access

• Scripts read pre-processed JSON files from the references/ directory: ontology_registry.json, cmso_summary.json, cmso_constraints.json (all read-only)
• No scripts write to the filesystem; all output goes to stdout
• No network access is required

Tool Restrictions

• Read: Used to inspect script source, reference files, and ontology constraint data
• Bash: Used to execute the three Python validation scripts (schema_checker.py, completeness_checker.py, relationship_checker.py) with explicit argument lists

Safety Measures

• No eval(), exec(), or dynamic code generation
• All subprocess calls use explicit argument lists (no shell=True)
• JSON input parsing uses json.loads() only (no pickle, no YAML with unsafe loaders)
• Validation logic operates on pre-loaded in-memory data structures; no dynamic file discovery or traversal

Limitations

• Constraints file is manually curated, not derived from OWL axioms
• Does not validate data types (e.g., whether a value is actually a float vs string)
• Does not validate cardinality (e.g., exactly one space group per structure)
• Subclass checking uses simple parent traversal, not full OWL reasoning

References

• Validation Rules — what is validated and why
• CMSO Constraints — required/recommended properties per class
• CMSO Guide — CMSO ontology overview

Version History