How do I install the Ontology Reasoner Check skill?

Run npx skillmds@latest add daniel-dona/ontology-reasoner-check in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

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This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Ontology Reasoner Check free to use?

Yes. Installing skills from SkillMD is free. This skill is licensed under MIT.

Who published Ontology Reasoner Check?

daniel-dona (@daniel-dona) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Ontology Reasoner Check by daniel-dona

Name: Ontology Reasoner Check
Rating: 4.666666666666667 (3 reviews)
Author: daniel-dona

Ontology Reasoner Check

Provides a script and instructions to check OWL logical consistency using the HermiT reasoner. Detects unsatisfiable classes, equivalences, and global inconsistency. Use before release to catch contradictory axioms that break reasoning.

daniel-dona Updated Sep 22, 2026

File contents

Ontology Reasoner Consistency Check

Runs the HermiT OWL reasoner on the merged ontology to detect logical contradictions. Reports unsatisfiable classes, non-trivial equivalences, and global ontology inconsistency.

Single script: scripts/reasoner_check.py

Note: The script strips owl:imports before reasoning to prevent owlready2 from trying to download remote ontologies (which would fail). This means the reasoner only checks axioms defined locally — imported vocabulary axioms are not included in the consistency check.

What It Detects

Issue	Example
Unsatisfiable class	`:SquareCircle` defined as `owl:intersectionOf (:Square :Circle)` and `:Square owl:disjointWith :Circle`
Global inconsistency	`owl:Thing ≡ owl:Nothing` — the whole ontology is contradictory
Non-trivial equivalences	`:Person ≡ :Human` inferred because both have identical necessary+sufficient conditions

Setup

cd <your-ontology-repo>
python3 -m venv .venv
source .venv/bin/activate

pip install rdflib owlready2

After finishing: deactivate the venv and remove it:
deactivate && rm -rf .venv
Skip this if the user asks to keep the environment.

Note: owlready2 bundles HermiT as a precompiled wheel. No Java required. The first time it runs, it may compile the native module, which takes a few seconds.

Usage

# Reason over all merged RDF files
python scripts/reasoner_check.py . -o REASONER_REPORT.md

# Reason over a specific file
python scripts/reasoner_check.py . --only-file ontology/main.owl

# JSON output
python scripts/reasoner_check.py . --format json

Standardized Report

All skills support --format report which outputs a common JSON schema:

{
  "skill": "skill-name",
  "summary": {"errors": N, "warnings": N, "info": N},
  "issues": [{"file": ".ttl", "element": ":Class", "message": "...",
              "severity": "error|warning|info", "check": "RULE",
              "suggestion": "fix"}]
}

This format is consumed by ontology-full-audit to produce unified reports.

Output Files

Never write files into the repository without permission. Before generating any report or output file, ask the user where to save it (e.g. -o ../report.md or an absolute path outside the repo). The default output path in script examples is only a suggestion — always confirm with the user first.

Important Rules

Unsatisfiable classes are always bugs. A class that can never have instances indicates contradictory axioms. Check domain/range restrictions, disjointness, and cardinality constraints.
Global inconsistency is critical. If HermiT reports owl:Nothing ≡ owl:Thing, the entire ontology is logically broken. Fix unsatisfiable classes first — they're usually the root cause.
Non-trivial equivalences may be intentional. If :Person ≡ :Human, you may want to merge them or use owl:equivalentClass. The script flags them for review.
Reasoning can be slow on large ontologies. HermiT is optimized for OWL 2 DL. For very large ontologies (> 5000 classes), it may take several minutes.

---name: ontology-reasoner-checkdescription: Provides a script and instructions to check OWL logical consistency using the HermiT reasoner. Detects unsatisfiable classes, equivalences, and global inconsistency. Use before release to catch contradictory axioms that break reasoning.license: MIT---# Ontology Reasoner Consistency CheckRuns the **HermiT** OWL reasoner on the merged ontology to detect logicalcontradictions. Reports unsatisfiable classes, non-trivial equivalences, andglobal ontology inconsistency.**Single script:** `scripts/reasoner_check.py`> **Note:** The script strips `owl:imports` before reasoning to prevent> owlready2 from trying to download remote ontologies (which would fail).> This means the reasoner only checks axioms defined locally — imported> vocabulary axioms are not included in the consistency check.## What It Detects| Issue | Example ||-------|---------|| Unsatisfiable class | `:SquareCircle` defined as `owl:intersectionOf (:Square :Circle)` and `:Square owl:disjointWith :Circle` || Global inconsistency | `owl:Thing ≡ owl:Nothing` — the whole ontology is contradictory || Non-trivial equivalences | `:Person ≡ :Human` inferred because both have identical necessary+sufficient conditions |## Setup```bashcd <your-ontology-repo>python3 -m venv .venvsource .venv/bin/activatepip install rdflib owlready2```> **After finishing:** deactivate the venv and remove it:> ```bash> deactivate && rm -rf .venv> ```> Skip this if the user asks to keep the environment.> **Note:** `owlready2` bundles HermiT as a precompiled wheel. No Java required.> The first time it runs, it may compile the native module, which takes a few seconds.## Usage```bash# Reason over all merged RDF filespython scripts/reasoner_check.py . -o REASONER_REPORT.md# Reason over a specific filepython scripts/reasoner_check.py . --only-file ontology/main.owl# JSON outputpython scripts/reasoner_check.py . --format json```## Standardized ReportAll skills support `--format report` which outputs a common JSON schema:```json{ "skill": "skill-name", "summary": {"errors": N, "warnings": N, "info": N}, "issues": [{"file": ".ttl", "element": ":Class", "message": "...", "severity": "error|warning|info", "check": "RULE", "suggestion": "fix"}]}```This format is consumed by `ontology-full-audit` to produce unified reports.## Output Files**Never write files into the repository without permission.** Before generatingany report or output file, ask the user where to save it (e.g. `-o ../report.md`or an absolute path outside the repo). The default output path in scriptexamples is only a suggestion — always confirm with the user first.## Important Rules1. **Unsatisfiable classes are always bugs.** A class that can never have instances indicates contradictory axioms. Check domain/range restrictions, disjointness, and cardinality constraints.2. **Global inconsistency is critical.** If HermiT reports `owl:Nothing ≡ owl:Thing`, the entire ontology is logically broken. Fix unsatisfiable classes first — they're usually the root cause.3. **Non-trivial equivalences may be intentional.** If `:Person ≡ :Human`, you may want to merge them or use `owl:equivalentClass`. The script flags them for review.4. **Reasoning can be slow on large ontologies.** HermiT is optimized for OWL 2 DL. For very large ontologies (> 5000 classes), it may take several minutes.

Frequently asked questions