Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add HeshamFS/materials-simulation-skills --skill ontology-validatorgit clone --depth 1 https://github.com/HeshamFS/materials-simulation-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/heshamfs/materials-simulation-skills/ontology-validator)<a href="https://agentmods.dev/skills/heshamfs/materials-simulation-skills/ontology-validator"><img src="https://agentmods.dev/badge/skills/heshamfs/materials-simulation-skills/ontology-validator/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/heshamfs/materials-simulation-skills/ontology-validator"><img src="https://agentmods.dev/badge/skills/heshamfs/materials-simulation-skills/ontology-validator.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00122 | $0.02993 |
| Opus 5 | $0.00061 | $0.01496 |
| Sonnet 5 | $0.00024 | $0.00599 |
| Haiku 4.5 | $0.00012 | $0.00299 |
Grade A, and why
ontology-validator scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 217 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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 3.10+
- No external dependencies (Python standard library only)
- Requires ontology-explorer's
cmso_summary.jsonandontology_registry.json
Inputs to Gather
| Input | Description | Example |
|---|---|---|
| Annotation | JSON dict or list of annotation dicts | {"class":"UnitCell","properties":{"has Bravais lattice":"cF"}} |
| Class name | Class to check completeness for | Crystal Structure |
| Provided properties | Comma-separated property names | "has unit cell,has space group" |
| Relationships | JSON array of subject-property-object triples | [{"subject_class":"Material","property":"has structure","object_class":"Crystal Structure"}] |
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)
| Script | Key Outputs |
|---|---|
scripts/schema_checker.py |
results.valid, results.errors (each unknown_class/unknown_property error carries a suggestions array of nearest matches), results.warnings, results.class_valid, results.properties_valid |
scripts/completeness_checker.py |
results.completeness_score, results.required_missing, results.recommended_missing, results.optional_missing, results.unrecognized |
scripts/relationship_checker.py |
results.valid, results.results, results.errors |
Workflow
- After mapping a sample with ontology-mapper, pass the annotations to
schema_checker.pyto verify correctness. - For a specific class, use
completeness_checker.pyto see what required/recommended properties are missing. - When building relationships between instances, use
relationship_checker.pyto ensure domain/range consistency.
What ships with it
8 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- CHANGELOG.md 4.0 KB
- evals/evals.json 9.8 KB
- references/asmo_constraints.json 1.1 KB
- references/cmso_constraints.json 1.0 KB
- references/validation_rules.md 2.0 KB
- scripts/completeness_checker.py 11 KB runs code
- scripts/relationship_checker.py 7.7 KB runs code
- scripts/schema_checker.py 14 KB runs code
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 10d ago First seen · 217 lines · 122 tokens per session scan A 2c117c9cf15c
ontology-validator is a skill published in the GitHub repository HeshamFS/materials-simulation-skills (66 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 122 tokens to every session and 2,993 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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