Zurück zu Fähigkeiten

ontology-explorer

HeshamFS
Aktualisiert 2 days ago
6 Ansichten
40
3
40
Auf GitHub ansehen
Dokumentewordaidata

Über

Die Ontologie-Explorer-Fähigkeit analysiert und durchsucht Materialwissenschafts-Ontologien (wie CMSO/ASMO), um Klassenhierarchien zu durchsuchen, Eigenschaften zu prüfen und nach Begriffen zu suchen. Sie hilft Entwicklern, die passenden Ontologie-Begriffe für Konzepte wie Kristallstrukturen oder Simulationsmetadaten zu finden. Nutzen Sie sie, um Ontologie-Strukturen zu erkunden, Klassenbeziehungen zu verstehen oder sich in eine unbekannte Materialontologie einzuarbeiten.

Schnellinstallation

Claude Code

Empfohlen
Primär
npx skills add HeshamFS/materials-simulation-skills -a claude-code
Plugin-BefehlAlternativ
/plugin add https://github.com/HeshamFS/materials-simulation-skills
Git CloneAlternativ
git clone https://github.com/HeshamFS/materials-simulation-skills.git ~/.claude/skills/ontology-explorer

Kopieren Sie diesen Befehl und fügen Sie ihn in Claude Code ein, um diese Fähigkeit zu installieren

Dokumentation

Ontology Explorer

Goal

Enable an agent to understand, navigate, and query the structure of materials science ontologies without loading verbose OWL/XML files directly. Provides fast access to class hierarchies, property definitions, and domain-range relationships through pre-processed JSON summaries.

Requirements

  • Python 3.8+
  • No external dependencies (Python standard library only)
  • Internet access required only for owl_parser.py and ontology_summarizer.py when fetching remote OWL files

Inputs to Gather

InputDescriptionExample
Ontology nameRegistered ontology to querycmso
Class nameA specific class to inspectMaterial, UnitCell
Property nameA specific property to look uphasMaterial, hasSpaceGroupNumber
Search termKeyword to search across labelscrystal, lattice
OWL sourcePath or URL to an OWL/XML file (for parsing/summarizing)https://raw.githubusercontent.com/OCDO/cmso/main/cmso.owl

Decision Guidance

What do you need?
├── Understand overall ontology structure
│   └── class_browser.py --ontology cmso --list-roots
├── Inspect a specific class
│   └── class_browser.py --ontology cmso --class <name>
├── Find properties for a class
│   └── property_lookup.py --ontology cmso --class <name>
├── Look up a specific property
│   └── property_lookup.py --ontology cmso --property <name>
├── Search for a concept
│   ├── class_browser.py --ontology cmso --search <term>
│   └── property_lookup.py --ontology cmso --search <term>
├── Parse a new/updated OWL file
│   └── owl_parser.py --source <path-or-url>
└── Generate/refresh a summary JSON
    └── ontology_summarizer.py --source <url> --output <path>

Script Outputs (JSON Fields)

ScriptKey Outputs
scripts/owl_parser.pyresults.metadata, results.classes, results.object_properties, results.data_properties, results.class_hierarchy
scripts/ontology_summarizer.pyresults.output_file, results.statistics
scripts/class_browser.pyresults.class_info, results.subtree, results.properties, results.path_to_root, results.roots, results.search_results
scripts/property_lookup.pyresults.property_info, results.class_properties, results.search_results

Workflow

  1. Identify which ontology the user is working with (default: CMSO).
  2. Use class_browser.py --list-roots to see the top-level concepts.
  3. Drill into specific classes with class_browser.py --class <name> to see hierarchy, children, and applicable properties.
  4. Look up individual properties with property_lookup.py --property <name>.
  5. If the user mentions a concept but not its ontology name, use --search to find matching classes or properties.
  6. For a new or updated ontology, run owl_parser.py to parse the raw OWL, then ontology_summarizer.py to generate a summary JSON.

Conversational Workflow Example

User: I have an FCC copper simulation. What CMSO classes should I use to describe it?

Agent: Let me explore the CMSO ontology to find the relevant classes.

[Runs: class_browser.py --ontology cmso --search "crystal" --json]

For an FCC copper simulation, the relevant CMSO classes are:

- **Computational Sample** → **Atomic Scale Sample**: your simulation is an atomic-scale sample
- **Material** → **Crystalline Material**: copper is crystalline
- **Crystal Structure**: describes the FCC arrangement
- **Unit Cell**: the repeating FCC unit cell (a=b=c=3.615 Å, α=β=γ=90°)
- **Space Group**: FCC copper is space group 225 (Fm-3m)
- **Chemical Element**: Cu

The key relationships:
  AtomicScaleSample → hasMaterial → CrystallineMaterial → hasStructure → CrystalStructure → hasUnitCell → UnitCell

Shall I look up the specific properties for any of these classes?

CLI Examples

# List root classes in CMSO
python3 skills/ontology/ontology-explorer/scripts/class_browser.py \
  --ontology cmso --list-roots --json

# Inspect the Material class hierarchy
python3 skills/ontology/ontology-explorer/scripts/class_browser.py \
  --ontology cmso --class Material --json

# Search for crystal-related classes
python3 skills/ontology/ontology-explorer/scripts/class_browser.py \
  --ontology cmso --search crystal --json

# Find all properties for UnitCell
python3 skills/ontology/ontology-explorer/scripts/property_lookup.py \
  --ontology cmso --class UnitCell --json

# Look up a specific property
python3 skills/ontology/ontology-explorer/scripts/property_lookup.py \
  --ontology cmso --property "has space group" --json

# Parse a remote OWL file
python3 skills/ontology/ontology-explorer/scripts/owl_parser.py \
  --source https://raw.githubusercontent.com/OCDO/cmso/main/cmso.owl --json

# Generate a summary JSON from an OWL file
python3 skills/ontology/ontology-explorer/scripts/ontology_summarizer.py \
  --source https://raw.githubusercontent.com/OCDO/cmso/main/cmso.owl \
  --output summary.json --json

Error Handling

ErrorCauseResolution
Ontology 'X' not in registryOntology name not registeredCheck references/ontology_registry.json for available names
Class 'X' not foundClass label doesn't match any entryUse --search to find similar names, or --list-roots to see available classes
Property 'X' not foundProperty label doesn't matchUse --search to find similar properties
Cannot parse OWL sourceInvalid XML or unreachable URLCheck file path or URL; ensure the file is valid OWL/XML
Summary file not foundSummary JSON hasn't been generatedRun ontology_summarizer.py first

Interpretation Guidance

  • Class hierarchy: root classes are the broadest concepts; leaf classes are the most specific. A class inherits all properties from its ancestors.
  • Object properties: show how classes relate to each other (domain → range). A property with domain UnitCell and range Basis means a unit cell has a basis.
  • Data properties: show what literal values a class carries. A property with domain ChemicalElement and range xsd:string means an element has a string-valued attribute.
  • Union domains: some properties apply to multiple classes (e.g., hasVector applies to both SimulationCell and UnitCell), shown as SimulationCell | UnitCell.
  • Search relevance: 1.0 = label match, 0.5 = description match only.

Security

Input Validation

  • --ontology is validated against registered ontology names in ontology_registry.json (fixed allowlist)
  • --class and --property names are validated against a safe-character pattern to prevent injection
  • --search terms are length-limited and used only for substring matching against pre-processed labels (never interpolated into queries or code)
  • --source for owl_parser.py accepts file paths or URLs; URLs are validated against https:// scheme only

File Access

  • class_browser.py and property_lookup.py read pre-processed JSON summary files from the references/ directory (read-only)
  • owl_parser.py reads a single OWL/XML file from a local path or HTTPS URL; remote fetches have a 30-second timeout
  • ontology_summarizer.py writes a single JSON summary file to the path specified by --output
  • No scripts modify or delete existing files

Tool Restrictions

  • Read: Used to inspect script source, reference files, and ontology summaries
  • Bash: Used to execute the four Python scripts (owl_parser.py, ontology_summarizer.py, class_browser.py, property_lookup.py) with explicit argument lists; URL fetching is contained within the Python scripts with timeout limits

Safety Measures

  • No eval(), exec(), or dynamic code generation
  • All subprocess calls use explicit argument lists (no shell=True)
  • OWL/XML parsing uses Python's xml.etree.ElementTree which does not resolve external entities by default, mitigating XXE attacks
  • Remote URL fetching is limited to HTTPS with a 30-second timeout to prevent abuse
  • Search results are capped in count to prevent output flooding

Limitations

  • Only supports OWL/XML format (not Turtle, JSON-LD, or N-Triples)
  • Does not support OWL reasoning or inference (e.g., does not compute transitive closures)
  • Class hierarchy extraction handles simple rdfs:subClassOf only (not complex OWL restrictions)
  • Descriptions may be missing for classes that lack rdfs:comment, skos:definition, or IAO annotations
  • URL fetching requires internet access and may time out (30-second limit)

References

Version History

DateVersionChanges
2026-02-251.0Initial release with CMSO support

GitHub Repository

HeshamFS/materials-simulation-skills
Pfad: skills/ontology/ontology-explorer
0
agent-skillsagentscli-toolscomputational-sciencellmmaterials-science

Verwandte Skills

release-standards

Dokumente

Diese Fähigkeit bietet Richtlinien für semantische Versionierung (semver) und Formatierungsstandards für Changelogs bei Softwareveröffentlichungen. Nutzen Sie sie bei der Vorbereitung von Releases, um Versionsnummern (Major/Minor/Patch) korrekt zu erhöhen und Changelog-Einträge zu strukturieren. Sie enthält Regeln für Pre-Release-Kennzeichnungen und klare Beispiele für Entwickler.

Skill ansehen

commit-standards

Dokumente

Diese Fähigkeit formatiert Git-Commit-Nachrichten gemäß dem Conventional Commits-Standard. Sie stellt Vorlagen und Typdefinitionen (wie `feat`, `fix`, `refactor`) bereit, um Konsistenz beim Schreiben oder Überprüfen von Commits zu gewährleisten. Verwenden Sie sie während des Commit-Prozesses, um eine klare, strukturierte Commit-Historie zu erstellen.

Skill ansehen

huggingface-tokenizers

Dokumente

Diese Fähigkeit bietet eine leistungsstarke Tokenisierung mit HuggingFace's Rust-basierter Bibliothek und verarbeitet 1 GB Text in unter 20 Sekunden. Sie unterstützt BPE-, WordPiece- und Unigram-Algorithmen und ermöglicht das Training benutzerdefinierter Tokenizer sowie die Verfolgung von Ausrichtungen. Nutzen Sie sie, wenn Sie produktionsreife, schnelle Tokenisierung benötigen oder benutzerdefinierte Tokenizer erstellen möchten, die in das Transformers-Ökosystem integriert sind.

Skill ansehen

nano-pdf

Dokumente

nano-pdf ist ein CLI-Tool, das Entwicklern ermöglicht, PDFs mit natürlichen Sprachbefehlen zu bearbeiten, wie etwa Text zu ändern oder Tippfehler auf bestimmten Seiten zu korrigieren. Es ist ideal für schnelle, programmatische PDF-Modifikationen direkt vom Terminal aus. Überprüfen Sie stets die Ausgabe, da die Seitennummerierung zwischen Versionen variieren kann.

Skill ansehen