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GNN Active Inference ontology processing and validation. Use when working with ActInfOntologyAnnotation sections, mapping GNN variables to ontology terms, validating semantic annotations, or exploring Active Inference concept hierarchies.
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
Generalized Notation Notation (GNN) processing pipeline for Active Inference generative models. Use when working with GNN files, running the 25-step pipeline, parsing model specifications, generating simulations, or producing visualizations and reports from GNN model definitions.
GNN command-line interface dispatch and health checks. Use when invoking the `gnn` CLI, validating subcommand availability, or checking command-line access to pipeline modules.
GNN LLM-enhanced analysis and model interpretation. Use when generating natural language descriptions of GNN models, getting AI-assisted model explanations, or performing LLM-powered analysis of Active Inference specifications.
GNN Language Server Protocol integration. Use when starting editor diagnostics, checking hover behavior, or validating LSP support for GNN files.
GNN Model Context Protocol processing and tool registration. Use when registering GNN operations as MCP tools, building MCP server configurations, or integrating GNN capabilities with LLM tool-use workflows.
GNN pipeline orchestration and configuration management. Use when configuring pipeline execution, setting step inclusion/exclusion, managing pipeline state, or customizing the 25-step execution flow.
SOC 職業分類に基づく
| name | gnn-ontology |
| description | GNN Active Inference ontology processing and validation. Use when working with ActInfOntologyAnnotation sections, mapping GNN variables to ontology terms, validating semantic annotations, or exploring Active Inference concept hierarchies. |
Processes Active Inference ontology annotations in GNN models. Maps GNN variables to standardized Active Inference concepts and validates semantic consistency.
# Run ontology processing
python src/10_ontology.py --target-dir input/gnn_files --output-dir output --verbose
# As part of pipeline
python src/main.py --only-steps 10 --verbose
| GNN Annotation | Ontology Concept | Description |
|---|---|---|
LikelihoodMatrix | A matrix | Observation model |
TransitionMatrix | B matrix | State dynamics |
HiddenState | s vector | Latent state beliefs |
Observation | o vector | Sensory observations |
Policy | π | Action sequences |
Preference | C matrix | Preferred observations |
from ontology import (
process_ontology, parse_gnn_ontology_section, process_gnn_ontology,
load_defined_ontology_terms, validate_annotations,
generate_ontology_report_for_file, parse_annotation,
OntologyProcessor, OntologyValidator
)
# Process ontology section from GNN content
parsed = parse_gnn_ontology_section(gnn_content)
# Load defined ontology terms
terms = load_defined_ontology_terms()
# Validate annotations against defined terms
result = validate_annotations(annotations_list, terms)
# Use OntologyProcessor class
processor = OntologyProcessor()
result = processor.process_ontology(data)
# Use OntologyValidator class
validator = OntologyValidator()
is_valid = validator.validate_ontology(content)
process_ontology — main pipeline processing functionparse_gnn_ontology_section — extract ontology from GNN contentvalidate_annotations — validate against known termsOntologyProcessor — class with process_ontology(), validate_terms()OntologyValidator — class with validate_ontology(), check_consistency()output/10_ontology_output/This module registers tools with the GNN MCP server (see mcp.py):
extract_ontology_annotationslist_standard_ontology_termsprocess_ontologyvalidate_ontology_terms