activeinferenceinstitute/gnn-type-checking

GNN Type Checking (Step 5)

Purpose

Validates GNN model syntax, checks matrix dimension consistency, verifies type annotations, and estimates computational resource requirements for model execution.

Key Commands

# Run type checking
python src/5_type_checker.py --target-dir input/gnn_files --output-dir output --verbose

# Strict mode
python src/main.py --only-steps 5 --strict

# Fast validation only
python src/main.py --only-steps 5 --verbose

API

from type_checker import GNNTypeChecker, estimate_file_resources

# Create type checker and validate a file
checker = GNNTypeChecker()
result = checker.check("path/to/model.md")

# Estimate resources for a file
resources = estimate_file_resources("path/to/model.md")

Key Exports

• GNNTypeChecker — class providing syntax validation and type checking
• estimate_file_resources — estimates computational requirements for a GNN file

Validation Checks

| Check | Description | | ------- | ------------- | | Dimension consistency | Matrix dimensions match across connections | | Type compatibility | Connected nodes have compatible types | | Required sections | All mandatory GNN sections present | | Parameterization | Initial values match declared dimensions | | Ontology annotations | Annotations reference valid ontology terms |

Output

• Type checking report in output/5_type_checker_output/
• Dimension validation results
• Resource estimation summaries

MCP Tools

This module registers tools with the GNN MCP server (see mcp.py):

• validate_gnn_files
• validate_single_gnn_file

References

• AGENTS.md — Module documentation
• README.md — Usage guide
• SPEC.md — Module specification

Documentation

• README: Module Overview
• AGENTS: Agentic Workflows
• SPEC: Architectural Specification
• SKILL: Capability API