Skip to content

Tools: Validation

Model validation tools.

validate_model(object_types=None, check_references=True)

Schema-based pre-flight check — run after any model modifications.

Checks field types, numeric ranges, required fields, enum values, singleton constraints (codes E001-E010, W001-W003), and cross-object reference integrity.

IMPORTANT: This is schema validation only. It does not run EnergyPlus and cannot detect runtime faults such as convergence failures, zone connectivity issues, or autosizing problems. A model that passes this check may still fail to simulate.

Preconditions: model loaded (load_model or new_model). Side effects: none — read-only. Next steps: check_model_integrity for domain-level QA, then save_model, then run_simulation for definitive runtime validation.

Source code in src/idfkit_mcp/tools/validation.py 
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
@tool(annotations=_READ_ONLY)
def validate_model(
    object_types: Annotated[list[str] | None, Field(description="Only validate specific types (default: all).")] = None,
    check_references: Annotated[bool, Field(description="Check reference integrity.")] = True,
) -> ValidationResult:
    """Schema-based pre-flight check — run after any model modifications.

    Checks field types, numeric ranges, required fields, enum values, singleton
    constraints (codes E001-E010, W001-W003), and cross-object reference integrity.

    IMPORTANT: This is schema validation only. It does not run EnergyPlus and cannot
    detect runtime faults such as convergence failures, zone connectivity issues, or
    autosizing problems. A model that passes this check may still fail to simulate.

    Preconditions: model loaded (load_model or new_model).
    Side effects: none — read-only.
    Next steps: check_model_integrity for domain-level QA, then save_model,
    then run_simulation for definitive runtime validation.
    """
    from idfkit import validate_document

    state = get_state()
    doc = state.require_model()
    if not list(doc.all_objects):
        logger.warning("validate_model: model has no objects")
    result = validate_document(doc, check_references=check_references, object_types=object_types)
    data = serialize_validation_result(result, version=doc.version)  # type: ignore[arg-type]
    logger.info(
        "Validation complete: %d errors, %d warnings",
        data.get("error_count", 0),
        data.get("warning_count", 0),
    )
    return ValidationResult.model_validate(data)