AI Model Metadata Schema (models/model_metadata.py)

Provides a provider-neutral structure for defining AI model capabilities, intents, and cost tiers. Use this to standardize model selection logic across different LLM providers.

# Source: https://github.com/omnigent-ai/omnigent | License: Apache-2.0 | Copyright You must retain, in the Source form of any Derivative Works
# Provided via justclaw.it.com; keep this notice with the code.
"""Provider-neutral metadata used for model selection."""

from __future__ import annotations

from dataclasses import dataclass
from enum import Enum


def concrete_reported_model(value: object) -> str | None:
    """Keep model reports verbatim, excluding Claude Code's local-error marker."""
    if not isinstance(value, str):
        return None
    model = value.strip()
    return model if model and model != "<synthetic>" else None


class ModelIntent(str, Enum):
    """Stable purpose requested by a model-selection caller."""

    DEFAULT = "default"
    FAST = "fast"
    BALANCED = 

... (truncated -- full source via MCP)