diff --git a/docs/adding_providers.md b/docs/adding_providers.md
index 0a62c8c..21abd53 100644
--- a/docs/adding_providers.md
+++ b/docs/adding_providers.md
@@ -7,7 +7,7 @@ This guide explains how to add support for a new AI model provider to the Zen MC
 Each provider:
 - Inherits from `ModelProvider` (base class) or `OpenAICompatibleProvider` (for OpenAI-compatible APIs)
 - Defines supported models using `ModelCapabilities` objects
-- Implements a few core abstract methods
+- Implements the minimal abstract hooks (`get_provider_type()` and `generate_content()`)
 - Gets registered automatically via environment variables
 
 ## Choose Your Implementation Path
@@ -15,11 +15,11 @@ Each provider:
 **Option A: Full Provider (`ModelProvider`)**
 - For APIs with unique features or custom authentication
 - Complete control over API calls and response handling
-- Required methods: `generate_content()`, `get_capabilities()`, `validate_model_name()`, `get_provider_type()` (override `count_tokens()` only when you have a provider-accurate tokenizer)
+- Implement `generate_content()` and `get_provider_type()`; override `get_all_model_capabilities()` to expose your catalogue and extend `_lookup_capabilities()` / `_ensure_model_allowed()` only when you need registry lookups or custom restriction rules (override `count_tokens()` only when you have a provider-accurate tokenizer)
 
 **Option B: OpenAI-Compatible (`OpenAICompatibleProvider`)**
 - For APIs that follow OpenAI's chat completion format
-- Only need to define: model configurations, capabilities, and validation
+- Supply `MODEL_CAPABILITIES`, override `get_provider_type()`, and optionally adjust configuration (the base class handles alias resolution, validation, and request wiring)
 - Inherits all API handling automatically
 
 ⚠️ **Important**: If using aliases (like `"gpt"` → `"gpt-4"`), override `generate_content()` to resolve them before API calls.
@@ -62,8 +62,7 @@ logger = logging.getLogger(__name__)
 
 class ExampleModelProvider(ModelProvider):
     """Example model provider implementation."""
-    
-    # Define models using ModelCapabilities objects (like Gemini provider)
+
     MODEL_CAPABILITIES = {
         "example-large": ModelCapabilities(
             provider=ProviderType.EXAMPLE,
@@ -87,51 +86,47 @@ class ExampleModelProvider(ModelProvider):
             aliases=["small", "fast"],
         ),
     }
-    
+
     def __init__(self, api_key: str, **kwargs):
         super().__init__(api_key, **kwargs)
         # Initialize your API client here
-    
-    def get_capabilities(self, model_name: str) -> ModelCapabilities:
+
+    def get_all_model_capabilities(self) -> dict[str, ModelCapabilities]:
+        return dict(self.MODEL_CAPABILITIES)
+
+    def get_provider_type(self) -> ProviderType:
+        return ProviderType.EXAMPLE
+
+    def generate_content(
+        self,
+        prompt: str,
+        model_name: str,
+        system_prompt: Optional[str] = None,
+        temperature: float = 0.7,
+        max_output_tokens: Optional[int] = None,
+        **kwargs,
+    ) -> ModelResponse:
         resolved_name = self._resolve_model_name(model_name)
-        
-        if resolved_name not in self.MODEL_CAPABILITIES:
-            raise ValueError(f"Unsupported model: {model_name}")
-        
-        # Apply restrictions if needed
-        from utils.model_restrictions import get_restriction_service
-        restriction_service = get_restriction_service()
-        if not restriction_service.is_allowed(ProviderType.EXAMPLE, resolved_name, model_name):
-            raise ValueError(f"Model '{model_name}' is not allowed.")
-        
-        return self.MODEL_CAPABILITIES[resolved_name]
-    
-    def generate_content(self, prompt: str, model_name: str, system_prompt: Optional[str] = None, 
-                        temperature: float = 0.7, max_output_tokens: Optional[int] = None, **kwargs) -> ModelResponse:
-        resolved_name = self._resolve_model_name(model_name)
-        
+
         # Your API call logic here
         # response = your_api_client.generate(...)
-        
+
         return ModelResponse(
-            content="Generated response",  # From your API
+            content="Generated response",
             usage={"input_tokens": 100, "output_tokens": 50, "total_tokens": 150},
             model_name=resolved_name,
             friendly_name="Example",
             provider=ProviderType.EXAMPLE,
         )
-    def get_provider_type(self) -> ProviderType:
-        return ProviderType.EXAMPLE
-    
-    def validate_model_name(self, model_name: str) -> bool:
-        resolved_name = self._resolve_model_name(model_name)
-        return resolved_name in self.MODEL_CAPABILITIES
 ```
 
-`ModelProvider.count_tokens()` uses a simple 4-characters-per-token estimate so
-providers work out of the box. Override the method only when you can call into
-the provider's real tokenizer (for example, the OpenAI-compatible base class
-already integrates `tiktoken`).
+`ModelProvider.get_capabilities()` automatically resolves aliases, enforces the
+shared restriction service, and returns the correct `ModelCapabilities`
+instance. Override `_lookup_capabilities()` only when you source capabilities
+from a registry or remote API. `ModelProvider.count_tokens()` uses a simple
+4-characters-per-token estimate so providers work out of the box—override it
+only when you can call the provider's real tokenizer (for example, the
+OpenAI-compatible base class integrates `tiktoken`).
 
 #### Option B: OpenAI-Compatible Provider (Simplified)
 
@@ -172,26 +167,16 @@ class ExampleProvider(OpenAICompatibleProvider):
     def __init__(self, api_key: str, **kwargs):
         kwargs.setdefault("base_url", "https://api.example.com/v1")
         super().__init__(api_key, **kwargs)
-    
-    def get_capabilities(self, model_name: str) -> ModelCapabilities:
-        resolved_name = self._resolve_model_name(model_name)
-        if resolved_name not in self.MODEL_CAPABILITIES:
-            raise ValueError(f"Unsupported model: {model_name}")
-        return self.MODEL_CAPABILITIES[resolved_name]
-    
+
     def get_provider_type(self) -> ProviderType:
         return ProviderType.EXAMPLE
-    
-    def validate_model_name(self, model_name: str) -> bool:
-        resolved_name = self._resolve_model_name(model_name)
-        return resolved_name in self.MODEL_CAPABILITIES
-    
-    def generate_content(self, prompt: str, model_name: str, **kwargs) -> ModelResponse:
-        # IMPORTANT: Resolve aliases before API call
-        resolved_model_name = self._resolve_model_name(model_name)
-        return super().generate_content(prompt=prompt, model_name=resolved_model_name, **kwargs)
 ```
 
+`OpenAICompatibleProvider` already exposes the declared models via
+`MODEL_CAPABILITIES`, resolves aliases through the shared base pipeline, and
+enforces restrictions. Most subclasses only need to provide the class metadata
+shown above.
+
 ### 3. Register Your Provider
 
 Add environment variable mapping in `providers/registry.py`:
@@ -237,15 +222,11 @@ DISABLED_TOOLS=debug,tracer
 Create basic tests to verify your implementation:
 
 ```python
-# Test model validation
-provider = ExampleModelProvider("test-key")
-assert provider.validate_model_name("large") == True
-assert provider.validate_model_name("unknown") == False
-
 # Test capabilities
-caps = provider.get_capabilities("large")
-assert caps.context_window > 0
-assert caps.provider == ProviderType.EXAMPLE
+provider = ExampleModelProvider("test-key")
+capabilities = provider.get_capabilities("large")
+assert capabilities.context_window > 0
+assert capabilities.provider == ProviderType.EXAMPLE
 ```
 
 
@@ -259,31 +240,19 @@ When a user requests a model, providers are checked in priority order:
 3. **OpenRouter** - catch-all for everything else
 
 ### Model Validation
-Your `validate_model_name()` should **only** return `True` for models you explicitly support:
-
-```python
-def validate_model_name(self, model_name: str) -> bool:
-    resolved_name = self._resolve_model_name(model_name)
-    return resolved_name in self.MODEL_CAPABILITIES  # Be specific!
-```
+`ModelProvider.validate_model_name()` delegates to `get_capabilities()` so most
+providers can rely on the shared implementation. Override it only when you need
+to opt out of that pipeline—for example, `CustomProvider` declines OpenRouter
+models so they fall through to the dedicated OpenRouter provider.
 
 ### Model Aliases
-The base class handles alias resolution automatically via the `aliases` field in `ModelCapabilities`.
+Aliases declared on `ModelCapabilities` are applied automatically via
+`_resolve_model_name()`, and both the validation and request flows call it
+before touching your SDK. Override `generate_content()` only when your provider
+needs additional alias handling beyond the shared behaviour.
 
 ## Important Notes
 
-### Alias Resolution in OpenAI-Compatible Providers
-If using `OpenAICompatibleProvider` with aliases, **you must override `generate_content()`** to resolve aliases before API calls:
-
-```python
-def generate_content(self, prompt: str, model_name: str, **kwargs) -> ModelResponse:
-    # Resolve alias before API call
-    resolved_model_name = self._resolve_model_name(model_name)
-    return super().generate_content(prompt=prompt, model_name=resolved_model_name, **kwargs)
-```
-
-Without this, API calls with aliases like `"large"` will fail because your API doesn't recognize the alias.
-
 ## Best Practices
 
 - **Be specific in model validation** - only accept models you actually support
diff --git a/providers/base.py b/providers/base.py
index d959832..05b688a 100644
--- a/providers/base.py
+++ b/providers/base.py
@@ -43,128 +43,37 @@ class ModelProvider(ABC):
         self.api_key = api_key
         self.config = kwargs
 
-    @abstractmethod
-    def get_capabilities(self, model_name: str) -> ModelCapabilities:
-        """Get capabilities for a specific model."""
-        pass
-
-    @abstractmethod
-    def generate_content(
-        self,
-        prompt: str,
-        model_name: str,
-        system_prompt: Optional[str] = None,
-        temperature: float = 0.3,
-        max_output_tokens: Optional[int] = None,
-        **kwargs,
-    ) -> ModelResponse:
-        """Generate content using the model.
-
-        Args:
-            prompt: User prompt to send to the model
-            model_name: Name of the model to use
-            system_prompt: Optional system prompt for model behavior
-            temperature: Sampling temperature (0-2)
-            max_output_tokens: Maximum tokens to generate
-            **kwargs: Provider-specific parameters
-
-        Returns:
-            ModelResponse with generated content and metadata
-        """
-        pass
-
-    def count_tokens(self, text: str, model_name: str) -> int:
-        """Estimate token usage for a piece of text.
-
-        Providers can rely on this shared implementation or override it when
-        they expose a more accurate tokenizer. This default uses a simple
-        character-based heuristic so it works even without provider-specific
-        tooling.
-        """
-
-        resolved_model = self._resolve_model_name(model_name)
-
-        if not text:
-            return 0
-
-        # Rough estimation: ~4 characters per token for English text
-        estimated = max(1, len(text) // 4)
-        logger.debug("Estimating %s tokens for model %s via character heuristic", estimated, resolved_model)
-        return estimated
-
+    # ------------------------------------------------------------------
+    # Provider identity & capability surface
+    # ------------------------------------------------------------------
     @abstractmethod
     def get_provider_type(self) -> ProviderType:
-        """Get the provider type."""
-        pass
+        """Return the concrete provider identity."""
 
-    @abstractmethod
-    def validate_model_name(self, model_name: str) -> bool:
-        """Validate if the model name is supported by this provider."""
-        pass
+    def get_capabilities(self, model_name: str) -> ModelCapabilities:
+        """Resolve capability metadata for a model name.
 
-    def validate_parameters(self, model_name: str, temperature: float, **kwargs) -> None:
-        """Validate model parameters against capabilities.
-
-        Raises:
-            ValueError: If parameters are invalid
+        This centralises the alias resolution → lookup → restriction check
+        pipeline so providers only override the pieces they genuinely need to
+        customise. Subclasses usually only override ``_lookup_capabilities`` to
+        integrate a registry or dynamic source, or ``_finalise_capabilities`` to
+        tweak the returned object.
         """
-        capabilities = self.get_capabilities(model_name)
 
-        # Validate temperature using constraint
-        if not capabilities.temperature_constraint.validate(temperature):
-            constraint_desc = capabilities.temperature_constraint.get_description()
-            raise ValueError(f"Temperature {temperature} is invalid for model {model_name}. {constraint_desc}")
+        resolved_name = self._resolve_model_name(model_name)
+        capabilities = self._lookup_capabilities(resolved_name, model_name)
 
-    def get_model_configurations(self) -> dict[str, ModelCapabilities]:
-        """Get model configurations for this provider.
+        if capabilities is None:
+            self._raise_unsupported_model(model_name)
 
-        This is a hook method that subclasses can override to provide
-        their model configurations from different sources.
+        self._ensure_model_allowed(capabilities, resolved_name, model_name)
+        return self._finalise_capabilities(capabilities, resolved_name, model_name)
+
+    def get_all_model_capabilities(self) -> dict[str, ModelCapabilities]:
+        """Return the provider's statically declared model capabilities."""
 
-        Returns:
-            Dictionary mapping model names to their ModelCapabilities objects
-        """
-        model_map = getattr(self, "MODEL_CAPABILITIES", None)
-        if isinstance(model_map, dict) and model_map:
-            return {k: v for k, v in model_map.items() if isinstance(v, ModelCapabilities)}
         return {}
 
-    def _resolve_model_name(self, model_name: str) -> str:
-        """Resolve model shorthand to full name.
-
-        This implementation uses the hook methods to support different
-        model configuration sources.
-
-        Args:
-            model_name: Model name that may be an alias
-
-        Returns:
-            Resolved model name
-        """
-        # Get model configurations from the hook method
-        model_configs = self.get_model_configurations()
-
-        # First check if it's already a base model name (case-sensitive exact match)
-        if model_name in model_configs:
-            return model_name
-
-        # Check case-insensitively for both base models and aliases
-        model_name_lower = model_name.lower()
-
-        # Check base model names case-insensitively
-        for base_model in model_configs:
-            if base_model.lower() == model_name_lower:
-                return base_model
-
-        # Check aliases from the model configurations
-        alias_map = ModelCapabilities.collect_aliases(model_configs)
-        for base_model, aliases in alias_map.items():
-            if any(alias.lower() == model_name_lower for alias in aliases):
-                return base_model
-
-        # If not found, return as-is
-        return model_name
-
     def list_models(
         self,
         *,
@@ -175,7 +84,7 @@ class ModelProvider(ABC):
     ) -> list[str]:
         """Return formatted model names supported by this provider."""
 
-        model_configs = self.get_model_configurations()
+        model_configs = self.get_all_model_capabilities()
         if not model_configs:
             return []
 
@@ -202,36 +111,155 @@ class ModelProvider(ABC):
             unique=unique,
         )
 
-    def close(self):
-        """Clean up any resources held by the provider.
+    # ------------------------------------------------------------------
+    # Request execution
+    # ------------------------------------------------------------------
+    @abstractmethod
+    def generate_content(
+        self,
+        prompt: str,
+        model_name: str,
+        system_prompt: Optional[str] = None,
+        temperature: float = 0.3,
+        max_output_tokens: Optional[int] = None,
+        **kwargs,
+    ) -> ModelResponse:
+        """Generate content using the model."""
+
+    def count_tokens(self, text: str, model_name: str) -> int:
+        """Estimate token usage for a piece of text."""
+
+        resolved_model = self._resolve_model_name(model_name)
+
+        if not text:
+            return 0
+
+        estimated = max(1, len(text) // 4)
+        logger.debug("Estimating %s tokens for model %s via character heuristic", estimated, resolved_model)
+        return estimated
+
+    def close(self) -> None:
+        """Clean up any resources held by the provider."""
 
-        Default implementation does nothing.
-        Subclasses should override if they hold resources that need cleanup.
-        """
-        # Base implementation: no resources to clean up
         return
 
+    # ------------------------------------------------------------------
+    # Validation hooks
+    # ------------------------------------------------------------------
+    def validate_model_name(self, model_name: str) -> bool:
+        """Return ``True`` when the model resolves to an allowed capability."""
+
+        try:
+            self.get_capabilities(model_name)
+        except ValueError:
+            return False
+        return True
+
+    def validate_parameters(self, model_name: str, temperature: float, **kwargs) -> None:
+        """Validate model parameters against capabilities."""
+
+        capabilities = self.get_capabilities(model_name)
+
+        if not capabilities.temperature_constraint.validate(temperature):
+            constraint_desc = capabilities.temperature_constraint.get_description()
+            raise ValueError(f"Temperature {temperature} is invalid for model {model_name}. {constraint_desc}")
+
+    # ------------------------------------------------------------------
+    # Preference / registry hooks
+    # ------------------------------------------------------------------
     def get_preferred_model(self, category: "ToolModelCategory", allowed_models: list[str]) -> Optional[str]:
-        """Get the preferred model from this provider for a given category.
+        """Get the preferred model from this provider for a given category."""
 
-        Args:
-            category: The tool category requiring a model
-            allowed_models: Pre-filtered list of model names that are allowed by restrictions
-
-        Returns:
-            Model name if this provider has a preference, None otherwise
-        """
-        # Default implementation - providers can override with specific logic
         return None
 
     def get_model_registry(self) -> Optional[dict[str, Any]]:
-        """Get the model registry for providers that maintain one.
+        """Return the model registry backing this provider, if any."""
 
-        This is a hook method for providers like CustomProvider that maintain
-        a dynamic model registry.
+        return None
+
+    # ------------------------------------------------------------------
+    # Capability lookup pipeline
+    # ------------------------------------------------------------------
+    def _lookup_capabilities(
+        self,
+        canonical_name: str,
+        requested_name: Optional[str] = None,
+    ) -> Optional[ModelCapabilities]:
+        """Return ``ModelCapabilities`` for the canonical model name."""
+
+        return self.get_all_model_capabilities().get(canonical_name)
+
+    def _ensure_model_allowed(
+        self,
+        capabilities: ModelCapabilities,
+        canonical_name: str,
+        requested_name: str,
+    ) -> None:
+        """Raise ``ValueError`` if the model violates restriction policy."""
+
+        try:
+            from utils.model_restrictions import get_restriction_service
+        except Exception:  # pragma: no cover - only triggered if service import breaks
+            return
+
+        restriction_service = get_restriction_service()
+        if not restriction_service:
+            return
+
+        if restriction_service.is_allowed(self.get_provider_type(), canonical_name, requested_name):
+            return
+
+        raise ValueError(
+            f"{self.get_provider_type().value} model '{canonical_name}' is not allowed by restriction policy."
+        )
+
+    def _finalise_capabilities(
+        self,
+        capabilities: ModelCapabilities,
+        canonical_name: str,
+        requested_name: str,
+    ) -> ModelCapabilities:
+        """Allow subclasses to adjust capability metadata before returning."""
+
+        return capabilities
+
+    def _raise_unsupported_model(self, model_name: str) -> None:
+        """Raise the canonical unsupported-model error."""
+
+        raise ValueError(f"Unsupported model '{model_name}' for provider {self.get_provider_type().value}.")
+
+    def _resolve_model_name(self, model_name: str) -> str:
+        """Resolve model shorthand to full name.
+
+        This implementation uses the hook methods to support different
+        model configuration sources.
+
+        Args:
+            model_name: Model name that may be an alias
 
         Returns:
-            Model registry dict or None if not applicable
+            Resolved model name
         """
-        # Default implementation - most providers don't have a registry
-        return None
+        # Get model configurations from the hook method
+        model_configs = self.get_all_model_capabilities()
+
+        # First check if it's already a base model name (case-sensitive exact match)
+        if model_name in model_configs:
+            return model_name
+
+        # Check case-insensitively for both base models and aliases
+        model_name_lower = model_name.lower()
+
+        # Check base model names case-insensitively
+        for base_model in model_configs:
+            if base_model.lower() == model_name_lower:
+                return base_model
+
+        # Check aliases from the model configurations
+        alias_map = ModelCapabilities.collect_aliases(model_configs)
+        for base_model, aliases in alias_map.items():
+            if any(alias.lower() == model_name_lower for alias in aliases):
+                return base_model
+
+        # If not found, return as-is
+        return model_name
diff --git a/providers/custom.py b/providers/custom.py
index 6a06457..63e6f8e 100644
--- a/providers/custom.py
+++ b/providers/custom.py
@@ -83,117 +83,69 @@ class CustomProvider(OpenAICompatibleProvider):
             aliases = self._registry.list_aliases()
             logging.info(f"Custom provider loaded {len(models)} models with {len(aliases)} aliases")
 
-    def _resolve_model_name(self, model_name: str) -> str:
-        """Resolve model aliases to actual model names.
+    # ------------------------------------------------------------------
+    # Capability surface
+    # ------------------------------------------------------------------
+    def _lookup_capabilities(
+        self,
+        canonical_name: str,
+        requested_name: Optional[str] = None,
+    ) -> Optional[ModelCapabilities]:
+        """Return custom capabilities from the registry or generic defaults."""
 
-        For Ollama-style models, strips version tags (e.g., 'llama3.2:latest' -> 'llama3.2')
-        since the base model name is what's typically used in API calls.
-
-        Args:
-            model_name: Input model name or alias
-
-        Returns:
-            Resolved model name with version tags stripped if applicable
-        """
-        # First, try to resolve through registry as-is
-        config = self._registry.resolve(model_name)
-
-        if config:
-            if config.model_name != model_name:
-                logging.info(f"Resolved model alias '{model_name}' to '{config.model_name}'")
-            return config.model_name
-        else:
-            # If not found in registry, handle version tags for local models
-            # Strip version tags (anything after ':') for Ollama-style models
-            if ":" in model_name:
-                base_model = model_name.split(":")[0]
-                logging.debug(f"Stripped version tag from '{model_name}' -> '{base_model}'")
-
-                # Try to resolve the base model through registry
-                base_config = self._registry.resolve(base_model)
-                if base_config:
-                    logging.info(f"Resolved base model '{base_model}' to '{base_config.model_name}'")
-                    return base_config.model_name
-                else:
-                    return base_model
-            else:
-                # If not found in registry and no version tag, return as-is
-                logging.debug(f"Model '{model_name}' not found in registry, using as-is")
-                return model_name
-
-    def get_capabilities(self, model_name: str) -> ModelCapabilities:
-        """Get capabilities for a custom model.
-
-        Args:
-            model_name: Name of the model (or alias)
-
-        Returns:
-            ModelCapabilities from registry or generic defaults
-        """
-        # Try to get from registry first
-        capabilities = self._registry.get_capabilities(model_name)
+        builtin = super()._lookup_capabilities(canonical_name, requested_name)
+        if builtin is not None:
+            return builtin
 
+        capabilities = self._registry.get_capabilities(canonical_name)
         if capabilities:
-            # Check if this is an OpenRouter model and apply restrictions
-            config = self._registry.resolve(model_name)
-            if config and not config.is_custom:
-                # This is an OpenRouter model, check restrictions
-                from utils.model_restrictions import get_restriction_service
-
-                restriction_service = get_restriction_service()
-                if not restriction_service.is_allowed(ProviderType.OPENROUTER, config.model_name, model_name):
-                    raise ValueError(f"OpenRouter model '{model_name}' is not allowed by restriction policy.")
-
-                # Update provider type to OPENROUTER for OpenRouter models
-                capabilities.provider = ProviderType.OPENROUTER
-            else:
-                # Update provider type to CUSTOM for local custom models
+            config = self._registry.resolve(canonical_name)
+            if config and getattr(config, "is_custom", False):
                 capabilities.provider = ProviderType.CUSTOM
-            return capabilities
-        else:
-            # Resolve any potential aliases and create generic capabilities
-            resolved_name = self._resolve_model_name(model_name)
+                return capabilities
+            # Non-custom models should fall through so OpenRouter handles them
+            return None
 
-            logging.debug(
-                f"Using generic capabilities for '{resolved_name}' via Custom API. "
-                "Consider adding to custom_models.json for specific capabilities."
-            )
+        logging.debug(
+            f"Using generic capabilities for '{canonical_name}' via Custom API. "
+            "Consider adding to custom_models.json for specific capabilities."
+        )
 
-            # Infer temperature behaviour for generic capability fallback
-            supports_temperature, temperature_constraint, temperature_reason = TemperatureConstraint.resolve_settings(
-                resolved_name
-            )
+        supports_temperature, temperature_constraint, temperature_reason = TemperatureConstraint.resolve_settings(
+            canonical_name
+        )
 
-            logging.warning(
-                f"Model '{resolved_name}' not found in custom_models.json. Using generic capabilities with inferred settings. "
-                f"Temperature support: {supports_temperature} ({temperature_reason}). "
-                "For better accuracy, add this model to your custom_models.json configuration."
-            )
+        logging.warning(
+            f"Model '{canonical_name}' not found in custom_models.json. Using generic capabilities with inferred settings. "
+            f"Temperature support: {supports_temperature} ({temperature_reason}). "
+            "For better accuracy, add this model to your custom_models.json configuration."
+        )
 
-            # Create generic capabilities with inferred defaults
-            capabilities = ModelCapabilities(
-                provider=ProviderType.CUSTOM,
-                model_name=resolved_name,
-                friendly_name=f"{self.FRIENDLY_NAME} ({resolved_name})",
-                context_window=32_768,  # Conservative default
-                max_output_tokens=32_768,  # Conservative default max output
-                supports_extended_thinking=False,  # Most custom models don't support this
-                supports_system_prompts=True,
-                supports_streaming=True,
-                supports_function_calling=False,  # Conservative default
-                supports_temperature=supports_temperature,
-                temperature_constraint=temperature_constraint,
-            )
-
-            # Mark as generic for validation purposes
-            capabilities._is_generic = True
-
-            return capabilities
+        generic = ModelCapabilities(
+            provider=ProviderType.CUSTOM,
+            model_name=canonical_name,
+            friendly_name=f"{self.FRIENDLY_NAME} ({canonical_name})",
+            context_window=32_768,
+            max_output_tokens=32_768,
+            supports_extended_thinking=False,
+            supports_system_prompts=True,
+            supports_streaming=True,
+            supports_function_calling=False,
+            supports_temperature=supports_temperature,
+            temperature_constraint=temperature_constraint,
+        )
+        generic._is_generic = True
+        return generic
 
     def get_provider_type(self) -> ProviderType:
-        """Get the provider type."""
+        """Identify this provider for restriction and logging logic."""
+
         return ProviderType.CUSTOM
 
+    # ------------------------------------------------------------------
+    # Validation
+    # ------------------------------------------------------------------
+
     def validate_model_name(self, model_name: str) -> bool:
         """Validate if the model name is allowed.
 
@@ -206,49 +158,41 @@ class CustomProvider(OpenAICompatibleProvider):
         Returns:
             True if model is intended for custom/local endpoint
         """
-        # logging.debug(f"Custom provider validating model: '{model_name}'")
+        if super().validate_model_name(model_name):
+            return True
 
-        # Try to resolve through registry first
         config = self._registry.resolve(model_name)
-        if config:
-            model_id = config.model_name
-            # Use explicit is_custom flag for clean validation
-            if config.is_custom:
-                logging.debug(f"... [Custom] Model '{model_name}' -> '{model_id}' validated via registry")
-                return True
-            else:
-                # This is a cloud/OpenRouter model - CustomProvider should NOT handle these
-                # Let OpenRouter provider handle them instead
-                # logging.debug(f"... [Custom] Model '{model_name}' -> '{model_id}' not custom (defer to OpenRouter)")
-                return False
+        if config and not getattr(config, "is_custom", False):
+            return False
 
-        # Handle version tags for unknown models (e.g., "my-model:latest")
         clean_model_name = model_name
         if ":" in model_name:
-            clean_model_name = model_name.split(":")[0]
+            clean_model_name = model_name.split(":", 1)[0]
             logging.debug(f"Stripped version tag from '{model_name}' -> '{clean_model_name}'")
-            # Try to resolve the clean name
+
+            if super().validate_model_name(clean_model_name):
+                return True
+
             config = self._registry.resolve(clean_model_name)
-            if config:
-                return self.validate_model_name(clean_model_name)  # Recursively validate clean name
+            if config and not getattr(config, "is_custom", False):
+                return False
 
-        # For unknown models (not in registry), only accept if they look like local models
-        # This maintains backward compatibility for custom models not yet in the registry
-
-        # Accept models with explicit local indicators in the name
-        if any(indicator in clean_model_name.lower() for indicator in ["local", "ollama", "vllm", "lmstudio"]):
+        lowered = clean_model_name.lower()
+        if any(indicator in lowered for indicator in ["local", "ollama", "vllm", "lmstudio"]):
             logging.debug(f"Model '{clean_model_name}' validated via local indicators")
             return True
 
-        # Accept simple model names without vendor prefix (likely local/custom models)
         if "/" not in clean_model_name:
             logging.debug(f"Model '{clean_model_name}' validated as potential local model (no vendor prefix)")
             return True
 
-        # Reject everything else (likely cloud models not in registry)
         logging.debug(f"Model '{model_name}' rejected by custom provider (appears to be cloud model)")
         return False
 
+    # ------------------------------------------------------------------
+    # Request execution
+    # ------------------------------------------------------------------
+
     def generate_content(
         self,
         prompt: str,
@@ -284,25 +228,41 @@ class CustomProvider(OpenAICompatibleProvider):
             **kwargs,
         )
 
-    def get_model_configurations(self) -> dict[str, ModelCapabilities]:
-        """Get model configurations from the registry.
+    # ------------------------------------------------------------------
+    # Registry helpers
+    # ------------------------------------------------------------------
 
-        For CustomProvider, we convert registry configurations to ModelCapabilities objects.
+    def _resolve_model_name(self, model_name: str) -> str:
+        """Resolve registry aliases and strip version tags for local models."""
 
-        Returns:
-            Dictionary mapping model names to their ModelCapabilities objects
-        """
+        config = self._registry.resolve(model_name)
+        if config:
+            if config.model_name != model_name:
+                logging.info(f"Resolved model alias '{model_name}' to '{config.model_name}'")
+            return config.model_name
 
-        configs = {}
+        if ":" in model_name:
+            base_model = model_name.split(":")[0]
+            logging.debug(f"Stripped version tag from '{model_name}' -> '{base_model}'")
 
-        if self._registry:
-            # Get all models from registry
-            for model_name in self._registry.list_models():
-                # Only include custom models that this provider validates
-                if self.validate_model_name(model_name):
-                    config = self._registry.resolve(model_name)
-                    if config and config.is_custom:
-                        # Use ModelCapabilities directly from registry
-                        configs[model_name] = config
+            base_config = self._registry.resolve(base_model)
+            if base_config:
+                logging.info(f"Resolved base model '{base_model}' to '{base_config.model_name}'")
+                return base_config.model_name
+            return base_model
 
-        return configs
+        logging.debug(f"Model '{model_name}' not found in registry, using as-is")
+        return model_name
+
+    def get_all_model_capabilities(self) -> dict[str, ModelCapabilities]:
+        """Expose registry capabilities for models marked as custom."""
+
+        if not self._registry:
+            return {}
+
+        capabilities: dict[str, ModelCapabilities] = {}
+        for model_name in self._registry.list_models():
+            config = self._registry.resolve(model_name)
+            if config and getattr(config, "is_custom", False):
+                capabilities[model_name] = config
+        return capabilities
diff --git a/providers/dial.py b/providers/dial.py
index 1c0b885..db11417 100644
--- a/providers/dial.py
+++ b/providers/dial.py
@@ -261,68 +261,10 @@ class DIALModelProvider(OpenAICompatibleProvider):
 
         logger.info(f"Initialized DIAL provider with host: {dial_host} and api-version: {self.api_version}")
 
-    def get_capabilities(self, model_name: str) -> ModelCapabilities:
-        """Get capabilities for a specific model.
-
-        Args:
-            model_name: Name of the model (can be shorthand)
-
-        Returns:
-            ModelCapabilities object
-
-        Raises:
-            ValueError: If model is not supported or not allowed
-        """
-        resolved_name = self._resolve_model_name(model_name)
-
-        if resolved_name not in self.MODEL_CAPABILITIES:
-            raise ValueError(f"Unsupported DIAL model: {model_name}")
-
-        # Check restrictions
-        from utils.model_restrictions import get_restriction_service
-
-        restriction_service = get_restriction_service()
-        if not restriction_service.is_allowed(ProviderType.DIAL, resolved_name, model_name):
-            raise ValueError(f"Model '{model_name}' is not allowed by restriction policy.")
-
-        # Return the ModelCapabilities object directly from MODEL_CAPABILITIES
-        return self.MODEL_CAPABILITIES[resolved_name]
-
     def get_provider_type(self) -> ProviderType:
         """Get the provider type."""
         return ProviderType.DIAL
 
-    def validate_model_name(self, model_name: str) -> bool:
-        """Validate if the model name is supported.
-
-        Args:
-            model_name: Model name to validate
-
-        Returns:
-            True if model is supported and allowed, False otherwise
-        """
-        resolved_name = self._resolve_model_name(model_name)
-
-        if resolved_name not in self.MODEL_CAPABILITIES:
-            return False
-
-        # Check against base class allowed_models if configured
-        if self.allowed_models is not None:
-            # Check both original and resolved names (case-insensitive)
-            if model_name.lower() not in self.allowed_models and resolved_name.lower() not in self.allowed_models:
-                logger.debug(f"DIAL model '{model_name}' -> '{resolved_name}' not in allowed_models list")
-                return False
-
-        # Also check restrictions via ModelRestrictionService
-        from utils.model_restrictions import get_restriction_service
-
-        restriction_service = get_restriction_service()
-        if not restriction_service.is_allowed(ProviderType.DIAL, resolved_name, model_name):
-            logger.debug(f"DIAL model '{model_name}' -> '{resolved_name}' blocked by restrictions")
-            return False
-
-        return True
-
     def _get_deployment_client(self, deployment: str):
         """Get or create a cached client for a specific deployment.
 
@@ -504,7 +446,7 @@ class DIALModelProvider(OpenAICompatibleProvider):
             f"DIAL API error for model {model_name} after {self.MAX_RETRIES} attempts: {str(last_exception)}"
         )
 
-    def close(self):
+    def close(self) -> None:
         """Clean up HTTP clients when provider is closed."""
         logger.info("Closing DIAL provider HTTP clients...")
 
diff --git a/providers/gemini.py b/providers/gemini.py
index 952aab4..f333cf2 100644
--- a/providers/gemini.py
+++ b/providers/gemini.py
@@ -131,6 +131,19 @@ class GeminiModelProvider(ModelProvider):
         self._token_counters = {}  # Cache for token counting
         self._base_url = kwargs.get("base_url", None)  # Optional custom endpoint
 
+    # ------------------------------------------------------------------
+    # Capability surface
+    # ------------------------------------------------------------------
+
+    def get_all_model_capabilities(self) -> dict[str, ModelCapabilities]:
+        """Return statically defined Gemini capabilities."""
+
+        return dict(self.MODEL_CAPABILITIES)
+
+    # ------------------------------------------------------------------
+    # Client access
+    # ------------------------------------------------------------------
+
     @property
     def client(self):
         """Lazy initialization of Gemini client."""
@@ -146,25 +159,9 @@ class GeminiModelProvider(ModelProvider):
                 self._client = genai.Client(api_key=self.api_key)
         return self._client
 
-    def get_capabilities(self, model_name: str) -> ModelCapabilities:
-        """Get capabilities for a specific Gemini model."""
-        # Resolve shorthand
-        resolved_name = self._resolve_model_name(model_name)
-
-        if resolved_name not in self.MODEL_CAPABILITIES:
-            raise ValueError(f"Unsupported Gemini model: {model_name}")
-
-        # Check if model is allowed by restrictions
-        from utils.model_restrictions import get_restriction_service
-
-        restriction_service = get_restriction_service()
-        # IMPORTANT: Parameter order is (provider_type, model_name, original_name)
-        # resolved_name is the canonical model name, model_name is the user input
-        if not restriction_service.is_allowed(ProviderType.GOOGLE, resolved_name, model_name):
-            raise ValueError(f"Gemini model '{resolved_name}' is not allowed by restriction policy.")
-
-        # Return the ModelCapabilities object directly from MODEL_CAPABILITIES
-        return self.MODEL_CAPABILITIES[resolved_name]
+    # ------------------------------------------------------------------
+    # Request execution
+    # ------------------------------------------------------------------
 
     def generate_content(
         self,
@@ -365,26 +362,6 @@ class GeminiModelProvider(ModelProvider):
         """Get the provider type."""
         return ProviderType.GOOGLE
 
-    def validate_model_name(self, model_name: str) -> bool:
-        """Validate if the model name is supported and allowed."""
-        resolved_name = self._resolve_model_name(model_name)
-
-        # First check if model is supported
-        if resolved_name not in self.MODEL_CAPABILITIES:
-            return False
-
-        # Then check if model is allowed by restrictions
-        from utils.model_restrictions import get_restriction_service
-
-        restriction_service = get_restriction_service()
-        # IMPORTANT: Parameter order is (provider_type, model_name, original_name)
-        # resolved_name is the canonical model name, model_name is the user input
-        if not restriction_service.is_allowed(ProviderType.GOOGLE, resolved_name, model_name):
-            logger.debug(f"Gemini model '{model_name}' -> '{resolved_name}' blocked by restrictions")
-            return False
-
-        return True
-
     def get_thinking_budget(self, model_name: str, thinking_mode: str) -> int:
         """Get actual thinking token budget for a model and thinking mode."""
         resolved_name = self._resolve_model_name(model_name)
diff --git a/providers/openai_compatible.py b/providers/openai_compatible.py
index 98de109..8714186 100644
--- a/providers/openai_compatible.py
+++ b/providers/openai_compatible.py
@@ -5,7 +5,6 @@ import ipaddress
 import logging
 import os
 import time
-from abc import abstractmethod
 from typing import Optional
 from urllib.parse import urlparse
 
@@ -61,6 +60,33 @@ class OpenAICompatibleProvider(ModelProvider):
                 "This may be insecure. Consider setting an API key for authentication."
             )
 
+    def _ensure_model_allowed(
+        self,
+        capabilities: ModelCapabilities,
+        canonical_name: str,
+        requested_name: str,
+    ) -> None:
+        """Respect provider-specific allowlists before default restriction checks."""
+
+        super()._ensure_model_allowed(capabilities, canonical_name, requested_name)
+
+        if self.allowed_models is not None:
+            requested = requested_name.lower()
+            canonical = canonical_name.lower()
+
+            if requested not in self.allowed_models and canonical not in self.allowed_models:
+                raise ValueError(
+                    f"Model '{requested_name}' is not allowed by restriction policy. Allowed models: {sorted(self.allowed_models)}"
+                )
+
+    def get_all_model_capabilities(self) -> dict[str, ModelCapabilities]:
+        """Return statically declared capabilities for OpenAI-compatible providers."""
+
+        model_map = getattr(self, "MODEL_CAPABILITIES", None)
+        if isinstance(model_map, dict):
+            return {k: v for k, v in model_map.items() if isinstance(v, ModelCapabilities)}
+        return {}
+
     def _parse_allowed_models(self) -> Optional[set[str]]:
         """Parse allowed models from environment variable.
 
@@ -686,30 +712,6 @@ class OpenAICompatibleProvider(ModelProvider):
 
         return super().count_tokens(text, model_name)
 
-    @abstractmethod
-    def get_capabilities(self, model_name: str) -> ModelCapabilities:
-        """Get capabilities for a specific model.
-
-        Must be implemented by subclasses.
-        """
-        pass
-
-    @abstractmethod
-    def get_provider_type(self) -> ProviderType:
-        """Get the provider type.
-
-        Must be implemented by subclasses.
-        """
-        pass
-
-    @abstractmethod
-    def validate_model_name(self, model_name: str) -> bool:
-        """Validate if the model name is supported.
-
-        Must be implemented by subclasses.
-        """
-        pass
-
     def _is_error_retryable(self, error: Exception) -> bool:
         """Determine if an error should be retried based on structured error codes.
 
diff --git a/providers/openai_provider.py b/providers/openai_provider.py
index 29071f0..a032756 100644
--- a/providers/openai_provider.py
+++ b/providers/openai_provider.py
@@ -174,106 +174,61 @@ class OpenAIModelProvider(OpenAICompatibleProvider):
         kwargs.setdefault("base_url", "https://api.openai.com/v1")
         super().__init__(api_key, **kwargs)
 
-    def get_capabilities(self, model_name: str) -> ModelCapabilities:
-        """Get capabilities for a specific OpenAI model."""
-        # First check if it's a key in MODEL_CAPABILITIES
-        if model_name in self.MODEL_CAPABILITIES:
-            self._check_model_restrictions(model_name, model_name)
-            return self.MODEL_CAPABILITIES[model_name]
+    # ------------------------------------------------------------------
+    # Capability surface
+    # ------------------------------------------------------------------
 
-        # Try resolving as alias
-        resolved_name = self._resolve_model_name(model_name)
+    def _lookup_capabilities(
+        self,
+        canonical_name: str,
+        requested_name: Optional[str] = None,
+    ) -> Optional[ModelCapabilities]:
+        """Look up OpenAI capabilities from built-ins or the custom registry."""
 
-        # Check if resolved name is a key
-        if resolved_name in self.MODEL_CAPABILITIES:
-            self._check_model_restrictions(resolved_name, model_name)
-            return self.MODEL_CAPABILITIES[resolved_name]
+        builtin = super()._lookup_capabilities(canonical_name, requested_name)
+        if builtin is not None:
+            return builtin
 
-        # Finally check if resolved name matches any API model name
-        for key, capabilities in self.MODEL_CAPABILITIES.items():
-            if resolved_name == capabilities.model_name:
-                self._check_model_restrictions(key, model_name)
-                return capabilities
-
-        # Check custom models registry for user-configured OpenAI models
         try:
             from .openrouter_registry import OpenRouterModelRegistry
 
             registry = OpenRouterModelRegistry()
-            config = registry.get_model_config(resolved_name)
+            config = registry.get_model_config(canonical_name)
 
             if config and config.provider == ProviderType.OPENAI:
-                self._check_model_restrictions(config.model_name, model_name)
-
-                # Update provider type to ensure consistency
-                config.provider = ProviderType.OPENAI
                 return config
 
-        except Exception as e:
-            # Log but don't fail - registry might not be available
-            logger.debug(f"Could not check custom models registry for '{resolved_name}': {e}")
+        except Exception as exc:  # pragma: no cover - registry failures are non-critical
+            logger.debug(f"Could not resolve custom OpenAI model '{canonical_name}': {exc}")
 
+        return None
+
+    def _finalise_capabilities(
+        self,
+        capabilities: ModelCapabilities,
+        canonical_name: str,
+        requested_name: str,
+    ) -> ModelCapabilities:
+        """Ensure registry-sourced models report the correct provider type."""
+
+        if capabilities.provider != ProviderType.OPENAI:
+            capabilities.provider = ProviderType.OPENAI
+        return capabilities
+
+    def _raise_unsupported_model(self, model_name: str) -> None:
         raise ValueError(f"Unsupported OpenAI model: {model_name}")
 
-    def _check_model_restrictions(self, provider_model_name: str, user_model_name: str) -> None:
-        """Check if a model is allowed by restriction policy.
-
-        Args:
-            provider_model_name: The model name used by the provider
-            user_model_name: The model name requested by the user
-
-        Raises:
-            ValueError: If the model is not allowed by restriction policy
-        """
-        from utils.model_restrictions import get_restriction_service
-
-        restriction_service = get_restriction_service()
-        if not restriction_service.is_allowed(ProviderType.OPENAI, provider_model_name, user_model_name):
-            raise ValueError(f"OpenAI model '{user_model_name}' is not allowed by restriction policy.")
+    # ------------------------------------------------------------------
+    # Provider identity
+    # ------------------------------------------------------------------
 
     def get_provider_type(self) -> ProviderType:
         """Get the provider type."""
         return ProviderType.OPENAI
 
-    def validate_model_name(self, model_name: str) -> bool:
-        """Validate if the model name is supported and allowed."""
-        resolved_name = self._resolve_model_name(model_name)
-
-        # First, determine which model name to check against restrictions.
-        model_to_check = None
-        is_custom_model = False
-
-        if resolved_name in self.MODEL_CAPABILITIES:
-            model_to_check = resolved_name
-        else:
-            # If not a built-in model, check the custom models registry.
-            try:
-                from .openrouter_registry import OpenRouterModelRegistry
-
-                registry = OpenRouterModelRegistry()
-                config = registry.get_model_config(resolved_name)
-
-                if config and config.provider == ProviderType.OPENAI:
-                    model_to_check = config.model_name
-                    is_custom_model = True
-            except Exception as e:
-                # Log but don't fail - registry might not be available.
-                logger.debug(f"Could not check custom models registry for '{resolved_name}': {e}")
-
-        # If no model was found (neither built-in nor custom), it's invalid.
-        if not model_to_check:
-            return False
-
-        # Now, perform the restriction check once.
-        from utils.model_restrictions import get_restriction_service
-
-        restriction_service = get_restriction_service()
-        if not restriction_service.is_allowed(ProviderType.OPENAI, model_to_check, model_name):
-            model_type = "custom " if is_custom_model else ""
-            logger.debug(f"OpenAI {model_type}model '{model_name}' -> '{resolved_name}' blocked by restrictions")
-            return False
-
-        return True
+    # ------------------------------------------------------------------
+    # Request execution
+    # ------------------------------------------------------------------
 
     def generate_content(
         self,
@@ -298,6 +253,10 @@ class OpenAIModelProvider(OpenAICompatibleProvider):
             **kwargs,
         )
 
+    # ------------------------------------------------------------------
+    # Provider preferences
+    # ------------------------------------------------------------------
+
     def get_preferred_model(self, category: "ToolModelCategory", allowed_models: list[str]) -> Optional[str]:
         """Get OpenAI's preferred model for a given category from allowed models.
 
diff --git a/providers/openrouter.py b/providers/openrouter.py
index 1a60542..b4b9d6a 100644
--- a/providers/openrouter.py
+++ b/providers/openrouter.py
@@ -61,108 +61,52 @@ class OpenRouterProvider(OpenAICompatibleProvider):
             aliases = self._registry.list_aliases()
             logging.info(f"OpenRouter loaded {len(models)} models with {len(aliases)} aliases")
 
-    def _resolve_model_name(self, model_name: str) -> str:
-        """Resolve model aliases to OpenRouter model names.
+    # ------------------------------------------------------------------
+    # Capability surface
+    # ------------------------------------------------------------------
 
-        Args:
-            model_name: Input model name or alias
-
-        Returns:
-            Resolved OpenRouter model name
-        """
-        # Try to resolve through registry
-        config = self._registry.resolve(model_name)
-
-        if config:
-            if config.model_name != model_name:
-                logging.info(f"Resolved model alias '{model_name}' to '{config.model_name}'")
-            return config.model_name
-        else:
-            # If not found in registry, return as-is
-            # This allows using models not in our config file
-            logging.debug(f"Model '{model_name}' not found in registry, using as-is")
-            return model_name
-
-    def get_capabilities(self, model_name: str) -> ModelCapabilities:
-        """Get capabilities for a model.
-
-        Args:
-            model_name: Name of the model (or alias)
-
-        Returns:
-            ModelCapabilities from registry or generic defaults
-        """
-        # Try to get from registry first
-        capabilities = self._registry.get_capabilities(model_name)
+    def _lookup_capabilities(
+        self,
+        canonical_name: str,
+        requested_name: Optional[str] = None,
+    ) -> Optional[ModelCapabilities]:
+        """Fetch OpenRouter capabilities from the registry or build a generic fallback."""
 
+        capabilities = self._registry.get_capabilities(canonical_name)
         if capabilities:
             return capabilities
-        else:
-            # Resolve any potential aliases and create generic capabilities
-            resolved_name = self._resolve_model_name(model_name)
 
-            logging.debug(
-                f"Using generic capabilities for '{resolved_name}' via OpenRouter. "
-                "Consider adding to custom_models.json for specific capabilities."
-            )
+        logging.debug(
+            f"Using generic capabilities for '{canonical_name}' via OpenRouter. "
+            "Consider adding to custom_models.json for specific capabilities."
+        )
 
-            # Create generic capabilities with conservative defaults
-            capabilities = ModelCapabilities(
-                provider=ProviderType.OPENROUTER,
-                model_name=resolved_name,
-                friendly_name=self.FRIENDLY_NAME,
-                context_window=32_768,  # Conservative default context window
-                max_output_tokens=32_768,
-                supports_extended_thinking=False,
-                supports_system_prompts=True,
-                supports_streaming=True,
-                supports_function_calling=False,
-                temperature_constraint=RangeTemperatureConstraint(0.0, 2.0, 1.0),
-            )
+        generic = ModelCapabilities(
+            provider=ProviderType.OPENROUTER,
+            model_name=canonical_name,
+            friendly_name=self.FRIENDLY_NAME,
+            context_window=32_768,
+            max_output_tokens=32_768,
+            supports_extended_thinking=False,
+            supports_system_prompts=True,
+            supports_streaming=True,
+            supports_function_calling=False,
+            temperature_constraint=RangeTemperatureConstraint(0.0, 2.0, 1.0),
+        )
+        generic._is_generic = True
+        return generic
 
-            # Mark as generic for validation purposes
-            capabilities._is_generic = True
-
-            return capabilities
+    # ------------------------------------------------------------------
+    # Provider identity
+    # ------------------------------------------------------------------
 
     def get_provider_type(self) -> ProviderType:
-        """Get the provider type."""
+        """Identify this provider for restrictions and logging."""
         return ProviderType.OPENROUTER
 
-    def validate_model_name(self, model_name: str) -> bool:
-        """Validate if the model name is allowed.
-
-        As the catch-all provider, OpenRouter accepts any model name that wasn't
-        handled by higher-priority providers. OpenRouter will validate based on
-        the API key's permissions and local restrictions.
-
-        Args:
-            model_name: Model name to validate
-
-        Returns:
-            True if model is allowed, False if restricted
-        """
-        # Check model restrictions if configured
-        from utils.model_restrictions import get_restriction_service
-
-        restriction_service = get_restriction_service()
-        if restriction_service:
-            # Check if model name itself is allowed
-            if restriction_service.is_allowed(self.get_provider_type(), model_name):
-                return True
-
-            # Also check aliases - model_name might be an alias
-            model_config = self._registry.resolve(model_name)
-            if model_config and model_config.aliases:
-                for alias in model_config.aliases:
-                    if restriction_service.is_allowed(self.get_provider_type(), alias):
-                        return True
-
-            # If restrictions are configured and model/alias not in allowed list, reject
-            return False
-
-        # No restrictions configured - accept any model name as the fallback provider
-        return True
+    # ------------------------------------------------------------------
+    # Request execution
+    # ------------------------------------------------------------------
 
     def generate_content(
         self,
@@ -204,6 +148,10 @@ class OpenRouterProvider(OpenAICompatibleProvider):
             **kwargs,
         )
 
+    # ------------------------------------------------------------------
+    # Registry helpers
+    # ------------------------------------------------------------------
+
     def list_models(
         self,
         *,
@@ -227,6 +175,12 @@ class OpenRouterProvider(OpenAICompatibleProvider):
             if not config:
                 continue
 
+            # Custom models belong to CustomProvider; skip them here so the two
+            # providers don't race over the same registrations (important for tests
+            # that stub the registry with minimal objects lacking attrs).
+            if hasattr(config, "is_custom") and config.is_custom is True:
+                continue
+
             if restriction_service:
                 allowed = restriction_service.is_allowed(self.get_provider_type(), model_name)
 
@@ -255,24 +209,37 @@ class OpenRouterProvider(OpenAICompatibleProvider):
             unique=unique,
         )
 
-    def get_model_configurations(self) -> dict[str, ModelCapabilities]:
-        """Get model configurations from the registry.
+    # ------------------------------------------------------------------
+    # Registry helpers
+    # ------------------------------------------------------------------
 
-        For OpenRouter, we convert registry configurations to ModelCapabilities objects.
+    def _resolve_model_name(self, model_name: str) -> str:
+        """Resolve aliases defined in the OpenRouter registry."""
 
-        Returns:
-            Dictionary mapping model names to their ModelCapabilities objects
-        """
-        configs = {}
+        config = self._registry.resolve(model_name)
+        if config:
+            if config.model_name != model_name:
+                logging.info(f"Resolved model alias '{model_name}' to '{config.model_name}'")
+            return config.model_name
 
-        if self._registry:
-            # Get all models from registry
-            for model_name in self._registry.list_models():
-                # Only include models that this provider validates
-                if self.validate_model_name(model_name):
-                    config = self._registry.resolve(model_name)
-                    if config and not config.is_custom:  # Only OpenRouter models, not custom ones
-                        # Use ModelCapabilities directly from registry
-                        configs[model_name] = config
+        logging.debug(f"Model '{model_name}' not found in registry, using as-is")
+        return model_name
 
-        return configs
+    def get_all_model_capabilities(self) -> dict[str, ModelCapabilities]:
+        """Expose registry-backed OpenRouter capabilities."""
+
+        if not self._registry:
+            return {}
+
+        capabilities: dict[str, ModelCapabilities] = {}
+        for model_name in self._registry.list_models():
+            config = self._registry.resolve(model_name)
+            if not config:
+                continue
+
+            # See note in list_models: respect the CustomProvider boundary.
+            if hasattr(config, "is_custom") and config.is_custom is True:
+                continue
+
+            capabilities[model_name] = config
+        return capabilities
diff --git a/providers/registry.py b/providers/registry.py
index 917fd37..6f412ff 100644
--- a/providers/registry.py
+++ b/providers/registry.py
@@ -64,6 +64,8 @@ class ModelProviderRegistry:
         """
         instance = cls()
         instance._providers[provider_type] = provider_class
+        # Invalidate any cached instance so subsequent lookups use the new registration
+        instance._initialized_providers.pop(provider_type, None)
 
     @classmethod
     def get_provider(cls, provider_type: ProviderType, force_new: bool = False) -> Optional[ModelProvider]:
diff --git a/providers/xai.py b/providers/xai.py
index a9b2387..c03bc57 100644
--- a/providers/xai.py
+++ b/providers/xai.py
@@ -85,46 +85,10 @@ class XAIModelProvider(OpenAICompatibleProvider):
         kwargs.setdefault("base_url", "https://api.x.ai/v1")
         super().__init__(api_key, **kwargs)
 
-    def get_capabilities(self, model_name: str) -> ModelCapabilities:
-        """Get capabilities for a specific X.AI model."""
-        # Resolve shorthand
-        resolved_name = self._resolve_model_name(model_name)
-
-        if resolved_name not in self.MODEL_CAPABILITIES:
-            raise ValueError(f"Unsupported X.AI model: {model_name}")
-
-        # Check if model is allowed by restrictions
-        from utils.model_restrictions import get_restriction_service
-
-        restriction_service = get_restriction_service()
-        if not restriction_service.is_allowed(ProviderType.XAI, resolved_name, model_name):
-            raise ValueError(f"X.AI model '{model_name}' is not allowed by restriction policy.")
-
-        # Return the ModelCapabilities object directly from MODEL_CAPABILITIES
-        return self.MODEL_CAPABILITIES[resolved_name]
-
     def get_provider_type(self) -> ProviderType:
         """Get the provider type."""
         return ProviderType.XAI
 
-    def validate_model_name(self, model_name: str) -> bool:
-        """Validate if the model name is supported and allowed."""
-        resolved_name = self._resolve_model_name(model_name)
-
-        # First check if model is supported
-        if resolved_name not in self.MODEL_CAPABILITIES:
-            return False
-
-        # Then check if model is allowed by restrictions
-        from utils.model_restrictions import get_restriction_service
-
-        restriction_service = get_restriction_service()
-        if not restriction_service.is_allowed(ProviderType.XAI, resolved_name, model_name):
-            logger.debug(f"X.AI model '{model_name}' -> '{resolved_name}' blocked by restrictions")
-            return False
-
-        return True
-
     def generate_content(
         self,
         prompt: str,
diff --git a/tests/test_custom_provider.py b/tests/test_custom_provider.py
index 4c300f9..4f7ca30 100644
--- a/tests/test_custom_provider.py
+++ b/tests/test_custom_provider.py
@@ -54,11 +54,9 @@ class TestCustomProvider:
 
             provider = CustomProvider(api_key="test-key", base_url="http://localhost:11434/v1")
 
-            # Test with a model that should be in the registry (OpenRouter model)
-            capabilities = provider.get_capabilities("o3")  # o3 is an OpenRouter model
-
-            assert capabilities.provider == ProviderType.OPENROUTER  # o3 is an OpenRouter model (is_custom=false)
-            assert capabilities.context_window > 0
+            # OpenRouter-backed models should be handled by the OpenRouter provider
+            with pytest.raises(ValueError):
+                provider.get_capabilities("o3")
 
             # Test with a custom model (is_custom=true)
             capabilities = provider.get_capabilities("local-llama")
@@ -168,7 +166,13 @@ class TestCustomProviderRegistration:
             return CustomProvider(api_key="", base_url="http://localhost:11434/v1")
 
         with patch.dict(
-            os.environ, {"OPENROUTER_API_KEY": "test-openrouter-key", "CUSTOM_API_PLACEHOLDER": "configured"}
+            os.environ,
+            {
+                "OPENROUTER_API_KEY": "test-openrouter-key",
+                "CUSTOM_API_PLACEHOLDER": "configured",
+                "OPENROUTER_ALLOWED_MODELS": "llama,anthropic/claude-opus-4.1",
+            },
+            clear=True,
         ):
             # Register both providers
             ModelProviderRegistry.register_provider(ProviderType.OPENROUTER, OpenRouterProvider)
@@ -195,18 +199,22 @@ class TestCustomProviderRegistration:
             return CustomProvider(api_key="", base_url="http://localhost:11434/v1")
 
         with patch.dict(
-            os.environ, {"OPENROUTER_API_KEY": "test-openrouter-key", "CUSTOM_API_PLACEHOLDER": "configured"}
+            os.environ,
+            {
+                "OPENROUTER_API_KEY": "test-openrouter-key",
+                "CUSTOM_API_PLACEHOLDER": "configured",
+                "OPENROUTER_ALLOWED_MODELS": "",
+            },
+            clear=True,
         ):
-            # Register OpenRouter first (higher priority)
-            ModelProviderRegistry.register_provider(ProviderType.OPENROUTER, OpenRouterProvider)
-            ModelProviderRegistry.register_provider(ProviderType.CUSTOM, custom_provider_factory)
+            import utils.model_restrictions
 
-            # Test model resolution - OpenRouter should win for shared aliases
-            provider_for_model = ModelProviderRegistry.get_provider_for_model("llama")
+            utils.model_restrictions._restriction_service = None
+            custom_provider = custom_provider_factory()
+            openrouter_provider = OpenRouterProvider(api_key="test-openrouter-key")
 
-            # OpenRouter should be selected first due to registration order
-            assert provider_for_model is not None
-            # The exact provider type depends on which validates the model first
+            assert not custom_provider.validate_model_name("llama")
+            assert openrouter_provider.validate_model_name("llama")
 
 
 class TestConfigureProvidersFunction:
diff --git a/tests/test_dial_provider.py b/tests/test_dial_provider.py
index 9062a18..6c6f6a7 100644
--- a/tests/test_dial_provider.py
+++ b/tests/test_dial_provider.py
@@ -121,7 +121,7 @@ class TestDIALProvider:
         """Test that get_capabilities raises for invalid models."""
         provider = DIALModelProvider("test-key")
 
-        with pytest.raises(ValueError, match="Unsupported DIAL model"):
+        with pytest.raises(ValueError, match="Unsupported model 'invalid-model' for provider dial"):
             provider.get_capabilities("invalid-model")
 
     @patch("utils.model_restrictions.get_restriction_service")
diff --git a/tests/test_model_restrictions.py b/tests/test_model_restrictions.py
index 8aaf620..4277463 100644
--- a/tests/test_model_restrictions.py
+++ b/tests/test_model_restrictions.py
@@ -356,15 +356,13 @@ class TestCustomProviderOpenRouterRestrictions:
 
         provider = CustomProvider(base_url="http://test.com/v1")
 
-        # For OpenRouter models, get_capabilities should still work but mark them as OPENROUTER
-        # This tests the capabilities lookup, not validation
-        capabilities = provider.get_capabilities("opus")
-        assert capabilities.provider == ProviderType.OPENROUTER
+        # For OpenRouter models, CustomProvider should defer by raising
+        with pytest.raises(ValueError):
+            provider.get_capabilities("opus")
 
-        # Should raise for disallowed OpenRouter model
-        with pytest.raises(ValueError) as exc_info:
+        # Should raise for disallowed OpenRouter model (still defers)
+        with pytest.raises(ValueError):
             provider.get_capabilities("haiku")
-        assert "not allowed by restriction policy" in str(exc_info.value)
 
         # Should still work for custom models (is_custom=true)
         capabilities = provider.get_capabilities("local-llama")
diff --git a/tests/test_xai_provider.py b/tests/test_xai_provider.py
index f3e3a76..392be5b 100644
--- a/tests/test_xai_provider.py
+++ b/tests/test_xai_provider.py
@@ -141,7 +141,7 @@ class TestXAIProvider:
         """Test error handling for unsupported models."""
         provider = XAIModelProvider("test-key")
 
-        with pytest.raises(ValueError, match="Unsupported X.AI model"):
+        with pytest.raises(ValueError, match="Unsupported model 'invalid-model' for provider xai"):
             provider.get_capabilities("invalid-model")
 
     def test_extended_thinking_flags(self):
diff --git a/tools/listmodels.py b/tools/listmodels.py
index 7bde7f2..18e94aa 100644
--- a/tools/listmodels.py
+++ b/tools/listmodels.py
@@ -105,13 +105,11 @@ class ListModelsTool(BaseTool):
                 output_lines.append("**Status**: Configured and available")
                 output_lines.append("\n**Models**:")
 
-                # Get models from the provider's model configurations
-                for model_name, capabilities in provider.get_model_configurations().items():
-                    # Get description and context from the ModelCapabilities object
+                aliases = []
+                for model_name, capabilities in provider.get_all_model_capabilities().items():
                     description = capabilities.description or "No description available"
                     context_window = capabilities.context_window
 
-                    # Format context window
                     if context_window >= 1_000_000:
                         context_str = f"{context_window // 1_000_000}M context"
                     elif context_window >= 1_000:
@@ -120,31 +118,15 @@ class ListModelsTool(BaseTool):
                         context_str = f"{context_window} context" if context_window > 0 else "unknown context"
 
                     output_lines.append(f"- `{model_name}` - {context_str}")
+                    output_lines.append(f"  - {description}")
 
-                    # Extract key capability from description
-                    if "Ultra-fast" in description:
-                        output_lines.append("  - Fast processing, quick iterations")
-                    elif "Deep reasoning" in description:
-                        output_lines.append("  - Extended reasoning with thinking mode")
-                    elif "Strong reasoning" in description:
-                        output_lines.append("  - Logical problems, systematic analysis")
-                    elif "EXTREMELY EXPENSIVE" in description:
-                        output_lines.append("  - ⚠️ Professional grade (very expensive)")
-                    elif "Advanced reasoning" in description:
-                        output_lines.append("  - Advanced reasoning and complex analysis")
-
-                # Show aliases for this provider
-                aliases = []
-                for model_name, capabilities in provider.get_model_configurations().items():
-                    if capabilities.aliases:
-                        for alias in capabilities.aliases:
-                            # Skip aliases that are the same as the model name to avoid duplicates
-                            if alias != model_name:
-                                aliases.append(f"- `{alias}` → `{model_name}`")
+                    for alias in capabilities.aliases or []:
+                        if alias != model_name:
+                            aliases.append(f"- `{alias}` → `{model_name}`")
 
                 if aliases:
                     output_lines.append("\n**Aliases**:")
-                    output_lines.extend(sorted(aliases))  # Sort for consistent output
+                    output_lines.extend(sorted(aliases))
             else:
                 output_lines.append(f"**Status**: Not configured (set {info['env_key']})")