diff --git a/tools/make/linter.mk b/tools/make/linter.mk
index a252d4ac4..23548b361 100644
--- a/tools/make/linter.mk
+++ b/tools/make/linter.mk
@@ -4,14 +4,6 @@
 
 ##@ Linter
 
-docs-lint: docs-install ## Lint documentation in website/
-	@$(LOG_TARGET)
-	cd website && npm run lint
-
-docs-lint-fix: docs-install ## Auto-fix documentation lint issues in website/
-	@$(LOG_TARGET)
-	cd website && npm run lint:fix
-
 markdown-lint: ## Lint all markdown files in the project
 	@$(LOG_TARGET)
 	markdownlint -c tools/linter/markdown/markdownlint.yaml "**/*.md" \
diff --git a/website/docs/installation/configuration.md b/website/docs/installation/configuration.md
index 18742ee35..03b5b5ccc 100644
--- a/website/docs/installation/configuration.md
+++ b/website/docs/installation/configuration.md
@@ -15,14 +15,14 @@ The configuration file is located at `config/config.yaml`. Here's the structure
 
 # BERT model for semantic similarity
 bert_model:
-  model_id: sentence-transformers/all-MiniLM-L12-v2
+  model_id: models/all-MiniLM-L12-v2
   threshold: 0.6
   use_cpu: true
 
 # Semantic caching
 semantic_cache:
   backend_type: "memory"  # Options: "memory" or "milvus"
-  enabled: false
+  enabled: true
   similarity_threshold: 0.8  # Global default threshold
   max_entries: 1000
   ttl_seconds: 3600
@@ -30,7 +30,7 @@ semantic_cache:
 
 # Tool auto-selection
 tools:
-  enabled: false
+  enabled: true
   top_k: 3
   similarity_threshold: 0.2
   tools_db_path: "config/tools_db.json"
@@ -38,7 +38,7 @@ tools:
 
 # Jailbreak protection
 prompt_guard:
-  enabled: false  # Global default - can be overridden per category
+  enabled: true  # Global default - can be overridden per category
   use_modernbert: true
   model_id: "models/jailbreak_classifier_modernbert-base_model"
   threshold: 0.7
@@ -330,31 +330,23 @@ categories:
 Configure how different models handle reasoning mode syntax. This allows you to add new models without code changes:
 
 ```yaml
-# Model reasoning configurations - define how different models handle reasoning syntax
-model_reasoning_configs:
-  - name: "deepseek"
-    patterns: ["deepseek", "ds-", "ds_", "ds:", "ds "]
-    reasoning_syntax:
-      type: "chat_template_kwargs"
-      parameter: "thinking"
-
-  - name: "qwen3"
-    patterns: ["qwen3"]
-    reasoning_syntax:
-      type: "chat_template_kwargs"
-      parameter: "enable_thinking"
-
-  - name: "gpt-oss"
-    patterns: ["gpt-oss", "gpt_oss"]
-    reasoning_syntax:
-      type: "reasoning_effort"
-      parameter: "reasoning_effort"
-
-  - name: "gpt"
-    patterns: ["gpt"]
-    reasoning_syntax:
-      type: "reasoning_effort"
-      parameter: "reasoning_effort"
+# Reasoning family configurations - define how different model families handle reasoning syntax
+reasoning_families:
+  deepseek:
+    type: "chat_template_kwargs"
+    parameter: "thinking"
+
+  qwen3:
+    type: "chat_template_kwargs"
+    parameter: "enable_thinking"
+
+  gpt-oss:
+    type: "reasoning_effort"
+    parameter: "reasoning_effort"
+
+  gpt:
+    type: "reasoning_effort"
+    parameter: "reasoning_effort"
 
 # Global default reasoning effort level (when not specified per category)
 default_reasoning_effort: "medium"
@@ -364,46 +356,40 @@ default_reasoning_effort: "medium"
 
 **Configuration Structure:**
 
-- `name`: A unique identifier for the model family
-- `patterns`: Array of patterns to match against model names
-- `reasoning_syntax.type`: How the model expects reasoning mode to be specified
+- `name`: A unique identifier for the model family (e.g., "deepseek", "qwen3")
+- `type`: How the model expects reasoning mode to be specified
   - `"chat_template_kwargs"`: Use chat template parameters (for models like DeepSeek, Qwen3)
   - `"reasoning_effort"`: Use OpenAI-compatible reasoning_effort field (for GPT models)
-- `reasoning_syntax.parameter`: The specific parameter name the model uses
+- `parameter`: The specific parameter name the model uses
 
 **Pattern Matching:**
-The system supports both simple string patterns and regular expressions for flexible model matching:
+The system supports model family names that are matched against model configurations:
 
-- **Simple string matches**: `"deepseek"` matches any model containing "deepseek"
-- **Prefix patterns**: `"ds-"` matches models starting with "ds-" or exactly "ds"
-- **Regular expressions**: `"^gpt-4.*"` matches models starting with "gpt-4"
-- **Wildcard**: `"*"` matches all models (use for fallback configurations)
-- **Multiple patterns**: `["deepseek", "ds-", "^phi.*"]` matches any of these patterns
+- **Family names**: `"deepseek"`, `"qwen3"`, `"gpt-oss"`, `"gpt"`
+- Models are assigned to families via `model_config[model_name].reasoning_family`
+- Unknown models will have no reasoning fields applied when reasoning mode is enabled
 
-**Regex Pattern Examples:**
+**Adding New Models:**
+To support a new model family (e.g., Claude), simply add a new configuration:
 
 ```yaml
-patterns:
-  - "^gpt-4.*"        # Models starting with "gpt-4"
-  - ".*-instruct$"    # Models ending with "-instruct"
-  - "phi[0-9]+"       # Models like "phi3", "phi4", etc.
-  - "^(llama|mistral)" # Models starting with "llama" or "mistral"
+reasoning_families:
+  claude:
+    type: "chat_template_kwargs"
+    parameter: "enable_reasoning"
 ```
 
-**Adding New Models:**
-To support a new model family (e.g., Claude), simply add a new configuration:
+Then assign your model to the family:
 
 ```yaml
-model_reasoning_configs:
-  - name: "claude"
-    patterns: ["claude"]
-    reasoning_syntax:
-      type: "chat_template_kwargs"
-      parameter: "enable_reasoning"
+model_config:
+  "claude-3-opus":
+    reasoning_family: "claude"
+    preferred_endpoints: ["endpoint1"]
 ```
 
 **Unknown Models:**
-Models that don't match any configured pattern will have no reasoning fields applied when reasoning mode is enabled. This prevents issues with models that don't support reasoning syntax.
+Models that don't have a `reasoning_family` assigned will have no reasoning fields applied when reasoning mode is enabled. This prevents issues with models that don't support reasoning syntax.
 
 **Default Reasoning Effort:**
 Set the global default reasoning effort level used when categories don't specify their own effort level:
@@ -505,7 +491,7 @@ tools:
 
 # BERT Model for Similarity
 bert_model:
-  model_id: sentence-transformers/all-MiniLM-L12-v2
+  model_id: models/all-MiniLM-L12-v2
   threshold: 0.6                  # Similarity threshold
   use_cpu: true                   # CPU-only inference
 
@@ -974,27 +960,31 @@ make test-prompt-guard               # Jailbreak protection
 
 **Model not getting reasoning fields:**
 
-- Check that the model name matches a pattern in `model_reasoning_configs`
-- Verify the pattern syntax (exact matches vs prefixes)
-- Unknown models will have no reasoning fields applied (this is by design)
+- Check that the model has a `reasoning_family` assigned in `model_config`
+- Verify the reasoning family exists in `reasoning_families` configuration
+- Unknown models (without `reasoning_family`) will have no reasoning fields applied (this is by design)
 
 **Wrong reasoning syntax applied:**
 
-- Ensure the `reasoning_syntax.type` matches your model's expected format
-- Check the `reasoning_syntax.parameter` name is correct
+- Ensure the `type` field in `reasoning_families` matches your model's expected format
+- Check the `parameter` name is correct for your model family
 - DeepSeek models typically use `chat_template_kwargs` with `"thinking"`
 - GPT models typically use `reasoning_effort`
 
 **Adding support for new models:**
 
 ```yaml
-# Add a new model configuration
-model_reasoning_configs:
-  - name: "my-new-model"
-    patterns: ["my-model"]
-    reasoning_syntax:
-      type: "chat_template_kwargs"  # or "reasoning_effort"
-      parameter: "custom_parameter"
+# Add a new reasoning family
+reasoning_families:
+  my-new-family:
+    type: "chat_template_kwargs"  # or "reasoning_effort"
+    parameter: "custom_parameter"
+
+# Assign model to the family
+model_config:
+  "my-model":
+    reasoning_family: "my-new-family"
+    preferred_endpoints: ["endpoint1"]
 ```
 
 **Testing model reasoning configuration:**
diff --git a/website/docs/overview/categories/configuration.md b/website/docs/overview/categories/configuration.md
index 6ed2ad3cc..b985d59c8 100644
--- a/website/docs/overview/categories/configuration.md
+++ b/website/docs/overview/categories/configuration.md
@@ -13,12 +13,10 @@ categories:
   - name: "category_name"
     description: "Optional description"
     system_prompt: "Category-specific system prompt"
-    use_reasoning: true|false
-    reasoning_description: "Why reasoning is needed"
-    reasoning_effort: "low|medium|high"
     model_scores:
       - model: "model_name"
         score: 0.0-1.0
+        use_reasoning: true|false  # Per-model reasoning setting
 ```
 
 ## Configuration Parameters
@@ -148,58 +146,42 @@ categories:
 - **0.6-0.8**: Standard categories (general queries)
 - **0.4-0.6**: Technical categories (code generation, development tools)
 
-#### `use_reasoning` (Required)
-
-- **Type**: Boolean
-- **Description**: Whether to enable reasoning mode for this category
-- **Default**: `false`
-- **Impact**: Enables step-by-step problem solving
-
-```yaml
-categories:
-  - name: "math"
-    use_reasoning: true  # Enable reasoning for math problems
-```
+### Model Scoring
 
-#### `reasoning_description` (Optional)
+#### `model_scores` (Required)
 
-- **Type**: String
-- **Description**: Explanation of why reasoning is needed
-- **Purpose**: Documentation and model context
-- **Best Practice**: Provide clear justification
+- **Type**: Array of model-score pairs
+- **Description**: Defines model preferences and reasoning settings for this category
+- **Purpose**: Intelligent model selection based on domain expertise
 
 ```yaml
 categories:
-  - name: "chemistry"
-    use_reasoning: true
-    reasoning_description: "Chemical reactions require systematic analysis"
+  - name: "math"
+    model_scores:
+      - model: "phi4"
+        score: 1.0      # Highest preference
+        use_reasoning: true  # Enable reasoning for this model on math
+      - model: "mistral-small3.1"
+        score: 0.8
+        use_reasoning: false  # No reasoning for this model
 ```
 
-#### `reasoning_effort` (Optional)
+#### `use_reasoning` (Model-Level, Required)
 
-- **Type**: String
-- **Valid Values**: `"low"`, `"medium"`, `"high"`
-- **Default**: `"medium"`
-- **Description**: Controls the depth of reasoning
+- **Type**: Boolean
+- **Location**: Within each `model_scores` entry
+- **Description**: Whether to enable reasoning mode for this specific model in this category
+- **Default**: `false`
+- **Impact**: Enables step-by-step problem solving for that model
 
 ```yaml
 categories:
   - name: "math"
-    use_reasoning: true
-    reasoning_effort: "high"  # Maximum reasoning depth
+    model_scores:
+      - model: "phi4"
+        score: 1.0
+        use_reasoning: true  # Enable reasoning for phi4 on math problems
 ```
-
-**Reasoning Effort Levels**:
-
-- **Low**: Basic step-by-step thinking (1-3 steps)
-- **Medium**: Moderate analysis (3-7 steps)
-- **High**: Deep reasoning (7-15 steps)
-
-### Model Scoring
-
-#### `model_scores` (Required)
-
-- **Type**: Array of model-score pairs
 - **Description**: Defines model preferences for this category
 - **Purpose**: Intelligent model selection based on domain expertise
 
@@ -231,16 +213,16 @@ categories:
 categories:
   - name: "math"
     description: "Mathematical problems requiring step-by-step reasoning"
-    use_reasoning: true
-    reasoning_description: "Mathematical problems require systematic analysis"
-    reasoning_effort: "high"
     model_scores:
       - model: "phi4"
         score: 1.0
+        use_reasoning: true  # Enable reasoning for phi4 on math
       - model: "mistral-small3.1"
         score: 0.8
+        use_reasoning: true  # Enable reasoning for mistral on math
       - model: "gemma3:27b"
         score: 0.6
+        use_reasoning: false  # No reasoning for gemma on math
 ```
 
 ### Example 2: Professional Category (Reasoning Disabled)
@@ -249,16 +231,16 @@ categories:
 categories:
   - name: "business"
     description: "Business strategy and management discussions"
-    use_reasoning: false
-    reasoning_description: "Business content is typically conversational"
-    reasoning_effort: "low"
     model_scores:
       - model: "phi4"
         score: 0.8
+        use_reasoning: false  # Business doesn't need reasoning
       - model: "gemma3:27b"
         score: 0.4
+        use_reasoning: false
       - model: "mistral-small3.1"
         score: 0.2
+        use_reasoning: false
 ```
 
 ### Example 3: Security-Focused Configuration (Jailbreak Protection)
@@ -270,36 +252,38 @@ categories:
     description: "Customer support and general inquiries"
     jailbreak_enabled: true  # Strict jailbreak protection
     jailbreak_threshold: 0.9  # High threshold for public-facing
-    use_reasoning: false
     model_scores:
       - model: "phi4"
         score: 0.9
+        use_reasoning: false
       - model: "mistral-small3.1"
         score: 0.7
+        use_reasoning: false
 
   # Technical category with relaxed threshold
   - name: "code_generation"
     description: "Code generation for developers"
     jailbreak_enabled: true  # Keep enabled
     jailbreak_threshold: 0.5  # Lower threshold to reduce false positives on code
-    use_reasoning: true
-    reasoning_effort: "medium"
     model_scores:
       - model: "gemma3:27b"
         score: 0.9
+        use_reasoning: true  # Enable reasoning for code
       - model: "phi4"
         score: 0.7
+        use_reasoning: true
 
   # General category using global default
   - name: "general"
     description: "General queries"
     # jailbreak_enabled not specified - inherits from global prompt_guard.enabled
-    use_reasoning: false
     model_scores:
       - model: "phi4"
         score: 0.6
+        use_reasoning: false
       - model: "mistral-small3.1"
         score: 0.6
+        use_reasoning: false
 ```
 
 ### Example 4: Multi-Category Configuration
@@ -308,51 +292,53 @@ categories:
 categories:
   # Technical categories with reasoning
   - name: "computer science"
-    use_reasoning: true
-    reasoning_description: "Programming requires logical analysis"
-    reasoning_effort: "medium"
     model_scores:
       - model: "gemma3:27b"
         score: 0.6
+        use_reasoning: true  # Enable reasoning for coding
       - model: "mistral-small3.1"
         score: 0.6
+        use_reasoning: true
       - model: "phi4"
         score: 0.0
+        use_reasoning: false
 
   - name: "physics"
-    use_reasoning: true
-    reasoning_description: "Physics concepts need systematic thinking"
-    reasoning_effort: "medium"
     model_scores:
       - model: "gemma3:27b"
         score: 0.4
+        use_reasoning: true  # Enable reasoning for physics
       - model: "phi4"
         score: 0.4
+        use_reasoning: true
       - model: "mistral-small3.1"
         score: 0.4
+        use_reasoning: true
 
   # General categories without reasoning
   - name: "history"
-    use_reasoning: false
-    reasoning_description: "Historical content is narrative-based"
     model_scores:
       - model: "mistral-small3.1"
         score: 0.8
+        use_reasoning: false  # History is narrative-based
       - model: "phi4"
         score: 0.6
+        use_reasoning: false
       - model: "gemma3:27b"
         score: 0.4
+        use_reasoning: false
 
   - name: "other"
-    use_reasoning: false
-    reasoning_description: "General content doesn't require reasoning"
     model_scores:
       - model: "gemma3:27b"
         score: 0.8
+        use_reasoning: false  # General content doesn't need reasoning
       - model: "phi4"
         score: 0.6
+        use_reasoning: false
       - model: "mistral-small3.1"
         score: 0.6
+        use_reasoning: false
 ```
 
 ## Configuration Best Practices
@@ -393,24 +379,36 @@ categories:
 # Reasoning recommended for:
 categories:
   - name: "math"
-    use_reasoning: true
-    reasoning_effort: "high"
+    model_scores:
+      - model: "phi4"
+        score: 1.0
+        use_reasoning: true  # Enable reasoning for math
 
   - name: "computer science"
-    use_reasoning: true
-    reasoning_effort: "medium"
+    model_scores:
+      - model: "gemma3:27b"
+        score: 0.6
+        use_reasoning: true  # Enable reasoning for coding
 
   - name: "chemistry"
-    use_reasoning: true
-    reasoning_effort: "high"
+    model_scores:
+      - model: "phi4"
+        score: 0.6
+        use_reasoning: true  # Enable reasoning for chemistry
 
 # Reasoning not needed for:
 categories:
   - name: "business"
-    use_reasoning: false
+    model_scores:
+      - model: "phi4"
+        score: 0.7
+        use_reasoning: false  # Business doesn't need reasoning
 
   - name: "history"
-    use_reasoning: false
+    model_scores:
+      - model: "mistral-small3.1"
+        score: 0.7
+        use_reasoning: false  # History is narrative
 ```
 
 ### 3. Performance Tuning
@@ -421,24 +419,24 @@ categories:
 # High-performance setup (lower latency)
 categories:
   - name: "math"
-    use_reasoning: true
-    reasoning_effort: "medium"  # Reduced from "high"
     model_scores:
       - model: "phi4"
         score: 1.0
+        use_reasoning: false  # Disable reasoning for speed
       - model: "mistral-small3.1"
         score: 0.6  # Larger gap for faster selection
+        use_reasoning: false
 
 # High-accuracy setup (higher latency)
 categories:
   - name: "math"
-    use_reasoning: true
-    reasoning_effort: "high"    # Maximum reasoning
     model_scores:
       - model: "phi4"
         score: 1.0
+        use_reasoning: true  # Enable reasoning for accuracy
       - model: "mistral-small3.1"
         score: 0.9  # Close scores for better fallback
+        use_reasoning: true
 ```
 
 ## Classifier Configuration
@@ -569,11 +567,10 @@ routing_rules:
 categories:
   - name: "math"
     system_prompt: "You are a mathematics expert. Provide step-by-step solutions."
-    use_reasoning: true
-    reasoning_effort: "high"
     model_scores:
       - model: "phi4"
         score: 1.0
+        use_reasoning: true  # Per-model reasoning setting
 ```
 
 ## Complete Configuration Example
@@ -583,31 +580,26 @@ categories:
   - name: "math"
     description: "Mathematical problems and calculations"
     system_prompt: "You are a mathematics expert. Provide step-by-step solutions, show your work clearly, and explain mathematical concepts in an understandable way."
-    use_reasoning: true
-    reasoning_effort: "high"
     model_scores:
       - model: "openai/gpt-oss-20b"
         score: 0.9
-        use_reasoning: true
+        use_reasoning: true  # Enable reasoning for this model
 
   - name: "computer science"
     description: "Programming and software engineering"
     system_prompt: "You are a computer science expert. Provide clear, practical solutions with code examples when helpful."
-    use_reasoning: true
-    reasoning_effort: "medium"
     model_scores:
       - model: "openai/gpt-oss-20b"
         score: 0.8
-        use_reasoning: true
+        use_reasoning: true  # Enable reasoning for coding
 
   - name: "business"
     description: "Business strategy and management"
     system_prompt: "You are a professional business consultant. Provide practical, actionable advice."
-    use_reasoning: false
     model_scores:
       - model: "openai/gpt-oss-20b"
         score: 0.7
-        use_reasoning: false
+        use_reasoning: false  # Business doesn't need reasoning
 ```
 
 ## Next Steps
diff --git a/website/docs/overview/categories/technical-details.md b/website/docs/overview/categories/technical-details.md
index 54c169dc8..3e3264266 100644
--- a/website/docs/overview/categories/technical-details.md
+++ b/website/docs/overview/categories/technical-details.md
@@ -431,10 +431,10 @@ func (c *Classifier) HealthCheck() error {
    ```yaml
    categories:
      - name: "new_category"
-       use_reasoning: false
        model_scores:
          - model: "best-model-for-category"
            score: 1.0
+           use_reasoning: false  # Set per-model reasoning
    ```
 
 ### Custom Classification Models
diff --git a/website/docs/proposals/nvidia-dynamo-integration.md b/website/docs/proposals/nvidia-dynamo-integration.md
index a6933ec37..281d65d1e 100644
--- a/website/docs/proposals/nvidia-dynamo-integration.md
+++ b/website/docs/proposals/nvidia-dynamo-integration.md
@@ -336,7 +336,7 @@ The Semantic Router leverages **four specialized deep learning models** for inte
 
 ```yaml
 bert_model:
-  model_id: sentence-transformers/all-MiniLM-L12-v2
+  model_id: models/all-MiniLM-L12-v2
   threshold: 0.6
   use_cpu: true
 ```
diff --git a/website/docs/training/model-performance-eval.md b/website/docs/training/model-performance-eval.md
index 529c54815..2f9ef86dd 100644
--- a/website/docs/training/model-performance-eval.md
+++ b/website/docs/training/model-performance-eval.md
@@ -271,7 +271,7 @@ see more about config at [configuration](https://vllm-semantic-router.com/docs/i
 
 ```yaml
 bert_model:
-  model_id: sentence-transformers/all-MiniLM-L12-v2
+  model_id: models/all-MiniLM-L12-v2
   threshold: 0.6
   use_cpu: true
 semantic_cache:
@@ -310,35 +310,32 @@ classifier:
     pii_mapping_path: models/pii_classifier_modernbert-base_presidio_token_model/pii_type_mapping.json
 categories:
 - name: business
-  use_reasoning: false
-  reasoning_description: Business content is typically conversational
-  reasoning_effort: low
   model_scores:
   - model: phi4
     score: 0.2
+    use_reasoning: false  # Business doesn't need reasoning
   - model: qwen3-0.6B
     score: 0.0
+    use_reasoning: false
 - name: law
-  use_reasoning: false
-  reasoning_description: Legal content is typically explanatory
-  reasoning_effort: medium
   model_scores:
   - model: phi4
     score: 0.8
+    use_reasoning: false  # Legal content is explanatory
   - model: qwen3-0.6B
     score: 0.2
+    use_reasoning: false
 
 # Ignore some categories here
 
 - name: engineering
-  use_reasoning: true
-  reasoning_description: Engineering problems require systematic problem-solving
-  reasoning_effort: high
   model_scores:
   - model: phi4
     score: 0.6
+    use_reasoning: true  # Engineering requires problem-solving
   - model: qwen3-0.6B
     score: 0.2
+    use_reasoning: true
 default_reasoning_effort: medium
 default_model: phi4
 ```
diff --git a/website/docs/tutorials/intelligent-route/reasoning.md b/website/docs/tutorials/intelligent-route/reasoning.md
index 29b4774cb..719bbb98c 100644
--- a/website/docs/tutorials/intelligent-route/reasoning.md
+++ b/website/docs/tutorials/intelligent-route/reasoning.md
@@ -66,19 +66,19 @@ model_config:
     reasoning_family: "gpt-oss"
     preferred_endpoints: ["endpoint1"]
 
-# Categories: which kinds of queries require reasoning and at what effort
+# Categories: which models to use for each type of query, with per-model reasoning settings
 categories:
 - name: math
-  use_reasoning: true
-  reasoning_effort: high  # overrides default_reasoning_effort
-  reasoning_description: "Mathematical problems require step-by-step reasoning"
   model_scores:
   - model: openai/gpt-oss-20b
     score: 1.0
+    use_reasoning: true  # Enable reasoning for this model on math
   - model: deepseek-v31
     score: 0.8
+    use_reasoning: true
   - model: qwen3-30b
     score: 0.8
+    use_reasoning: true
 
 
 # A safe default when no category is confidently selected
@@ -87,11 +87,10 @@ default_model: qwen3-30b
 
 Notes
 
-- Reasoning is controlled by categories.use_reasoning and optionally categories.reasoning_effort.
-- A model only gets reasoning fields if it has a model_config.<MODEL>.reasoning_family that maps to a reasoning_families entry.
+- Reasoning is controlled per-model within `model_scores` using the `use_reasoning` field.
+- A model only gets reasoning fields if it has a model_config.<MODEL>.reasoning_family that maps to a reasoning_families entry.
 - DeepSeek/Qwen3 (chat_template_kwargs): the router injects chat_template_kwargs only when reasoning is enabled. When disabled, no chat_template_kwargs are added.
-- GPT/GPT-OSS (reasoning_effort): when reasoning is enabled, the router sets reasoning_effort based on the category (fallback to default_reasoning_effort). When reasoning is disabled, if the request already contains reasoning_effort and the model’s family type is reasoning_effort, the router preserves the original value; otherwise it is absent.
-- Category descriptions (for example, description and reasoning_description) are informational only today; they do not affect routing or classification.
+- GPT/GPT-OSS (reasoning_effort): when reasoning is enabled, the router sets reasoning_effort based on global `default_reasoning_effort`. When reasoning is disabled, if the request already contains reasoning_effort and the model's family type is reasoning_effort, the router preserves the original value; otherwise it is absent.
 - Categories must be from MMLU-Pro at the moment; avoid free-form categories like "general". If you want generic categories, consider opening an issue to map them to MMLU-Pro.
 
 2) Start the router