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-# ComfyUI-ConditioningEnhancer
-Post-encode refiner for CLIP/Qwen3-4B conditioning in ComfyUI (normalize, attention, MLP)
+## Capitan Conditioning Enhancer
+Lightweight post-processing node for Qwen3-4B conditioning in Z-Image Turbo workflows.
+Refines the 2560-dim CONDITIONING from native Qwen3-4B text encoder with:
+
+## Per-token normalization
+Optional 8-head self-attention
+2-layer MLP refiner (very wide hidden size supported)
+Positive/negative blend strength
+
+Improves coherence, detail retention, mood consistency, and prompt following — especially powerful when stacked (first node glues scene, second sharpens/details).
+Many users find this node so useful at low strength they remove CLIPAttentionMultiply entirely.
+## Installation
+extract zip in ComfyUI/custom_nodes 
+Or
+
+git clone https://github.com/capitan01R/ComfyUI-ConditioningEnhancer.git
+
+restart ComfyUI or reload custom nodes
+
+No dependencies.
+## Placement
+After CLIP Text Encode (Prompt) → before KSampler.
+![](images/node.png)
+
+### Parameters Explained
+
+| Parameter              | Type    | Default | Range             | What it does                                                                                       | Typical use / effect                                                                 |
+|------------------------|---------|---------|-------------------|----------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------|
+| enhance_strength       | FLOAT   | 0.0     | -2.0 → 2.0        | Positive: add refinement, Negative: subtract refinement (sharper, anti-smoothing)                | 0.00–0.15 = subtle polish<br>Negative = crisp/literal<br>>0.5 = high risk            |
+| normalize              | BOOLEAN | true    | true/false        | Per-token mean subtraction + unit variance normalization                                          | Almost always true — stability & cleaner generations                                 |
+| add_self_attention     | BOOLEAN | false   | true/false        | Light 8-head self-attention across tokens (distant prompt parts influence each other)            | true = better cohesion & complex scene unity<br>false = literal control              |
+| mlp_hidden_mult        | INT     | 2       | 1 → 100           | Hidden layer width multiplier for MLP (2560 → 2560×mult → 2560)                                  | 2–10 = balanced<br>20–50 = hyper-literal detail (recommended max)<br>60–100 = extreme (low strength only) |
+
+
+## MLP note — UI allows up to 100, but recommended max is 50. Higher rarely adds value and mostly increases artifact risk even at tiny strength (0.01–0.05).
+Recommended Starting Points
+Daily essential / stabilizer
+
+strength: 0.00–0.10
+normalize: true
+add_self_attention: true
+mlp_hidden_mult: 2–4
+
+Hyper-literal detail mode (stacked)
+
+First node: strength 0.05–0.10, normalize true, self-attn true, mult 2–4
+Second node: strength 0.05–0.15 (or -0.05 – -0.15), normalize true, self-attn false, mult 40–50
+
+Warnings
+High strength (>0.4) + high mlp_hidden_mult + self-attention → rainbow artifacts / noise likely.
+Very high mult (60+) needs extremely low strength (≤0.05).
+Always test same seed first. Negative strength + high mult usually safer than positive.