Add agent pipeline figure to model card

README.md

@@ -211,6 +211,12 @@ The trained adapter improves both levels over the direct Qwen3.6-35B-A3B baselin
 
 The trained+agents result uses this adapter as the Actor and combines it with a separate Simulator/Selector model. The agent is not a physical simulator and does not execute wet-lab actions. It samples candidate next actions or action sequences, checks symbolic protocol-state consistency, and selects the most consistent candidate.
 
+<p align="center">
+  <img src="assets/figure3_agent.png" alt="Actor-Simulator-Selector agent pipeline" width="100%">
+</p>
+
+The trained Actor reads the same task inputs used by the public datasets: multi-view asset images, historical actions, and candidate next actions for Level 1, or wet experiment context, constraints, available inputs, and an action pool for Level 2. The Simulator builds current and target symbolic protocol states and predicts candidate reagent/instrument state transitions. The Selector compares the candidate-state pairs and returns the selected action prediction, which is evaluated with Level 1 next-action accuracy or Level 2 AST-based action-sequence and parameter metrics.
+
 Agent setting: `Qwen3.6-35B-A3B(trained)` is used as Actor, and Gemini 3.1 Pro is used as Simulator/Selector. This Simulator/Selector choice is the current setting and has not been exhaustively ablated.
 
 ## 🚀 Quick Start