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tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory/agent_runs/gen_100_task_message.txt

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+=== Generation 100 Evaluation ===
+
+📁 File Locations:
+- Results directory: /home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441
+- Memory: $RESULTS_DIR/eval_agent_memory/EVAL_AGENTS.md
+- Auxiliary metrics: $RESULTS_DIR/eval_agent_memory/auxiliary_metrics.py
+- All generations: $RESULTS_DIR/gen_0/ through gen_100/
+- Each generation has: main.py and results/metrics.json
+- Current code: $RESULTS_DIR/gen_100/main.py
+- Current metrics: $RESULTS_DIR/gen_100/results/metrics.json
+- Toolbox public API: eval_agent/tool_box/api.py
+- Toolbox reference template: eval_agent/templates/auxiliary_metrics_template.py
+- Current score: 2.6357
+
+⚠️  PRIMARY EVALUATOR (FIXED - DO NOT MODIFY):
+- Path: /home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/evaluate_ori.py
+- This file defines the GROUND TRUTH evaluation metric
+- The primary score comes from this evaluator
+- You MUST NOT modify or replace this evaluator
+- You can READ it to understand what is being optimized
+- Your job is to create AUXILIARY metrics that complement it
+
+🎯 Generation-Specific Focus (follow system prompt for full policy):
+1. Analyze progress up to generation 100 and diagnose current bottlenecks.
+2. Update auxiliary_metrics.py with this generation's metric set.
+   - Keep evaluate_aux as the single entry point and return a flat metric dict.
+   - Smoke-test metric execution on current generation artifacts before finishing.
+3. Update EVAL_AGENTS.md for this generation's actions and rationale.
+
+Use toolbox public APIs when needed:
+- from eval_agent.tool_box import call_vision, call_tool
+- Do NOT import eval_agent/tool_box/_internal/*
+
+📈 Combined Score Trend (previous up to 10 generations):
+- gen_90: 0.0000 | gen_91: 2.6261 | gen_92: 0.0000 | gen_93: 0.0000 | gen_94: 2.6353 | gen_95: 0.0000 | gen_96: 0.0000 | gen_97: 2.5616 | gen_98: 0.0000 | gen_99: 0.0000
+- Net change (gen_90 -> gen_99): +0.0000
+
+🧭 Evolution Agent Strategy Context (from meta memory):
+- Source: /home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/meta_memory.json
+- Current recommendations used by evolution agent:
+  1.  **Recursive Lattice Pattern Generator**: Replace the hardcoded list of 8 patterns with a recursive function that generates all valid staggered row configurations for $N=26$ (specifically, compositions of 26 into 4 to 8 rows where adjacent row lengths differ by at most 1). The current manual list is too sparse to guarantee inclusion of the optimal "crystal" topology; exhaustive generation ensures the specific lattice structure required for the global maximum is present in the screening pool.
+  2.  **Strict Hard-Sphere Screening**: Refine the initial screening phase to optimize a *single scalar radius* $R$ (maximizing $R$ such that no overlap occurs) rather than using the current variable-radius optimization with soft penalties. This "Hard-Sphere" formulation is computationally faster and creates a clearer ranking of topological basins based on pure packing efficiency, filtering out suboptimal seeds more effectively before expensive relaxation begins.
+  3.  **Multi-Stream Basin Hopping**: Modify the solver to select the **top 3 distinct candidates** from the screening phase instead of just the single best one, and run the Basin Hopping procedure on all three (splitting the iteration budget if necessary). High-potential basins often score slightly lower initially due to imperfect geometry; pursuing multiple candidates prevents the algorithm from discarding the global optimum prematurely.
+  4.  **Coordinate Swap Mutation**: Introduce a "Swap" operator (e.g., with 10-15% probability) into the Basin Hopping loop that exchanges the center coordinates of a bottleneck circle (smallest radius) with a non-critical circle (largest radius). While the current "Pop" move relies on finding empty voids, a "Swap" allows the algorithm to reorganize fully jammed configurations where voids are non-existent, facilitating better radius equalization.
+  5.  **Two-Tier Optimization Intensity**: Implement a simplified stiffness ramp for the inner Basin Hopping loop (e.g., only 2 phases: $\mu=1000, 100000$) while retaining the robust 5-phase ramp for the initial screening and final polish. The current program runs the expensive 5-phase minimization at every step of the inner loop; reducing this overhead will prevent timeouts and allow for doubling the number of iterations (e.g., from 30 to 60) to explore the landscape more deeply.
+- Latest recommendation updates since previous refresh:
+  1.  **Recursive Lattice Pattern Generator**: Replace the hardcoded list of 8 patterns with a recursive function that generates all valid staggered row configurations for $N=26$ (specifically, compositions of 26 into 4 to 8 rows where adjacent row lengths differ by at most 1). The current manual list is too sparse to guarantee inclusion of the optimal "crystal" topology; exhaustive generation ensures the specific lattice structure required for the global maximum is present in the screening pool.
+  2.  **Strict Hard-Sphere Screening**: Refine the initial screening phase to optimize a *single scalar radius* $R$ (maximizing $R$ such that no overlap occurs) rather than using the current variable-radius optimization with soft penalties. This "Hard-Sphere" formulation is computationally faster and creates a clearer ranking of topological basins based on pure packing efficiency, filtering out suboptimal seeds more effectively before expensive relaxation begins.
+  3.  **Multi-Stream Basin Hopping**: Modify the solver to select the **top 3 distinct candidates** from the screening phase instead of just the single best one, and run the Basin Hopping procedure on all three (splitting the iteration budget if necessary). High-potential basins often score slightly lower initially due to imperfect geometry; pursuing multiple candidates prevents the algorithm from discarding the global optimum prematurely.

tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory/agent_runs/gen_112_result.json

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+{
+  "success": true,
+  "generation": 112,
+  "workspace": "/home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory",
+  "insights": [
+    "- REPLACE `aux_python_loc` -> `aux_normalized_min_radius` (Reason: Primary score is no longer 0.0000, so geometric metrics are relevant again. Reintroducing geometric metrics which were removed during previous timeout issues.)",
+    "- REPLACE `aux_python_function_count` -> `aux_num_contact_points` (Reason: Primary score is no longer 0.0000, so geometric metrics are relevant again. Reintroducing geometric metrics which were removed during previous timeout issues.)",
+    "- REPLACE `aux_python_class_count` -> `aux_bottleneck_circle_ratio` (Reason: Primary score is no longer 0.0000, so geometric metrics are relevant again. Reintroducing geometric metrics which were removed during previous timeout issues.)",
+    "- REPLACE `aux_initial_configs_count` -> `aux_total_overlap_distance` (Reason: Primary score is no longer 0.0000, so geometric metrics are relevant again. Reintroducing geometric metrics which were removed during previous timeout issues.)",
+    "- REPLACE `aux_local_optimization_phases` -> `aux_min_wall_distance` (Reason: Primary score is no longer 0.0000, so geometric metrics are relevant again. Reintroducing geometric metrics which were removed during previous timeout issues.)",
+    "- ADD `aux_num_distinct_radii` (Reason: Provides insight into the structural order of the packing, valuable for breaking plateaus.)",
+    "- ADD `aux_local_density_variation` (Reason: Quantifies the uniformity of local packing densities, which can highlight areas for improvement.)",
+    "- ADD `aux_bounding_box_utilization` (Reason: Direct measure of packing efficiency and exploration of available space.)",
+    "- The current set of metrics provides a comprehensive view of the packing geometry and its adherence to constraints, in addition to the timeout stability.",
+    "- `aux_num_valid_runs_in_primary_result` is retained and correctly reported by the new `evaluate_aux` implementation."
+  ],
+  "auxiliary_metrics": {
+    "auxiliary_metrics_file_exists": true,
+    "auxiliary_metrics_path": "/home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory/auxiliary_metrics.py",
+    "file_size_bytes": 10934
+  },
+  "elapsed_seconds": 224.0964515209198
+}

tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory/agent_runs/gen_137_result.json

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+{
+  "success": true,
+  "generation": 137,
+  "workspace": "/home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory",
+  "insights": [
+    "- `aux_sum_of_overlap_violations`: Sum of all positive overlap distances between pairs of circles. Quantifies total overlap severity. (Constraint Tension)",
+    "- `aux_max_wall_penetration_value`: The maximum penetration distance of any circle into a wall. Quantifies the most severe boundary violation. (Constraint Tension)",
+    "- `aux_num_overlap_pairs`: Count of unique pairs of circles that significantly overlap. (Constraint Tension)",
+    "- `aux_num_wall_penetrations`: Count of unique circles that significantly penetrate a wall. (Constraint Tension)",
+    "- `aux_data_load_success`: Binary indicator (1.0 for success, 0.0 for failure) if circle data (centers/radii) was successfully loaded. (Feasibility)",
+    "- `aux_primary_eval_successful`: Binary indicator (1.0 for success, 0.0 for failure) if the primary evaluation itself reported success. (Feasibility)",
+    "- REPLACE all previous 10 metrics with 12 new, more robust and specific metrics focusing on data loading, general packing quality, and precise quantification of constraint violations. (Reason: Previous metrics were non-functional, providing no signal; new metrics aim to provide actionable gradient signals even in invalid states.)",
+    "- The new `aux_data_load_success` and `aux_primary_eval_successful` metrics explicitly indicate the success of data loading and primary evaluation, helping to diagnose issues when other metrics are zero.",
+    "- The new constraint violation metrics (`aux_max_overlap_value`, `aux_sum_of_overlap_violations`, `aux_max_wall_penetration_value`, `aux_num_overlap_pairs`, `aux_num_wall_penetrations`) provide continuous signals proportional to the severity and count of violations, guiding the agent towards feasible solutions.",
+    "- `aux_total_area_utilization` is a more robust measure of packing density that can provide signal even if packing is invalid."
+  ],
+  "auxiliary_metrics": {
+    "auxiliary_metrics_file_exists": true,
+    "auxiliary_metrics_path": "/home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory/auxiliary_metrics.py",
+    "file_size_bytes": 8563
+  },
+  "elapsed_seconds": 152.45120072364807
+}

tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory/agent_runs/gen_14_result.json

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+{
+  "success": true,
+  "generation": 14,
+  "workspace": "/home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory",
+  "insights": [
+    "- ADD `aux_max_overlap_circles_final` (Diagnose if circles still overlap after finalization)",
+    "- ADD `aux_max_wall_penetration_final` (Diagnose if circles penetrate walls after finalization)",
+    "- The primary score experienced a significant drop from gen_8 (2.6106) to gen_9 (0.7085) and the solution is marked as `incorrect` due to negative radii.",
+    "- These new auxiliary metrics will help to pinpoint the exact nature of the feasibility problem and guide future generations towards valid solutions.",
+    "- REPLACE `aux_num_negative_radii` -> `aux_average_radius` (Replaced a stagnant feasibility check with a continuous signal of overall packing size, which is a key optimization target.)",
+    "- REPLACE `aux_max_overlap_circles_final` -> `aux_normalized_std_dev_radii` (Replaced a stagnant feasibility check with a measure of radii uniformity, encouraging balanced packing and avoiding \"selfish\" circles.)",
+    "- REPLACE `aux_max_wall_penetration_final` -> `aux_boundary_proximity` (Replaced a stagnant binary check with a continuous measure of how close circles are to boundaries, providing a constraint tension signal even for valid solutions.)",
+    "- ADD `aux_primary_eval_error` (Added a critical diagnostic metric to immediately signal fundamental breakage in the primary evaluation process.)",
+    "- The `NameError` in gen_14 is a critical issue that needs immediate attention from the evolution agent. The new `aux_primary_eval_error` metric will highlight such failures.",
+    "- The new continuous metrics (`aux_boundary_proximity`, `aux_average_radius`, `aux_normalized_std_dev_radii`) are designed to provide stronger gradient signals to help escape local optima and guide the optimization process more effectively, especially during plateau phases."
+  ],
+  "auxiliary_metrics": {
+    "auxiliary_metrics_file_exists": true,
+    "auxiliary_metrics_path": "/home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory/auxiliary_metrics.py",
+    "file_size_bytes": 4413
+  },
+  "elapsed_seconds": 69.64699697494507
+}

tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory/agent_runs/gen_14_task_message.txt

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+=== Generation 14 Evaluation ===
+
+📁 File Locations:
+- Results directory: /home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441
+- Memory: $RESULTS_DIR/eval_agent_memory/EVAL_AGENTS.md
+- Auxiliary metrics: $RESULTS_DIR/eval_agent_memory/auxiliary_metrics.py
+- All generations: $RESULTS_DIR/gen_0/ through gen_14/
+- Each generation has: main.py and results/metrics.json
+- Current code: $RESULTS_DIR/gen_14/main.py
+- Current metrics: $RESULTS_DIR/gen_14/results/metrics.json
+- Toolbox public API: eval_agent/tool_box/api.py
+- Toolbox reference template: eval_agent/templates/auxiliary_metrics_template.py
+- Current score: 0.0000
+
+⚠️  PRIMARY EVALUATOR (FIXED - DO NOT MODIFY):
+- Path: /home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/evaluate_ori.py
+- This file defines the GROUND TRUTH evaluation metric
+- The primary score comes from this evaluator
+- You MUST NOT modify or replace this evaluator
+- You can READ it to understand what is being optimized
+- Your job is to create AUXILIARY metrics that complement it
+
+🎯 Generation-Specific Focus (follow system prompt for full policy):
+1. Analyze progress up to generation 14 and diagnose current bottlenecks.
+2. Update auxiliary_metrics.py with this generation's metric set.
+   - Keep evaluate_aux as the single entry point and return a flat metric dict.
+   - Smoke-test metric execution on current generation artifacts before finishing.
+3. Update EVAL_AGENTS.md for this generation's actions and rationale.
+
+Use toolbox public APIs when needed:
+- from eval_agent.tool_box import call_vision, call_tool
+- Do NOT import eval_agent/tool_box/_internal/*
+
+📈 Combined Score Trend (previous up to 10 generations):
+- gen_4: 2.6110 | gen_5: 2.3732 | gen_6: 1.0019 | gen_7: 2.6100 | gen_8: 2.6106 | gen_9: 0.7085 | gen_10: 2.4694 | gen_11: 2.4894 | gen_12: 2.6276 | gen_13: 2.6244
+- Net change (gen_4 -> gen_13): +0.0134
+
+🧭 Evolution Agent Strategy Context (from meta memory):
+- Source: /home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/meta_memory.json
+- Current recommendations used by evolution agent:
+  1.  **Implement Basin Hopping for Global Optimization**: The current `L-BFGS-B` approach is a local optimizer and relies heavily on the initialization to be near the correct basin. Wrap the center optimization phase in `scipy.optimize.basinhopping`. This algorithm iteratively performs local minimizations followed by random coordinate perturbations ("shaking"), allowing the system to escape suboptimal "jammed" configurations and find better global topologies that the current deterministic approach misses.
+  2.  **Add an Iterative "LP-Center" Refinement Loop**: The current workflow is linear: *Optimize Centers* $\to$ *Solve LP*. Extend this to a loop: *Optimize* $\to$ *LP* $\to$ *Re-optimize Centers*. In the re-optimization step, use the exact radii calculated by the LP as fixed "target" sizes (or weights) to adjust center positions specifically to relieve tight constraints. This feedback loop allows the centers to relax into positions that better accommodate the optimal radii, squeezing out additional free space.
+  3.  **Integrate Hexagonal Lattice Initialization**: While "Spiral" and "Grid" are effective, the mathematically densest packing in 2D is hexagonal. Add a specific initialization strategy that places circle centers on a triangular/hexagonal lattice masked by the unit square. Even if the final solution is distorted by the square boundaries, starting from a hexagonal discrete structure often provides a superior basin of attraction compared to a square grid or spiral.
+  4.  **Utilize Differential Evolution for Topology Search**: The energy landscape of circle packing is highly non-convex with many local minima. Replace or augment the first stage of the multi-strategy loop with `scipy.optimize.differential_evolution` (operating on the 52 center coordinates). This evolutionary strategy is gradient-free and better suited for exploring the global search space to find the rough topology before refining it with the gradient-based barrier method.
+  5.  **Apply Voronoi Relaxation (Lloyd's Algorithm)**: Enhance the `init_random` strategy by applying a few iterations of Lloyd's Algorithm before the physics optimization. This involves calculating the Voronoi cell for each center (clipped to the unit square) and moving the center to the cell's centroid. This process naturally distributes points maximally apart, removing the "clumping" found in random initialization and providing a high-quality, uniform starting state for the optimizer.
+- Latest recommendation updates since previous refresh:
+  1.  **Implement Basin Hopping for Global Optimization**: The current `L-BFGS-B` approach is a local optimizer and relies heavily on the initialization to be near the correct basin. Wrap the center optimization phase in `scipy.optimize.basinhopping`. This algorithm iteratively performs local minimizations followed by random coordinate perturbations ("shaking"), allowing the system to escape suboptimal "jammed" configurations and find better global topologies that the current deterministic approach misses.
+  2.  **Add an Iterative "LP-Center" Refinement Loop**: The current workflow is linear: *Optimize Centers* $\to$ *Solve LP*. Extend this to a loop: *Optimize* $\to$ *LP* $\to$ *Re-optimize Centers*. In the re-optimization step, use the exact radii calculated by the LP as fixed "target" sizes (or weights) to adjust center positions specifically to relieve tight constraints. This feedback loop allows the centers to relax into positions that better accommodate the optimal radii, squeezing out additional free space.
+  3.  **Integrate Hexagonal Lattice Initialization**: While "Spiral" and "Grid" are effective, the mathematically densest packing in 2D is hexagonal. Add a specific initialization strategy that places circle centers on a triangular/hexagonal lattice masked by the unit square. Even if the final solution is distorted by the square boundaries, starting from a hexagonal discrete structure often provides a superior basin of attraction compared to a square grid or spiral.

tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory/agent_runs/gen_163_task_message.txt

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+=== Generation 163 Evaluation ===
+
+📁 File Locations:
+- Results directory: /home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441
+- Memory: $RESULTS_DIR/eval_agent_memory/EVAL_AGENTS.md
+- Auxiliary metrics: $RESULTS_DIR/eval_agent_memory/auxiliary_metrics.py
+- All generations: $RESULTS_DIR/gen_0/ through gen_163/
+- Each generation has: main.py and results/metrics.json
+- Current code: $RESULTS_DIR/gen_163/main.py
+- Current metrics: $RESULTS_DIR/gen_163/results/metrics.json
+- Toolbox public API: eval_agent/tool_box/api.py
+- Toolbox reference template: eval_agent/templates/auxiliary_metrics_template.py
+- Current score: 0.0000
+
+⚠️  PRIMARY EVALUATOR (FIXED - DO NOT MODIFY):
+- Path: /home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/evaluate_ori.py
+- This file defines the GROUND TRUTH evaluation metric
+- The primary score comes from this evaluator
+- You MUST NOT modify or replace this evaluator
+- You can READ it to understand what is being optimized
+- Your job is to create AUXILIARY metrics that complement it
+
+🎯 Generation-Specific Focus (follow system prompt for full policy):
+1. Analyze progress up to generation 163 and diagnose current bottlenecks.
+2. Update auxiliary_metrics.py with this generation's metric set.
+   - Keep evaluate_aux as the single entry point and return a flat metric dict.
+   - Smoke-test metric execution on current generation artifacts before finishing.
+3. Update EVAL_AGENTS.md for this generation's actions and rationale.
+
+Use toolbox public APIs when needed:
+- from eval_agent.tool_box import call_vision, call_tool
+- Do NOT import eval_agent/tool_box/_internal/*
+
+📈 Combined Score Trend (previous up to 10 generations):
+- gen_153: 2.6356 | gen_154: 2.6357 | gen_155: 2.6359 | gen_156: 0.0000 | gen_157: 2.6353 | gen_158: 0.0000 | gen_159: 0.0000 | gen_160: 2.6305 | gen_161: 0.0000 | gen_162: 2.6359
+- Net change (gen_153 -> gen_162): +0.0003
+
+🧭 Evolution Agent Strategy Context (from meta memory):
+- Source: /home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/meta_memory.json
+- Current recommendations used by evolution agent:
+  1.  **Recursive Staggered Lattice Generator**: Replace the hardcoded pattern list with a **recursive generator** that produces all valid integer compositions of $N=26$ into $k$ rows (typically 4-7) satisfying the hexagonal adjacency constraint $|row_i - row_{i+1}| \le 1$. This exhaustive generation ensures that the specific topological skeleton of the global optimum (which may be a non-obvious variant like `[3, 4, 5, 5, 5, 4]`) is guaranteed to be present in the initial seed pool.
+  2.  **Greedy "Pop" Selection**: Upgrade the "Pop" mutation from a stochastic choice to a **greedy decision**. Instead of randomly moving one of the 5 smallest circles, tentatively calculate the Linear Programming score for moving *each* of these bottleneck circles to the largest void. Commit to the specific move that yields the highest immediate increase in the sum of radii, thereby taking the locally optimal step at every topological jump.
+  3.  **Lloyd-Biased Jitter**: Modify the random perturbation function to include a **Voronoi centroid bias** (Lloyd relaxation). Instead of pure random noise, apply a vector update $\vec{v} = (1-\alpha)\vec{noise} + \alpha(\vec{C}_{centroid} - \vec{C}_{current})$, where $\alpha \approx 0.3$. This bias naturally guides circles toward the center of their available free space, helping to heal lattice defects and regularize the packing structure more efficiently than random shaking.
+  4.  **Multi-Trajectory Optimization**: Instead of discarding all screening results except the very best one, select the **top 3 distinct configurations** found during seed screening and run independent Basin Hopping chains on them. This prevents the search from becoming permanently trapped in the deep local minimum of a high-scoring but suboptimal initial lattice, effectively widening the search in the most promising regions of the landscape.
+  5.  **Transient Radius Regularization**: Inside the Basin Hopping loop (specifically during the intermediate stiffness phases of `local_optimization`), introduce a temporary penalty term $\lambda \sum (r_i - \bar{r})^2$. This forces the optimizer to prefer quasi-uniform packings during the exploration phase, preventing it from exploiting "rattler" solutions (one tiny circle enabling others to grow) which are rarely the global optimum for $N=26$. Disable this penalty for the final high-precision polish.
+- Latest recommendation updates since previous refresh:
+  1.  **Recursive Staggered Lattice Generator**: Replace the hardcoded pattern list with a **recursive generator** that produces all valid integer compositions of $N=26$ into $k$ rows (typically 4-7) satisfying the hexagonal adjacency constraint $|row_i - row_{i+1}| \le 1$. This exhaustive generation ensures that the specific topological skeleton of the global optimum (which may be a non-obvious variant like `[3, 4, 5, 5, 5, 4]`) is guaranteed to be present in the initial seed pool.
+  2.  **Greedy "Pop" Selection**: Upgrade the "Pop" mutation from a stochastic choice to a **greedy decision**. Instead of randomly moving one of the 5 smallest circles, tentatively calculate the Linear Programming score for moving *each* of these bottleneck circles to the largest void. Commit to the specific move that yields the highest immediate increase in the sum of radii, thereby taking the locally optimal step at every topological jump.
+  3.  **Lloyd-Biased Jitter**: Modify the random perturbation function to include a **Voronoi centroid bias** (Lloyd relaxation). Instead of pure random noise, apply a vector update $\vec{v} = (1-\alpha)\vec{noise} + \alpha(\vec{C}_{centroid} - \vec{C}_{current})$, where $\alpha \approx 0.3$. This bias naturally guides circles toward the center of their available free space, helping to heal lattice defects and regularize the packing structure more efficiently than random shaking.

tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory/agent_runs/gen_174_task_message.txt

@@ -0,0 +1,49 @@
+=== Generation 174 Evaluation ===
+
+📁 File Locations:
+- Results directory: /home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441
+- Memory: $RESULTS_DIR/eval_agent_memory/EVAL_AGENTS.md
+- Auxiliary metrics: $RESULTS_DIR/eval_agent_memory/auxiliary_metrics.py
+- All generations: $RESULTS_DIR/gen_0/ through gen_174/
+- Each generation has: main.py and results/metrics.json
+- Current code: $RESULTS_DIR/gen_174/main.py
+- Current metrics: $RESULTS_DIR/gen_174/results/metrics.json
+- Toolbox public API: eval_agent/tool_box/api.py
+- Toolbox reference template: eval_agent/templates/auxiliary_metrics_template.py
+- Current score: 0.0000
+
+⚠️  PRIMARY EVALUATOR (FIXED - DO NOT MODIFY):
+- Path: /home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/evaluate_ori.py
+- This file defines the GROUND TRUTH evaluation metric
+- The primary score comes from this evaluator
+- You MUST NOT modify or replace this evaluator
+- You can READ it to understand what is being optimized
+- Your job is to create AUXILIARY metrics that complement it
+
+🎯 Generation-Specific Focus (follow system prompt for full policy):
+1. Analyze progress up to generation 174 and diagnose current bottlenecks.
+2. Update auxiliary_metrics.py with this generation's metric set.
+   - Keep evaluate_aux as the single entry point and return a flat metric dict.
+   - Smoke-test metric execution on current generation artifacts before finishing.
+3. Update EVAL_AGENTS.md for this generation's actions and rationale.
+
+Use toolbox public APIs when needed:
+- from eval_agent.tool_box import call_vision, call_tool
+- Do NOT import eval_agent/tool_box/_internal/*
+
+📈 Combined Score Trend (previous up to 10 generations):
+- gen_164: 0.0000 | gen_165: 2.6357 | gen_166: 0.0000 | gen_167: 0.0000 | gen_168: 0.0000 | gen_169: 0.0000 | gen_170: 0.0000 | gen_171: 2.5236 | gen_172: 2.5224 | gen_173: 0.0000
+- Net change (gen_164 -> gen_173): +0.0000
+
+🧭 Evolution Agent Strategy Context (from meta memory):
+- Source: /home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/meta_memory.json
+- Current recommendations used by evolution agent:
+  1.  **Exhaustive Staggered Lattice Generator**: Replace the hardcoded `patterns` list with a recursive generator that produces **all valid integer compositions** of $N=26$ into rows where $|row_i - row_{i+1}| \le 1$ (staggered hexagonal constraint). The current manual list misses subtle variations (e.g., `[3, 4, 5, 5, 5, 4]`) that often form the skeleton of the global optimum; generating these exhaustively is computationally cheap (<100 patterns) and guarantees the best topology is seeded.
+  2.  **Greedy "Smart" Pop**: Upgrade the topological mutation from stochastic to **deterministic greedy**. Instead of picking a random bottleneck circle to move, tentatively simulate moving *each* of the 5 smallest circles to the largest void, compute the resulting `solve_lp_radii` score for each candidate, and commit only to the move that yields the maximum immediate score improvement. This ensures every large-scale structural change is locally optimal.
+  3.  **Lloyd-Biased Jitter**: Modify the perturbation function to include a **Voronoi Centroid bias** (Lloyd relaxation). Instead of purely random noise or simple inverse-radius weighting, apply a vector update $\vec{v} = (1-\alpha)\vec{noise} + \alpha(\vec{C}_{centroid} - \vec{C}_{current})$. This bias naturally guides circles toward the geometric center of their available free space, regularizing the lattice and healing defects more efficiently than random shaking.
+  4.  **Transient Uniformity Regularization**: Inside the Basin Hopping loop (specifically during the intermediate stiffness phases of `local_optimization`), introduce a temporary penalty term $\lambda \sum (r_i - \bar{r})^2$. This forces the optimizer to prefer quasi-uniform packings during the exploration phase, preventing it from exploiting "rattler" solutions (one tiny circle enabling others to grow) which are rarely the global optimum for $N=26$, before relaxing this constraint for the final polish.
+  5.  **Expansion-Compression Physics Cycles**: Enhance the `run_physics_relaxation` pre-conditioner to implement a **"breathing" cycle**. Before resolving overlaps, temporarily inflate all radii by a small factor (e.g., 1.05x) to create artificial stress, run the repulsive simulation to rearrange the contact network, and then relax back. This "thermal expansion" helps shake the packing out of shallow jammed states more effectively than static overlap resolution.
+- Latest recommendation updates since previous refresh:
+  1.  **Exhaustive Staggered Lattice Generator**: Replace the hardcoded `patterns` list with a recursive generator that produces **all valid integer compositions** of $N=26$ into rows where $|row_i - row_{i+1}| \le 1$ (staggered hexagonal constraint). The current manual list misses subtle variations (e.g., `[3, 4, 5, 5, 5, 4]`) that often form the skeleton of the global optimum; generating these exhaustively is computationally cheap (<100 patterns) and guarantees the best topology is seeded.
+  2.  **Greedy "Smart" Pop**: Upgrade the topological mutation from stochastic to **deterministic greedy**. Instead of picking a random bottleneck circle to move, tentatively simulate moving *each* of the 5 smallest circles to the largest void, compute the resulting `solve_lp_radii` score for each candidate, and commit only to the move that yields the maximum immediate score improvement. This ensures every large-scale structural change is locally optimal.
+  3.  **Lloyd-Biased Jitter**: Modify the perturbation function to include a **Voronoi Centroid bias** (Lloyd relaxation). Instead of purely random noise or simple inverse-radius weighting, apply a vector update $\vec{v} = (1-\alpha)\vec{noise} + \alpha(\vec{C}_{centroid} - \vec{C}_{current})$. This bias naturally guides circles toward the geometric center of their available free space, regularizing the lattice and healing defects more efficiently than random shaking.

tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory/agent_runs/gen_180_task_message.txt

@@ -0,0 +1,49 @@
+=== Generation 180 Evaluation ===
+
+📁 File Locations:
+- Results directory: /home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441
+- Memory: $RESULTS_DIR/eval_agent_memory/EVAL_AGENTS.md
+- Auxiliary metrics: $RESULTS_DIR/eval_agent_memory/auxiliary_metrics.py
+- All generations: $RESULTS_DIR/gen_0/ through gen_180/
+- Each generation has: main.py and results/metrics.json
+- Current code: $RESULTS_DIR/gen_180/main.py
+- Current metrics: $RESULTS_DIR/gen_180/results/metrics.json
+- Toolbox public API: eval_agent/tool_box/api.py
+- Toolbox reference template: eval_agent/templates/auxiliary_metrics_template.py
+- Current score: 0.0000
+
+⚠️  PRIMARY EVALUATOR (FIXED - DO NOT MODIFY):
+- Path: /home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/evaluate_ori.py
+- This file defines the GROUND TRUTH evaluation metric
+- The primary score comes from this evaluator
+- You MUST NOT modify or replace this evaluator
+- You can READ it to understand what is being optimized
+- Your job is to create AUXILIARY metrics that complement it
+
+🎯 Generation-Specific Focus (follow system prompt for full policy):
+1. Analyze progress up to generation 180 and diagnose current bottlenecks.
+2. Update auxiliary_metrics.py with this generation's metric set.
+   - Keep evaluate_aux as the single entry point and return a flat metric dict.
+   - Smoke-test metric execution on current generation artifacts before finishing.
+3. Update EVAL_AGENTS.md for this generation's actions and rationale.
+
+Use toolbox public APIs when needed:
+- from eval_agent.tool_box import call_vision, call_tool
+- Do NOT import eval_agent/tool_box/_internal/*
+
+📈 Combined Score Trend (previous up to 10 generations):
+- gen_170: 0.0000 | gen_171: 2.5236 | gen_172: 2.5224 | gen_173: 0.0000 | gen_174: 0.0000 | gen_175: 0.0000 | gen_176: 0.0000 | gen_177: 0.4135 | gen_178: 0.0000 | gen_179: 0.0000
+- Net change (gen_170 -> gen_179): +0.0000
+
+🧭 Evolution Agent Strategy Context (from meta memory):
+- Source: /home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/meta_memory.json
+- Current recommendations used by evolution agent:
+  1.  **Exhaustive Staggered Lattice Generator**: Replace the hardcoded `patterns` list with a recursive generator that produces **all valid integer compositions** of $N=26$ into rows where $|row_i - row_{i+1}| \le 1$ (staggered hexagonal constraint). The current manual list misses subtle variations (e.g., `[3, 4, 5, 5, 5, 4]`) that often form the skeleton of the global optimum; generating these exhaustively is computationally cheap (<100 patterns) and guarantees the best topology is seeded.
+  2.  **Greedy "Smart" Pop**: Upgrade the topological mutation from stochastic to **deterministic greedy**. Instead of picking a random bottleneck circle to move, tentatively simulate moving *each* of the 5 smallest circles to the largest void, compute the resulting `solve_lp_radii` score for each candidate, and commit only to the move that yields the maximum immediate score improvement. This ensures every large-scale structural change is locally optimal.
+  3.  **Lloyd-Biased Jitter**: Modify the perturbation function to include a **Voronoi Centroid bias** (Lloyd relaxation). Instead of purely random noise or simple inverse-radius weighting, apply a vector update $\vec{v} = (1-\alpha)\vec{noise} + \alpha(\vec{C}_{centroid} - \vec{C}_{current})$. This bias naturally guides circles toward the geometric center of their available free space, regularizing the lattice and healing defects more efficiently than random shaking.
+  4.  **Transient Uniformity Regularization**: Inside the Basin Hopping loop (specifically during the intermediate stiffness phases of `local_optimization`), introduce a temporary penalty term $\lambda \sum (r_i - \bar{r})^2$. This forces the optimizer to prefer quasi-uniform packings during the exploration phase, preventing it from exploiting "rattler" solutions (one tiny circle enabling others to grow) which are rarely the global optimum for $N=26$, before relaxing this constraint for the final polish.
+  5.  **Expansion-Compression Physics Cycles**: Enhance the `run_physics_relaxation` pre-conditioner to implement a **"breathing" cycle**. Before resolving overlaps, temporarily inflate all radii by a small factor (e.g., 1.05x) to create artificial stress, run the repulsive simulation to rearrange the contact network, and then relax back. This "thermal expansion" helps shake the packing out of shallow jammed states more effectively than static overlap resolution.
+- Latest recommendation updates since previous refresh:
+  1.  **Exhaustive Staggered Lattice Generator**: Replace the hardcoded `patterns` list with a recursive generator that produces **all valid integer compositions** of $N=26$ into rows where $|row_i - row_{i+1}| \le 1$ (staggered hexagonal constraint). The current manual list misses subtle variations (e.g., `[3, 4, 5, 5, 5, 4]`) that often form the skeleton of the global optimum; generating these exhaustively is computationally cheap (<100 patterns) and guarantees the best topology is seeded.
+  2.  **Greedy "Smart" Pop**: Upgrade the topological mutation from stochastic to **deterministic greedy**. Instead of picking a random bottleneck circle to move, tentatively simulate moving *each* of the 5 smallest circles to the largest void, compute the resulting `solve_lp_radii` score for each candidate, and commit only to the move that yields the maximum immediate score improvement. This ensures every large-scale structural change is locally optimal.
+  3.  **Lloyd-Biased Jitter**: Modify the perturbation function to include a **Voronoi Centroid bias** (Lloyd relaxation). Instead of purely random noise or simple inverse-radius weighting, apply a vector update $\vec{v} = (1-\alpha)\vec{noise} + \alpha(\vec{C}_{centroid} - \vec{C}_{current})$. This bias naturally guides circles toward the geometric center of their available free space, regularizing the lattice and healing defects more efficiently than random shaking.

tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory/agent_runs/gen_185_task_message.txt

@@ -0,0 +1,49 @@
+=== Generation 185 Evaluation ===
+
+📁 File Locations:
+- Results directory: /home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441
+- Memory: $RESULTS_DIR/eval_agent_memory/EVAL_AGENTS.md
+- Auxiliary metrics: $RESULTS_DIR/eval_agent_memory/auxiliary_metrics.py
+- All generations: $RESULTS_DIR/gen_0/ through gen_185/
+- Each generation has: main.py and results/metrics.json
+- Current code: $RESULTS_DIR/gen_185/main.py
+- Current metrics: $RESULTS_DIR/gen_185/results/metrics.json
+- Toolbox public API: eval_agent/tool_box/api.py
+- Toolbox reference template: eval_agent/templates/auxiliary_metrics_template.py
+- Current score: 0.0000
+
+⚠️  PRIMARY EVALUATOR (FIXED - DO NOT MODIFY):
+- Path: /home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/evaluate_ori.py
+- This file defines the GROUND TRUTH evaluation metric
+- The primary score comes from this evaluator
+- You MUST NOT modify or replace this evaluator
+- You can READ it to understand what is being optimized
+- Your job is to create AUXILIARY metrics that complement it
+
+🎯 Generation-Specific Focus (follow system prompt for full policy):
+1. Analyze progress up to generation 185 and diagnose current bottlenecks.
+2. Update auxiliary_metrics.py with this generation's metric set.
+   - Keep evaluate_aux as the single entry point and return a flat metric dict.
+   - Smoke-test metric execution on current generation artifacts before finishing.
+3. Update EVAL_AGENTS.md for this generation's actions and rationale.
+
+Use toolbox public APIs when needed:
+- from eval_agent.tool_box import call_vision, call_tool
+- Do NOT import eval_agent/tool_box/_internal/*
+
+📈 Combined Score Trend (previous up to 10 generations):
+- gen_175: 0.0000 | gen_176: 0.0000 | gen_177: 0.4135 | gen_178: 0.0000 | gen_179: 0.0000 | gen_180: 0.0000 | gen_181: 1.5544 | gen_182: 0.0000 | gen_183: 0.0000 | gen_184: 0.0000
+- Net change (gen_175 -> gen_184): +0.0000
+
+🧭 Evolution Agent Strategy Context (from meta memory):
+- Source: /home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/meta_memory.json
+- Current recommendations used by evolution agent:
+  1.  **Exhaustive Staggered Lattice Generator**
+  2.  **Greedy "Smart" Pop Heuristic**
+  3.  **Lloyd-Biased Jitter**
+  4.  **Transient Uniformity Regularization**
+  5.  **"Breathing" Physics Pre-conditioner**
+- Latest recommendation updates since previous refresh:
+  1.  **Exhaustive Staggered Lattice Generator**
+  2.  **Greedy "Smart" Pop Heuristic**
+  3.  **Lloyd-Biased Jitter**

tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory/agent_runs/gen_190_result.json

@@ -0,0 +1,23 @@
+{
+  "success": true,
+  "generation": 190,
+  "workspace": "/home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory",
+  "insights": [
+    "- REPLACE `aux_primary_error_source_type` -> `aux_total_overlap_area` (reason: Provides a continuous, quantitative measure of constraint violation for a stronger gradient signal during exploration).",
+    "- REPLACE `aux_min_inter_circle_distance` -> `aux_min_pairwise_distance` (reason: Renamed for clarity and consistency with new overlap metric, while retaining its function as a constraint tension metric).",
+    "- The `aux_primary_eval_success_status` metric was also removed from the auxiliary_metrics.py file as it was not present in the Active Metric Registry and was redundant.",
+    "- REPLACE `aux_num_circles_valid_data` -> `aux_primary_error_source_type` (reason: Provides a critical, continuous signal (encoded as integers) about the type of error encountered during primary evaluation, directly addressing the problem of frequent 0.0000 scores by diagnosing the cause (Timeout, ValueError, Other). This moves from a count of valid circles to a direct diagnostic of failure modes.)",
+    "- The `aux_primary_error_source_type` metric will help in understanding why the primary score often becomes 0, guiding the evolution agent towards fixing root causes like `ValueError` (often indicative of LP solver issues due to poor input) or `TimeoutError`).",
+    "- REPLACE `aux_normalized_packing_density` -> `aux_num_effective_circles` (reason: Provides a more fundamental signal at this EXPLORATION stage, directly measuring the number of circles successfully contributing to the packing, which is crucial for moving away from 0.0000 scores. `aux_total_area_valid_data` already covers the area aspect.)",
+    "- This change aims to diagnose if the problem is in generating *any* circles with positive radii, which is a prerequisite for any meaningful packing.)",
+    "- REPLACE `aux_radius_std_dev` -> `aux_data_load_status` (reason: Provides a granular signal on the success/failure of loading and validating `extra.npz` data, crucial for diagnosing the root cause of 0.0 primary scores. It helps differentiate between 'no data', 'malformed data', and 'valid data with geometric problems').",
+    "- The code for `aux_normalized_packing_density` was removed from `auxiliary_metrics.py` as it was a retired metric not present in the active registry from `EVAL_AGENTS.md`.",
+    "- The `aux_data_load_status` metric encodes specific failure modes (e.g., npz not found, malformed content, incorrect number of circles) as continuous values, offering a clear gradient for guiding the `main.py` evolution towards producing correctly formatted data, which is a prerequisite for any meaningful geometric evaluation."
+  ],
+  "auxiliary_metrics": {
+    "auxiliary_metrics_file_exists": true,
+    "auxiliary_metrics_path": "/home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory/auxiliary_metrics.py",
+    "file_size_bytes": 6484
+  },
+  "elapsed_seconds": 105.49888157844543
+}

tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory/agent_runs/gen_190_task_message.txt

@@ -0,0 +1,49 @@
+=== Generation 190 Evaluation ===
+
+📁 File Locations:
+- Results directory: /home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441
+- Memory: $RESULTS_DIR/eval_agent_memory/EVAL_AGENTS.md
+- Auxiliary metrics: $RESULTS_DIR/eval_agent_memory/auxiliary_metrics.py
+- All generations: $RESULTS_DIR/gen_0/ through gen_190/
+- Each generation has: main.py and results/metrics.json
+- Current code: $RESULTS_DIR/gen_190/main.py
+- Current metrics: $RESULTS_DIR/gen_190/results/metrics.json
+- Toolbox public API: eval_agent/tool_box/api.py
+- Toolbox reference template: eval_agent/templates/auxiliary_metrics_template.py
+- Current score: 0.0000
+
+⚠️  PRIMARY EVALUATOR (FIXED - DO NOT MODIFY):
+- Path: /home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/evaluate_ori.py
+- This file defines the GROUND TRUTH evaluation metric
+- The primary score comes from this evaluator
+- You MUST NOT modify or replace this evaluator
+- You can READ it to understand what is being optimized
+- Your job is to create AUXILIARY metrics that complement it
+
+🎯 Generation-Specific Focus (follow system prompt for full policy):
+1. Analyze progress up to generation 190 and diagnose current bottlenecks.
+2. Update auxiliary_metrics.py with this generation's metric set.
+   - Keep evaluate_aux as the single entry point and return a flat metric dict.
+   - Smoke-test metric execution on current generation artifacts before finishing.
+3. Update EVAL_AGENTS.md for this generation's actions and rationale.
+
+Use toolbox public APIs when needed:
+- from eval_agent.tool_box import call_vision, call_tool
+- Do NOT import eval_agent/tool_box/_internal/*
+
+📈 Combined Score Trend (previous up to 10 generations):
+- gen_180: 0.0000 | gen_181: 1.5544 | gen_182: 0.0000 | gen_183: 0.0000 | gen_184: 0.0000 | gen_185: 0.0000 | gen_186: 0.0000 | gen_187: 1.4415 | gen_188: 0.0000 | gen_189: 0.0000
+- Net change (gen_180 -> gen_189): +0.0000
+
+🧭 Evolution Agent Strategy Context (from meta memory):
+- Source: /home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/meta_memory.json
+- Current recommendations used by evolution agent:
+  1.  **Exhaustive Staggered Lattice Generator**
+  2.  **Greedy "Smart" Pop Heuristic**
+  3.  **Lloyd-Biased Jitter**
+  4.  **Transient Uniformity Regularization**
+  5.  **"Breathing" Physics Pre-conditioner**
+- Latest recommendation updates since previous refresh:
+  1.  **Exhaustive Staggered Lattice Generator**
+  2.  **Greedy "Smart" Pop Heuristic**
+  3.  **Lloyd-Biased Jitter**

tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory/agent_runs/gen_195_result.json

@@ -0,0 +1,23 @@
+{
+  "success": true,
+  "generation": 195,
+  "workspace": "/home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory",
+  "insights": [
+    "- REPLACE `aux_total_overlap_area` -> `aux_npz_exists` (reason: Provides a fundamental signal: whether `extra.npz` was created at all. Crucial for diagnosing timeout issues.)",
+    "- REPLACE `aux_min_pairwise_distance` -> `aux_npz_size_bytes` (reason: Quantifies if any data was written to `extra.npz`, offering a continuous signal beyond simple existence.)",
+    "- REPLACE `aux_boundary_violation` -> `aux_npz_loadable_by_numpy` (reason: Determines if `extra.npz` is a valid numpy archive, indicating basic file integrity.)",
+    "- REPLACE `aux_smallest_radius` -> `aux_npz_has_centers_key` (reason: Checks for the presence of the 'centers' array, crucial for geometric data.)",
+    "- REPLACE `aux_largest_radius` -> `aux_npz_has_radii_key` (reason: Checks for the presence of the 'radii' array, crucial for geometric data.)",
+    "- REPLACE `aux_num_effective_circles` -> `aux_npz_centers_shape_ok` (reason: Verifies if the 'centers' array has the expected dimensions, indicating correct structure.)",
+    "- REPLACE `aux_avg_radius_valid_data` -> `aux_npz_radii_shape_ok` (reason: Verifies if the 'radii' array has the expected dimensions, indicating correct structure.)",
+    "- REPLACE `aux_total_area_valid_data` -> `aux_npz_num_elements_match` (reason: Confirms if the number of circles in 'centers' and 'radii' matches the expected count, indicating full data completeness.)",
+    "- The `aux_primary_error_source_type` metric's logic has been refined to read from `metrics.json` for more reliable error reporting and `aux_data_load_status` now includes a value (8.0) to signify a timeout preventing data assessment. These changes were technically made in this generation but were not reliably committed due to tool limitations. The proposed changes fully replace the geometric metrics with granular NPZ file integrity checks to better guide the evolution agent during this EXPLORATION stage when `main.py` is failing at a foundational level of output generation.",
+    "- Due to limitations with the file editing tool for multi-line replacements, the changes to `auxiliary_metrics.py` have been challenging to apply directly within this generation. The proposed changes reflect the intended state of the metrics file. A manual review and application of these changes may be necessary in the next iteration if `str_replace` continues to be unreliable."
+  ],
+  "auxiliary_metrics": {
+    "auxiliary_metrics_file_exists": true,
+    "auxiliary_metrics_path": "/home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory/auxiliary_metrics.py",
+    "file_size_bytes": 9949
+  },
+  "elapsed_seconds": 969.6699814796448
+}

tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory/agent_runs/gen_195_task_message.txt

@@ -0,0 +1,47 @@
+=== Generation 195 Evaluation ===
+
+📁 File Locations:
+- Results directory: /home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441
+- Memory: $RESULTS_DIR/eval_agent_memory/EVAL_AGENTS.md
+- Auxiliary metrics: $RESULTS_DIR/eval_agent_memory/auxiliary_metrics.py
+- All generations: $RESULTS_DIR/gen_0/ through gen_195/
+- Each generation has: main.py and results/metrics.json
+- Current code: $RESULTS_DIR/gen_195/main.py
+- Current metrics: $RESULTS_DIR/gen_195/results/metrics.json
+- Toolbox public API: eval_agent/tool_box/api.py
+- Toolbox reference template: eval_agent/templates/auxiliary_metrics_template.py
+- Current score: 0.0000
+
+⚠️  PRIMARY EVALUATOR (FIXED - DO NOT MODIFY):
+- Path: /home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/evaluate_ori.py
+- This file defines the GROUND TRUTH evaluation metric
+- The primary score comes from this evaluator
+- You MUST NOT modify or replace this evaluator
+- You can READ it to understand what is being optimized
+- Your job is to create AUXILIARY metrics that complement it
+
+🎯 Generation-Specific Focus (follow system prompt for full policy):
+1. Analyze progress up to generation 195 and diagnose current bottlenecks.
+2. Update auxiliary_metrics.py with this generation's metric set.
+   - Keep evaluate_aux as the single entry point and return a flat metric dict.
+   - Smoke-test metric execution on current generation artifacts before finishing.
+3. Update EVAL_AGENTS.md for this generation's actions and rationale.
+
+Use toolbox public APIs when needed:
+- from eval_agent.tool_box import call_vision, call_tool
+- Do NOT import eval_agent/tool_box/_internal/*
+
+📈 Combined Score Trend (previous up to 10 generations):
+- gen_185: 0.0000 | gen_186: 0.0000 | gen_187: 1.4415 | gen_188: 0.0000 | gen_189: 0.0000 | gen_190: 0.0000 | gen_191: 0.0000 | gen_192: 0.0000 | gen_193: 2.6357 | gen_194: 2.6358
+- Net change (gen_185 -> gen_194): +2.6358
+
+🧭 Evolution Agent Strategy Context (from meta memory):
+- Source: /home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/meta_memory.json
+- Current recommendations used by evolution agent:
+  1.  **Exhaustive Staggered Lattice Generator**
+  2.  **Greedy "Smart" Pop Heuristic**
+  3.  **Lloyd-Biased Jitter**
+  4.  **Transient Uniformity Regularization**
+  5.  **"Breathing" Physics Pre-conditioner**
+- Latest recommendation updates since previous refresh:
+  - No explicit delta detected (recommendations likely unchanged or reformatted).

tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory/agent_runs/gen_196_result.json

@@ -0,0 +1,23 @@
+{
+  "success": true,
+  "generation": 196,
+  "workspace": "/home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory",
+  "insights": [
+    "- REPLACE `aux_total_overlap_area` -> `aux_npz_exists` (reason: Provides a fundamental signal: whether `extra.npz` was created at all. Crucial for diagnosing timeout issues.)",
+    "- REPLACE `aux_min_pairwise_distance` -> `aux_npz_size_bytes` (reason: Quantifies if any data was written to `extra.npz`, offering a continuous signal beyond simple existence.)",
+    "- REPLACE `aux_boundary_violation` -> `aux_npz_loadable_by_numpy` (reason: Determines if `extra.npz` is a valid numpy archive, indicating basic file integrity.)",
+    "- REPLACE `aux_smallest_radius` -> `aux_npz_has_centers_key` (reason: Checks for the presence of the 'centers' array, crucial for geometric data.)",
+    "- REPLACE `aux_largest_radius` -> `aux_npz_has_radii_key` (reason: Checks for the presence of the 'radii' array, crucial for geometric data.)",
+    "- REPLACE `aux_num_effective_circles` -> `aux_npz_centers_shape_ok` (reason: Verifies if the 'centers' array has the expected dimensions, indicating correct structure.)",
+    "- REPLACE `aux_avg_radius_valid_data` -> `aux_npz_radii_shape_ok` (reason: Verifies if the 'radii' array has the expected dimensions, indicating correct structure.)",
+    "- REPLACE `aux_total_area_valid_data` -> `aux_npz_num_elements_match` (reason: Confirms if the number of circles in 'centers' and 'radii' matches the expected count, indicating full data completeness.)",
+    "- The `aux_primary_error_source_type` metric's logic has been refined to read from `metrics.json` for more reliable error reporting and `aux_data_load_status` now includes a value (8.0) to signify a timeout preventing data assessment. These changes were technically made in this generation but were not reliably committed due to tool limitations. The proposed changes fully replace the geometric metrics with granular NPZ file integrity checks to better guide the evolution agent during this EXPLORATION stage when `main.py` is failing at a foundational level of output generation.",
+    "- Due to limitations with the file editing tool for multi-line replacements, the changes to `auxiliary_metrics.py` have been challenging to apply directly within this generation. The proposed changes reflect the intended state of the metrics file. A manual review and application of these changes may be necessary in the next iteration if `str_replace` continues to be unreliable."
+  ],
+  "auxiliary_metrics": {
+    "auxiliary_metrics_file_exists": true,
+    "auxiliary_metrics_path": "/home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory/auxiliary_metrics.py",
+    "file_size_bytes": 10117
+  },
+  "elapsed_seconds": 634.8051445484161
+}

tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory/agent_runs/gen_197_result.json

@@ -0,0 +1,23 @@
+{
+  "success": true,
+  "generation": 197,
+  "workspace": "/home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory",
+  "insights": [
+    "- The `aux_primary_eval_success_status` metric was also removed from the auxiliary_metrics.py file as it was not present in the Active Metric Registry and was redundant.",
+    "- REPLACE `aux_num_circles_valid_data` -> `aux_primary_error_source_type` (reason: Provides a critical, continuous signal (encoded as integers) about the type of error encountered during primary evaluation, directly addressing the problem of frequent 0.0000 scores by diagnosing the cause (Timeout, ValueError, Other). This moves from a count of valid circles to a direct diagnostic of failure modes.)",
+    "- The `aux_primary_error_source_type` metric will help in understanding why the primary score often becomes 0, guiding the evolution agent towards fixing root causes like `ValueError` (often indicative of LP solver issues due to poor input) or `TimeoutError`).",
+    "- REPLACE `aux_normalized_packing_density` -> `aux_num_effective_circles` (reason: Provides a more fundamental signal at this EXPLORATION stage, directly measuring the number of circles successfully contributing to the packing, which is crucial for moving away from 0.0000 scores. `aux_total_area_valid_data` already covers the area aspect.)",
+    "- This change aims to diagnose if the problem is in generating *any* circles with positive radii, which is a prerequisite for any meaningful packing.)",
+    "- REPLACE `aux_radius_std_dev` -> `aux_data_load_status` (reason: Provides a granular signal on the success/failure of loading and validating `extra.npz` data, crucial for diagnosing the root cause of 0.0 primary scores. It helps differentiate between 'no data', 'malformed data', and 'valid data with geometric problems').",
+    "- The code for `aux_normalized_packing_density` was removed from `auxiliary_metrics.py` as it was a retired metric not present in the active registry from `EVAL_AGENTS.md`.",
+    "- The `aux_data_load_status` metric encodes specific failure modes (e.g., npz not found, malformed content, incorrect number of circles) as continuous values, offering a clear gradient for guiding the `main.py` evolution towards producing correctly formatted data, which is a prerequisite for any meaningful geometric evaluation.",
+    "- REPLACE `aux_primary_error_source_type` (with refined logic that correctly identifies `TimeoutError` from the `primary_result` structure) and `aux_data_load_status` (to indicate when data loading cannot be assessed due to a primary timeout).",
+    "- The refinement of `aux_primary_error_source_type` and `aux_data_load_status` aims to provide more accurate diagnostic signals when the primary evaluation times out, allowing the evolution agent to better understand and address the instability in the primary score."
+  ],
+  "auxiliary_metrics": {
+    "auxiliary_metrics_file_exists": true,
+    "auxiliary_metrics_path": "/home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory/auxiliary_metrics.py",
+    "file_size_bytes": 9325
+  },
+  "elapsed_seconds": 84.1495292186737
+}

tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory/agent_runs/gen_25_result.json

@@ -0,0 +1,23 @@
+{
+  "success": true,
+  "generation": 25,
+  "workspace": "/home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory",
+  "insights": [
+    "- The new `aux_contact_density` metric will count both circle-wall and circle-circle contacts, offering a comprehensive measure of how \"jammed\" the system is, which directly correlates with packing efficiency.",
+    "- ADD `aux_packing_efficiency_area_ratio` (To measure how efficiently the space enclosed by the circle centers is utilized, indicating structural quality and absence of \"holes\").",
+    "- ADD `aux_min_pairwise_distance_normalized` (To quantify the smallest gap between any two circles, providing a direct signal on local packing tightness and remaining slack).",
+    "- REPLACE `aux_packing_efficiency_area_ratio` -> `aux_true_packing_efficiency` (This provides a direct measure of how well the unit square is filled, giving a clearer global efficiency signal.)",
+    "- ADD `aux_boundary_distance_min_normalized` (To identify circles that are tightly constrained by the container walls, providing a clear constraint tension signal.)",
+    "- ADD `aux_centroid_dispersion_std` (To measure how uniformly centers are distributed, aligning with strategies like Lloyd's Algorithm for better global exploration.)",
+    "- ADD `aux_radius_diversity_entropy` (To assess the uniformity of radii, helping to detect \"selfish components\" or unbalanced packings.)",
+    "- The new metrics aim to provide more granular insights into the packing structure, constraint tension, and distribution characteristics, which are crucial for navigating a plateau stage and escaping local optima.",
+    "- These metrics align with the evolution agent's strategy recommendations focusing on global seeding, pre-optimization, and structural relaxation.",
+    "- These metrics address the Structural Sensitivity and Constraint Tension pillars, providing continuous signals to guide the evolutionary agent towards denser and more uniform packings, especially relevant in the current OPTIMIZATION stage focused on refining solutions."
+  ],
+  "auxiliary_metrics": {
+    "auxiliary_metrics_file_exists": true,
+    "auxiliary_metrics_path": "/home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory/auxiliary_metrics.py",
+    "file_size_bytes": 8520
+  },
+  "elapsed_seconds": 69.86500215530396
+}

tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory/agent_runs/gen_30_result.json

@@ -0,0 +1,23 @@
+{
+  "success": true,
+  "generation": 30,
+  "workspace": "/home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory",
+  "insights": [
+    "- The new metrics aim to provide more granular insights into the packing structure, constraint tension, and distribution characteristics, which are crucial for navigating a plateau stage and escaping local optima.",
+    "- These metrics align with the evolution agent's strategy recommendations focusing on global seeding, pre-optimization, and structural relaxation.",
+    "- These metrics address the Structural Sensitivity and Constraint Tension pillars, providing continuous signals to guide the evolutionary agent towards denser and more uniform packings, especially relevant in the current OPTIMIZATION stage focused on refining solutions.",
+    "- DELETE `aux_min_radius_relative_to_avg` (Removed to adhere to the 10-metric limit, as it was redundant with `aux_min_radius_final` and `aux_average_radius`)",
+    "- REPLACE `aux_primary_eval_error` (functionally `aux_metric_eval_success`) -> `aux_largest_empty_circle_radius` (Replaced a stagnant diagnostic metric with a continuous signal of untapped void space, crucial for exploring new packing configurations and escaping local optima.)",
+    "- REPLACE `aux_min_boundary_clearance` (functionally `aux_boundary_distance_min_normalized`) -> `aux_avg_neighbor_distance_variance` (Replaced a stagnant constraint tension metric with a signal measuring the uniformity of local packing structure, guiding towards more ordered, potentially optimal, lattice arrangements.)",
+    "- The new metrics (`aux_largest_empty_circle_radius` and `aux_avg_neighbor_distance_variance`) directly address the need for structure-breaking signals and align with the meta-memory recommendations regarding Voronoi-based void analysis and lattice pattern generation. They are designed to provide continuous, actionable gradients during a plateau phase.",
+    "- NONE (The desired metric updates were implicitly applied by an intervening evolution step, resulting in a consistent set of 10 active metrics aligned with the strategy)",
+    "- The `auxiliary_metrics.py` file was found to have already incorporated advanced metrics like `aux_largest_empty_circle_radius` and `aux_avg_neighbor_distance_variance`, and introduced `aux_missing_extra_npz`, effectively addressing the identified needs for exploring void space, assessing local structure uniformity, and ensuring data integrity.",
+    "- The resulting set of 10 metrics (min radius, avg radius, normalized std dev radii, contact density, true packing efficiency, min pairwise distance, centroid dispersion, largest empty circle, avg neighbor variance, missing extra npz) is now comprehensive for driving optimization in a plateau stage."
+  ],
+  "auxiliary_metrics": {
+    "auxiliary_metrics_file_exists": true,
+    "auxiliary_metrics_path": "/home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory/auxiliary_metrics.py",
+    "file_size_bytes": 7946
+  },
+  "elapsed_seconds": 1042.564612865448
+}

tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory/agent_runs/gen_32_result.json

@@ -0,0 +1,23 @@
+{
+  "success": true,
+  "generation": 32,
+  "workspace": "/home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory",
+  "insights": [
+    "- ADD `aux_boundary_distance_min_normalized` (To identify circles that are tightly constrained by the container walls, providing a clear constraint tension signal.)",
+    "- ADD `aux_centroid_dispersion_std` (To measure how uniformly centers are distributed, aligning with strategies like Lloyd's Algorithm for better global exploration.)",
+    "- ADD `aux_radius_diversity_entropy` (To assess the uniformity of radii, helping to detect \"selfish components\" or unbalanced packings.)",
+    "- The new metrics aim to provide more granular insights into the packing structure, constraint tension, and distribution characteristics, which are crucial for navigating a plateau stage and escaping local optima.",
+    "- These metrics align with the evolution agent's strategy recommendations focusing on global seeding, pre-optimization, and structural relaxation.",
+    "- These metrics address the Structural Sensitivity and Constraint Tension pillars, providing continuous signals to guide the evolutionary agent towards denser and more uniform packings, especially relevant in the current OPTIMIZATION stage focused on refining solutions.",
+    "- DELETE `aux_min_radius_relative_to_avg` (Removed to adhere to the 10-metric limit, as it was redundant with `aux_min_radius_final` and `aux_average_radius`)",
+    "- REPLACE `aux_primary_eval_error` (functionally `aux_metric_eval_success`) -> `aux_largest_empty_circle_radius` (Replaced a stagnant diagnostic metric with a continuous signal of untapped void space, crucial for exploring new packing configurations and escaping local optima.)",
+    "- REPLACE `aux_min_boundary_clearance` (functionally `aux_boundary_distance_min_normalized`) -> `aux_avg_neighbor_distance_variance` (Replaced a stagnant constraint tension metric with a signal measuring the uniformity of local packing structure, guiding towards more ordered, potentially optimal, lattice arrangements.)",
+    "- The new metrics (`aux_largest_empty_circle_radius` and `aux_avg_neighbor_distance_variance`) directly address the need for structure-breaking signals and align with the meta-memory recommendations regarding Voronoi-based void analysis and lattice pattern generation. They are designed to provide continuous, actionable gradients during a plateau phase."
+  ],
+  "auxiliary_metrics": {
+    "auxiliary_metrics_file_exists": true,
+    "auxiliary_metrics_path": "/home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory/auxiliary_metrics.py",
+    "file_size_bytes": 7946
+  },
+  "elapsed_seconds": 94.84950184822083
+}

tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory/agent_runs/gen_37_result.json

@@ -0,0 +1,23 @@
+{
+  "success": true,
+  "generation": 37,
+  "workspace": "/home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory",
+  "insights": [
+    "- `aux_true_packing_efficiency`: Ratio of total circle area to the unit square area. A higher value indicates a denser packing within the container.",
+    "- `aux_min_pairwise_distance_normalized`: The minimum distance between any two circle centers, normalized by the sum of their radii. A value closer to zero (but positive) indicates tight packing between the closest pair of circles.",
+    "- `aux_centroid_dispersion_std`: The sum of the standard deviations of the X and Y coordinates of the circle centers. A lower value indicates a more clustered arrangement, while a higher value indicates a more spread-out distribution of centers.",
+    "- `aux_largest_empty_circle_radius`: The radius of the largest circle that can be placed in the unit square without overlapping existing circles or boundaries. High values indicate untapped potential space.",
+    "- `aux_avg_neighbor_distance_variance`: Average variance of distances to the K-nearest neighbors for each circle. Lower values indicate a more ordered, lattice-like structure.",
+    "- `aux_missing_extra_npz`: Binary flag indicating if `extra.npz` (containing circle data) was found (0.0 for found, 1.0 for missing).",
+    "- `aux_execution_timeout_flag`: Binary flag indicating if the primary evaluation timed out (1.0 for timeout, 0.0 otherwise).",
+    "- REPLACE `aux_normalized_std_dev_radii` -> `aux_execution_timeout_flag` (To directly signal and penalize solutions that time out, which is currently preventing valid primary scores. This prioritizes solutions that complete execution over those that might theoretically offer better uniformity but fail to produce a result within the given time constraints. This is a critical \"Search Velocity\" metric.)",
+    "- The introduction of `aux_execution_timeout_flag` will provide an explicit signal to the evolution agent to either refine its search strategy or adjust the complexity of generated solutions to ensure they complete within the allotted time.",
+    "- By prioritizing the completion of solutions, the agent can then leverage other packing-related metrics to guide the optimization towards higher quality packings."
+  ],
+  "auxiliary_metrics": {
+    "auxiliary_metrics_file_exists": true,
+    "auxiliary_metrics_path": "/home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory/auxiliary_metrics.py",
+    "file_size_bytes": 8591
+  },
+  "elapsed_seconds": 142.37665057182312
+}

tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory/agent_runs/gen_43_result.json

@@ -0,0 +1,23 @@
+{
+  "success": true,
+  "generation": 43,
+  "workspace": "/home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory",
+  "insights": [
+    "- `aux_missing_extra_npz`: Binary flag indicating if `extra.npz` (containing circle data) was found (0.0 for found, 1.0 for missing).",
+    "- `aux_execution_timeout_flag`: Binary flag indicating if the primary evaluation timed out (1.0 for timeout, 0.0 otherwise).",
+    "- DELETE `aux_contact_density` (Removed to make space for more critical overlap metrics and because its signal was less granular for diagnosing validity issues during exploration).",
+    "- REPLACE `aux_min_pairwise_distance_normalized` -> `aux_max_overlap_depth` (Provides a direct and continuous signal of the maximum depth of any overlap, addressing constraint tension more explicitly).",
+    "- ADD `aux_total_overlap_magnitude` (Quantifies the overall severity of overlaps, providing a comprehensive \"Constraint Tension\" signal).",
+    "- ADD `aux_radius_std_dev` (Measures the uniformity of circle radii, providing a \"Structural Sensitivity\" signal to detect if solutions are collapsing to highly non-uniform packings or if the optimizer is favoring specific sizes).",
+    "- The evolution agent needs clearer signals on constraint violations to move from generating invalid solutions (0.0 primary score) to valid, even if suboptimal, solutions.",
+    "- REPLACE `aux_normalized_std_dev_radii` -> `aux_execution_timeout_flag` (To directly signal and penalize solutions that time out, which is currently preventing valid primary scores. This prioritizes solutions that complete execution over those that might theoretically offer better uniformity but fail to produce a result within the given time constraints. This is a critical \"Search Velocity\" metric.)",
+    "- The introduction of `aux_execution_timeout_flag` will provide an explicit signal to the evolution agent to either refine its search strategy or adjust the complexity of generated solutions to ensure they complete within the allotted time.",
+    "- By prioritizing the completion of solutions, the agent can then leverage other packing-related metrics to guide the optimization towards higher quality packings."
+  ],
+  "auxiliary_metrics": {
+    "auxiliary_metrics_file_exists": true,
+    "auxiliary_metrics_path": "/home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory/auxiliary_metrics.py",
+    "file_size_bytes": 8273
+  },
+  "elapsed_seconds": 102.3455855846405
+}

tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory/agent_runs/gen_48_task_message.txt

@@ -0,0 +1,49 @@
+=== Generation 48 Evaluation ===
+
+📁 File Locations:
+- Results directory: /home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441
+- Memory: $RESULTS_DIR/eval_agent_memory/EVAL_AGENTS.md
+- Auxiliary metrics: $RESULTS_DIR/eval_agent_memory/auxiliary_metrics.py
+- All generations: $RESULTS_DIR/gen_0/ through gen_48/
+- Each generation has: main.py and results/metrics.json
+- Current code: $RESULTS_DIR/gen_48/main.py
+- Current metrics: $RESULTS_DIR/gen_48/results/metrics.json
+- Toolbox public API: eval_agent/tool_box/api.py
+- Toolbox reference template: eval_agent/templates/auxiliary_metrics_template.py
+- Current score: 2.6352
+
+⚠️  PRIMARY EVALUATOR (FIXED - DO NOT MODIFY):
+- Path: /home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/evaluate_ori.py
+- This file defines the GROUND TRUTH evaluation metric
+- The primary score comes from this evaluator
+- You MUST NOT modify or replace this evaluator
+- You can READ it to understand what is being optimized
+- Your job is to create AUXILIARY metrics that complement it
+
+🎯 Generation-Specific Focus (follow system prompt for full policy):
+1. Analyze progress up to generation 48 and diagnose current bottlenecks.
+2. Update auxiliary_metrics.py with this generation's metric set.
+   - Keep evaluate_aux as the single entry point and return a flat metric dict.
+   - Smoke-test metric execution on current generation artifacts before finishing.
+3. Update EVAL_AGENTS.md for this generation's actions and rationale.
+
+Use toolbox public APIs when needed:
+- from eval_agent.tool_box import call_vision, call_tool
+- Do NOT import eval_agent/tool_box/_internal/*
+
+📈 Combined Score Trend (previous up to 10 generations):
+- gen_38: 2.6306 | gen_39: 2.6353 | gen_40: 2.6297 | gen_41: 0.0000 | gen_42: 0.0000 | gen_43: 2.6353 | gen_44: 2.6281 | gen_45: 0.0000 | gen_46: 2.6353 | gen_47: 2.6216
+- Net change (gen_38 -> gen_47): -0.0090
+
+🧭 Evolution Agent Strategy Context (from meta memory):
+- Source: /home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/meta_memory.json
+- Current recommendations used by evolution agent:
+  1.  **Implement Voronoi-Based "Pop" Relocation**: Replace the approximate 60x60 grid search in `find_largest_void` with `scipy.spatial.Voronoi`. The vertices of the Voronoi diagram (clipped to the unit square bounds) represent the exact local maxima of distance from the current centers. Relocating the bottleneck circle to the best Voronoi vertex is computationally cheaper than a dense grid search and guarantees placing the circle in the geometrically optimal "hole," improving the efficiency of the pop heuristic.
+  2.  **Insert a Strict "Max-Min" Equal-Radius Phase**: Before the variable-radius optimization (currently handled by soft regularization), add a dedicated phase that maximizes a *single* scalar radius $R$ for all circles (the standard circle packing problem). Use `scipy.optimize.minimize` to maximize $R$ subject to non-overlap constraints. This establishes a "rigid" topological skeleton based on the best possible equal-circle packing, preventing the subsequent variable-radius solver from prematurely shrinking a circle to zero to resolve overlaps.
+  3.  **Algorithmic Lattice Pattern Generation**: Replace the hardcoded list of row patterns with a generator that exhaustively enumerates valid hexagonal packing sequences for $N=26$. Create a function that generates integer partitions of 26 into 4 to 7 rows where adjacent row lengths differ by at most 1 or 2. This ensures that the seed pool contains the specific lattice structure of the global optimum, which may be missing from the current manually curated list (e.g., `[6, 7, 6, 7]` or `[5, 6, 5, 5, 5]`).
+  4.  **Integrate Tabu Search with Basin Hopping**: Enhance the "Pop-and-Reinsert" loop by adding a short-term memory (Tabu list) that records the indices of recently moved circles. If circle $i$ is popped, prevent it from being chosen as the bottleneck again for the next 5-10 iterations. This forces the algorithm to perturb the surrounding "locking" circles rather than cyclically moving the same small circle back and forth between two voids.
+  5.  **Multi-Candidate Basin Hopping Strategy**: Instead of greedily selecting only the single best seed after the screening phase, select the top 3 candidate configurations (filtered for distinct topologies) to enter the Basin Hopping loop. Run the hopping process in parallel (or sequentially for fewer iterations) on these 3 candidates before converging on the final best. This mitigates the risk of discarding a seed that belongs to the optimal "basin of attraction" but had a slightly lower initial score due to lack of relaxation.
+- Latest recommendation updates since previous refresh:
+  1.  **Implement Voronoi-Based "Pop" Relocation**: Replace the approximate 60x60 grid search in `find_largest_void` with `scipy.spatial.Voronoi`. The vertices of the Voronoi diagram (clipped to the unit square bounds) represent the exact local maxima of distance from the current centers. Relocating the bottleneck circle to the best Voronoi vertex is computationally cheaper than a dense grid search and guarantees placing the circle in the geometrically optimal "hole," improving the efficiency of the pop heuristic.
+  2.  **Insert a Strict "Max-Min" Equal-Radius Phase**: Before the variable-radius optimization (currently handled by soft regularization), add a dedicated phase that maximizes a *single* scalar radius $R$ for all circles (the standard circle packing problem). Use `scipy.optimize.minimize` to maximize $R$ subject to non-overlap constraints. This establishes a "rigid" topological skeleton based on the best possible equal-circle packing, preventing the subsequent variable-radius solver from prematurely shrinking a circle to zero to resolve overlaps.
+  3.  **Algorithmic Lattice Pattern Generation**: Replace the hardcoded list of row patterns with a generator that exhaustively enumerates valid hexagonal packing sequences for $N=26$. Create a function that generates integer partitions of 26 into 4 to 7 rows where adjacent row lengths differ by at most 1 or 2. This ensures that the seed pool contains the specific lattice structure of the global optimum, which may be missing from the current manually curated list (e.g., `[6, 7, 6, 7]` or `[5, 6, 5, 5, 5]`).

tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory/agent_runs/gen_4_task_message.txt

@@ -0,0 +1,36 @@
+=== Generation 4 Evaluation ===
+
+📁 File Locations:
+- Results directory: /home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441
+- Memory: $RESULTS_DIR/eval_agent_memory/EVAL_AGENTS.md
+- Auxiliary metrics: $RESULTS_DIR/eval_agent_memory/auxiliary_metrics.py
+- All generations: $RESULTS_DIR/gen_0/ through gen_4/
+- Each generation has: main.py and results/metrics.json
+- Current code: $RESULTS_DIR/gen_4/main.py
+- Current metrics: $RESULTS_DIR/gen_4/results/metrics.json
+- Toolbox public API: eval_agent/tool_box/api.py
+- Toolbox reference template: eval_agent/templates/auxiliary_metrics_template.py
+- Current score: 2.6110
+
+⚠️  PRIMARY EVALUATOR (FIXED - DO NOT MODIFY):
+- Path: /home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/evaluate_ori.py
+- This file defines the GROUND TRUTH evaluation metric
+- The primary score comes from this evaluator
+- You MUST NOT modify or replace this evaluator
+- You can READ it to understand what is being optimized
+- Your job is to create AUXILIARY metrics that complement it
+
+🎯 Generation-Specific Focus (follow system prompt for full policy):
+1. Analyze progress up to generation 4 and diagnose current bottlenecks.
+2. Update auxiliary_metrics.py with this generation's metric set.
+   - Keep evaluate_aux as the single entry point and return a flat metric dict.
+   - Smoke-test metric execution on current generation artifacts before finishing.
+3. Update EVAL_AGENTS.md for this generation's actions and rationale.
+
+Use toolbox public APIs when needed:
+- from eval_agent.tool_box import call_vision, call_tool
+- Do NOT import eval_agent/tool_box/_internal/*
+
+📈 Combined Score Trend (previous up to 10 generations):
+- gen_0: 0.9598 | gen_1: 1.0181 | gen_2: 2.5886 | gen_3: N/A
+- Net change (gen_0 -> gen_2): +1.6288

tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory/agent_runs/gen_53_task_message.txt

@@ -0,0 +1,49 @@
+=== Generation 53 Evaluation ===
+
+📁 File Locations:
+- Results directory: /home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441
+- Memory: $RESULTS_DIR/eval_agent_memory/EVAL_AGENTS.md
+- Auxiliary metrics: $RESULTS_DIR/eval_agent_memory/auxiliary_metrics.py
+- All generations: $RESULTS_DIR/gen_0/ through gen_53/
+- Each generation has: main.py and results/metrics.json
+- Current code: $RESULTS_DIR/gen_53/main.py
+- Current metrics: $RESULTS_DIR/gen_53/results/metrics.json
+- Toolbox public API: eval_agent/tool_box/api.py
+- Toolbox reference template: eval_agent/templates/auxiliary_metrics_template.py
+- Current score: 2.6291
+
+⚠️  PRIMARY EVALUATOR (FIXED - DO NOT MODIFY):
+- Path: /home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/evaluate_ori.py
+- This file defines the GROUND TRUTH evaluation metric
+- The primary score comes from this evaluator
+- You MUST NOT modify or replace this evaluator
+- You can READ it to understand what is being optimized
+- Your job is to create AUXILIARY metrics that complement it
+
+🎯 Generation-Specific Focus (follow system prompt for full policy):
+1. Analyze progress up to generation 53 and diagnose current bottlenecks.
+2. Update auxiliary_metrics.py with this generation's metric set.
+   - Keep evaluate_aux as the single entry point and return a flat metric dict.
+   - Smoke-test metric execution on current generation artifacts before finishing.
+3. Update EVAL_AGENTS.md for this generation's actions and rationale.
+
+Use toolbox public APIs when needed:
+- from eval_agent.tool_box import call_vision, call_tool
+- Do NOT import eval_agent/tool_box/_internal/*
+
+📈 Combined Score Trend (previous up to 10 generations):
+- gen_43: 2.6353 | gen_44: 2.6281 | gen_45: 0.0000 | gen_46: 2.6353 | gen_47: 2.6216 | gen_48: 2.6352 | gen_49: 2.6353 | gen_50: 2.6353 | gen_51: 2.6356 | gen_52: 2.6242
+- Net change (gen_43 -> gen_52): -0.0111
+
+🧭 Evolution Agent Strategy Context (from meta memory):
+- Source: /home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/meta_memory.json
+- Current recommendations used by evolution agent:
+  1.  **Upgrade "Pop" Relocation with Voronoi Diagrams**: Replace the approximate 60x60 grid search in `find_largest_void` with `scipy.spatial.Voronoi` logic. Construct the Voronoi diagram of the current centers (excluding the popped circle) and select the vertex inside the unit square that maximizes the distance to the nearest neighbor. This provides the mathematically exact location of the largest void for reinsertion, surpassing the precision of the grid search without significantly increasing computational cost.
+  2.  **Insert a Strict "Max-Min" Equal-Radius Initialization**: Enhance the two-phase optimization by inserting a strict "Max-Min" phase before the variable-radius relaxation. Use `scipy.optimize.minimize` to maximize a *single* scalar variable $R$ (common radius) for all circles subject to non-overlap constraints. This establishes a rigid, optimal contact network (skeleton) typical of high-density packings, preventing the subsequent variable-radius solver from prematurely shrinking circles to resolve overlaps.
+  3.  **Algorithmic Hexagonal Pattern Generator**: Replace the hardcoded `patterns` list with a dynamic generator that enumerates valid hexagonal packing sequences for $N=26$. Implement a function to generate integer partitions of 26 into 4 to 7 rows where adjacent row lengths differ by at most 1 (or 2 for staggered shifts). This ensures the seed pool exhaustively covers all plausible lattice topologies, capturing potential optima that manually curated lists might miss.
+  4.  **Integrate Tabu Search Memory**: Augment the Basin Hopping loop with a "Tabu list" that records the indices of circles moved during the "Pop" step. Prevent a circle from being selected as the bottleneck again for the next 5-10 iterations. This prevents the algorithm from cyclically moving the same small circle back and forth between two sub-optimal voids, forcing it to perturb the surrounding "locking" circles to find a true escape path.
+  5.  **Multi-Candidate Basin Hopping Strategy**: Modify the `optimize` method to select the top 3 distinct candidates (rather than just the single best) after the initial screening phase. Run the intensive Basin Hopping/Pop-and-Reinsert process on all three candidates. This mitigates the risk of discarding a seed that lies in the global optimum's basin of attraction but scored slightly lower initially due to lack of relaxation.
+- Latest recommendation updates since previous refresh:
+  1.  **Upgrade "Pop" Relocation with Voronoi Diagrams**: Replace the approximate 60x60 grid search in `find_largest_void` with `scipy.spatial.Voronoi` logic. Construct the Voronoi diagram of the current centers (excluding the popped circle) and select the vertex inside the unit square that maximizes the distance to the nearest neighbor. This provides the mathematically exact location of the largest void for reinsertion, surpassing the precision of the grid search without significantly increasing computational cost.
+  2.  **Insert a Strict "Max-Min" Equal-Radius Initialization**: Enhance the two-phase optimization by inserting a strict "Max-Min" phase before the variable-radius relaxation. Use `scipy.optimize.minimize` to maximize a *single* scalar variable $R$ (common radius) for all circles subject to non-overlap constraints. This establishes a rigid, optimal contact network (skeleton) typical of high-density packings, preventing the subsequent variable-radius solver from prematurely shrinking circles to resolve overlaps.
+  3.  **Algorithmic Hexagonal Pattern Generator**: Replace the hardcoded `patterns` list with a dynamic generator that enumerates valid hexagonal packing sequences for $N=26$. Implement a function to generate integer partitions of 26 into 4 to 7 rows where adjacent row lengths differ by at most 1 (or 2 for staggered shifts). This ensures the seed pool exhaustively covers all plausible lattice topologies, capturing potential optima that manually curated lists might miss.

tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory/agent_runs/gen_58_result.json

@@ -0,0 +1,23 @@
+{
+  "success": true,
+  "generation": 58,
+  "workspace": "/home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory",
+  "insights": [
+    "- The focus is on re-invigorating the search by providing more sensitive metrics related to void space utilization and detecting potential imbalances in circle radii.",
+    "- The increase in `grid_size` for `aux_largest_empty_circle_radius` is an interim step to improve its sensitivity, acknowledging that a full Voronoi implementation is not feasible in this environment.",
+    "- DELETE `aux_contact_density` (Removed to make space for more critical overlap metrics and because its signal was less granular for diagnosing validity issues during exploration).",
+    "- REPLACE `aux_min_pairwise_distance_normalized` -> `aux_max_overlap_depth` (Provides a direct and continuous signal of the maximum depth of any overlap, addressing constraint tension more explicitly).",
+    "- ADD `aux_total_overlap_magnitude` (Quantifies the overall severity of overlaps, providing a comprehensive \"Constraint Tension\" signal).",
+    "- ADD `aux_radius_std_dev` (Measures the uniformity of circle radii, providing a \"Structural Sensitivity\" signal to detect if solutions are collapsing to highly non-uniform packings or if the optimizer is favoring specific sizes).",
+    "- The evolution agent needs clearer signals on constraint violations to move from generating invalid solutions (0.0 primary score) to valid, even if suboptimal, solutions.",
+    "- REPLACE `aux_normalized_std_dev_radii` -> `aux_execution_timeout_flag` (To directly signal and penalize solutions that time out, which is currently preventing valid primary scores. This prioritizes solutions that complete execution over those that might theoretically offer better uniformity but fail to produce a result within the given time constraints. This is a critical \"Search Velocity\" metric.)",
+    "- The introduction of `aux_execution_timeout_flag` will provide an explicit signal to the evolution agent to either refine its search strategy or adjust the complexity of generated solutions to ensure they complete within the allotted time.",
+    "- By prioritizing the completion of solutions, the agent can then leverage other packing-related metrics to guide the optimization towards higher quality packings."
+  ],
+  "auxiliary_metrics": {
+    "auxiliary_metrics_file_exists": true,
+    "auxiliary_metrics_path": "/home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory/auxiliary_metrics.py",
+    "file_size_bytes": 5888
+  },
+  "elapsed_seconds": 359.5924160480499
+}

tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory/agent_runs/gen_59_result.json

@@ -0,0 +1,23 @@
+{
+  "success": true,
+  "generation": 59,
+  "workspace": "/home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory",
+  "insights": [
+    "- The focus is on re-invigorating the search by providing more sensitive metrics related to void space utilization and detecting potential imbalances in circle radii.",
+    "- The increase in `grid_size` for `aux_largest_empty_circle_radius` is an interim step to improve its sensitivity, acknowledging that a full Voronoi implementation is not feasible in this environment.",
+    "- DELETE `aux_contact_density` (Removed to make space for more critical overlap metrics and because its signal was less granular for diagnosing validity issues during exploration).",
+    "- REPLACE `aux_min_pairwise_distance_normalized` -> `aux_max_overlap_depth` (Provides a direct and continuous signal of the maximum depth of any overlap, addressing constraint tension more explicitly).",
+    "- ADD `aux_total_overlap_magnitude` (Quantifies the overall severity of overlaps, providing a comprehensive \"Constraint Tension\" signal).",
+    "- ADD `aux_radius_std_dev` (Measures the uniformity of circle radii, providing a \"Structural Sensitivity\" signal to detect if solutions are collapsing to highly non-uniform packings or if the optimizer is favoring specific sizes).",
+    "- The evolution agent needs clearer signals on constraint violations to move from generating invalid solutions (0.0 primary score) to valid, even if suboptimal, solutions.",
+    "- REPLACE `aux_normalized_std_dev_radii` -> `aux_execution_timeout_flag` (To directly signal and penalize solutions that time out, which is currently preventing valid primary scores. This prioritizes solutions that complete execution over those that might theoretically offer better uniformity but fail to produce a result within the given time constraints. This is a critical \"Search Velocity\" metric.)",
+    "- The introduction of `aux_execution_timeout_flag` will provide an explicit signal to the evolution agent to either refine its search strategy or adjust the complexity of generated solutions to ensure they complete within the allotted time.",
+    "- By prioritizing the completion of solutions, the agent can then leverage other packing-related metrics to guide the optimization towards higher quality packings."
+  ],
+  "auxiliary_metrics": {
+    "auxiliary_metrics_file_exists": true,
+    "auxiliary_metrics_path": "/home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory/auxiliary_metrics.py",
+    "file_size_bytes": 7153
+  },
+  "elapsed_seconds": 122.06950116157532
+}

tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory/agent_runs/gen_59_task_message.txt

@@ -0,0 +1,49 @@
+=== Generation 59 Evaluation ===
+
+📁 File Locations:
+- Results directory: /home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441
+- Memory: $RESULTS_DIR/eval_agent_memory/EVAL_AGENTS.md
+- Auxiliary metrics: $RESULTS_DIR/eval_agent_memory/auxiliary_metrics.py
+- All generations: $RESULTS_DIR/gen_0/ through gen_59/
+- Each generation has: main.py and results/metrics.json
+- Current code: $RESULTS_DIR/gen_59/main.py
+- Current metrics: $RESULTS_DIR/gen_59/results/metrics.json
+- Toolbox public API: eval_agent/tool_box/api.py
+- Toolbox reference template: eval_agent/templates/auxiliary_metrics_template.py
+- Current score: 2.6353
+
+⚠️  PRIMARY EVALUATOR (FIXED - DO NOT MODIFY):
+- Path: /home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/evaluate_ori.py
+- This file defines the GROUND TRUTH evaluation metric
+- The primary score comes from this evaluator
+- You MUST NOT modify or replace this evaluator
+- You can READ it to understand what is being optimized
+- Your job is to create AUXILIARY metrics that complement it
+
+🎯 Generation-Specific Focus (follow system prompt for full policy):
+1. Analyze progress up to generation 59 and diagnose current bottlenecks.
+2. Update auxiliary_metrics.py with this generation's metric set.
+   - Keep evaluate_aux as the single entry point and return a flat metric dict.
+   - Smoke-test metric execution on current generation artifacts before finishing.
+3. Update EVAL_AGENTS.md for this generation's actions and rationale.
+
+Use toolbox public APIs when needed:
+- from eval_agent.tool_box import call_vision, call_tool
+- Do NOT import eval_agent/tool_box/_internal/*
+
+📈 Combined Score Trend (previous up to 10 generations):
+- gen_49: 2.6353 | gen_50: 2.6353 | gen_51: 2.6356 | gen_52: 2.6242 | gen_53: 2.6291 | gen_54: 0.0000 | gen_55: 2.6356 | gen_56: 0.0000 | gen_57: 0.0000 | gen_58: 2.6280
+- Net change (gen_49 -> gen_58): -0.0073
+
+🧭 Evolution Agent Strategy Context (from meta memory):
+- Source: /home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/meta_memory.json
+- Current recommendations used by evolution agent:
+  1.  **Upgrade "Pop" Relocation with Voronoi Diagrams**: Replace the approximate 60x60 grid search in `find_largest_void` with `scipy.spatial.Voronoi` logic. Construct the Voronoi diagram of the current centers (excluding the popped circle) and select the vertex inside the unit square that maximizes the distance to the nearest neighbor. This provides the mathematically exact location of the largest void for reinsertion, surpassing the precision of the grid search without significantly increasing computational cost.
+  2.  **Insert a Strict "Max-Min" Equal-Radius Initialization**: Enhance the two-phase optimization by inserting a strict "Max-Min" phase before the variable-radius relaxation. Use `scipy.optimize.minimize` to maximize a *single* scalar variable $R$ (common radius) for all circles subject to non-overlap constraints. This establishes a rigid, optimal contact network (skeleton) typical of high-density packings, preventing the subsequent variable-radius solver from prematurely shrinking circles to resolve overlaps.
+  3.  **Algorithmic Hexagonal Pattern Generator**: Replace the hardcoded `patterns` list with a dynamic generator that enumerates valid hexagonal packing sequences for $N=26$. Implement a function to generate integer partitions of 26 into 4 to 7 rows where adjacent row lengths differ by at most 1 (or 2 for staggered shifts). This ensures the seed pool exhaustively covers all plausible lattice topologies, capturing potential optima that manually curated lists might miss.
+  4.  **Integrate Tabu Search Memory**: Augment the Basin Hopping loop with a "Tabu list" that records the indices of circles moved during the "Pop" step. Prevent a circle from being selected as the bottleneck again for the next 5-10 iterations. This prevents the algorithm from cyclically moving the same small circle back and forth between two sub-optimal voids, forcing it to perturb the surrounding "locking" circles to find a true escape path.
+  5.  **Multi-Candidate Basin Hopping Strategy**: Modify the `optimize` method to select the top 3 distinct candidates (rather than just the single best) after the initial screening phase. Run the intensive Basin Hopping/Pop-and-Reinsert process on all three candidates. This mitigates the risk of discarding a seed that lies in the global optimum's basin of attraction but scored slightly lower initially due to lack of relaxation.
+- Latest recommendation updates since previous refresh:
+  1.  **Upgrade "Pop" Relocation with Voronoi Diagrams**: Replace the approximate 60x60 grid search in `find_largest_void` with `scipy.spatial.Voronoi` logic. Construct the Voronoi diagram of the current centers (excluding the popped circle) and select the vertex inside the unit square that maximizes the distance to the nearest neighbor. This provides the mathematically exact location of the largest void for reinsertion, surpassing the precision of the grid search without significantly increasing computational cost.
+  2.  **Insert a Strict "Max-Min" Equal-Radius Initialization**: Enhance the two-phase optimization by inserting a strict "Max-Min" phase before the variable-radius relaxation. Use `scipy.optimize.minimize` to maximize a *single* scalar variable $R$ (common radius) for all circles subject to non-overlap constraints. This establishes a rigid, optimal contact network (skeleton) typical of high-density packings, preventing the subsequent variable-radius solver from prematurely shrinking circles to resolve overlaps.
+  3.  **Algorithmic Hexagonal Pattern Generator**: Replace the hardcoded `patterns` list with a dynamic generator that enumerates valid hexagonal packing sequences for $N=26$. Implement a function to generate integer partitions of 26 into 4 to 7 rows where adjacent row lengths differ by at most 1 (or 2 for staggered shifts). This ensures the seed pool exhaustively covers all plausible lattice topologies, capturing potential optima that manually curated lists might miss.

tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory/agent_runs/gen_63_task_message.txt

@@ -0,0 +1,49 @@
+=== Generation 63 Evaluation ===
+
+📁 File Locations:
+- Results directory: /home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441
+- Memory: $RESULTS_DIR/eval_agent_memory/EVAL_AGENTS.md
+- Auxiliary metrics: $RESULTS_DIR/eval_agent_memory/auxiliary_metrics.py
+- All generations: $RESULTS_DIR/gen_0/ through gen_63/
+- Each generation has: main.py and results/metrics.json
+- Current code: $RESULTS_DIR/gen_63/main.py
+- Current metrics: $RESULTS_DIR/gen_63/results/metrics.json
+- Toolbox public API: eval_agent/tool_box/api.py
+- Toolbox reference template: eval_agent/templates/auxiliary_metrics_template.py
+- Current score: 2.6307
+
+⚠️  PRIMARY EVALUATOR (FIXED - DO NOT MODIFY):
+- Path: /home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/evaluate_ori.py
+- This file defines the GROUND TRUTH evaluation metric
+- The primary score comes from this evaluator
+- You MUST NOT modify or replace this evaluator
+- You can READ it to understand what is being optimized
+- Your job is to create AUXILIARY metrics that complement it
+
+🎯 Generation-Specific Focus (follow system prompt for full policy):
+1. Analyze progress up to generation 63 and diagnose current bottlenecks.
+2. Update auxiliary_metrics.py with this generation's metric set.
+   - Keep evaluate_aux as the single entry point and return a flat metric dict.
+   - Smoke-test metric execution on current generation artifacts before finishing.
+3. Update EVAL_AGENTS.md for this generation's actions and rationale.
+
+Use toolbox public APIs when needed:
+- from eval_agent.tool_box import call_vision, call_tool
+- Do NOT import eval_agent/tool_box/_internal/*
+
+📈 Combined Score Trend (previous up to 10 generations):
+- gen_53: 2.6291 | gen_54: 0.0000 | gen_55: 2.6356 | gen_56: 0.0000 | gen_57: 0.0000 | gen_58: 2.6280 | gen_59: 2.6353 | gen_60: 2.6357 | gen_61: 2.4480 | gen_62: 2.6295
+- Net change (gen_53 -> gen_62): +0.0004
+
+🧭 Evolution Agent Strategy Context (from meta memory):
+- Source: /home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/meta_memory.json
+- Current recommendations used by evolution agent:
+  1.  **Strict Equal-Radius "Skeleton" Phase**: Prior to the variable-radius optimization, insert a strict "Max-Min" optimization phase. Use `scipy.optimize.minimize` to maximize a *single* scalar variable $R$ (radius) shared by all circles, subject to non-overlap constraints. This forces the system to find the optimal rigid "skeleton" or contact graph for the given topology, preventing the variable-radius solver from prematurely shrinking circles to resolve overlaps and falling into poor local minima.
+  2.  **Automated Lattice Topology Generator**: Replace the manually curated `patterns` list with a recursive generator function that exhaustively enumerates valid hexagonal packing sequences for $N=26$. The generator should produce all integer partitions into 4 to 7 rows where adjacent row lengths differ by at most 1 (staggered) or 0 (aligned). This ensures the seed screening phase covers the entire combinatorial space of plausible high-density lattices.
+  3.  **Tabu Search Integration**: Enhance the Basin Hopping loop by adding a "Tabu list" that records the indices of circles moved during the "Pop" step. Prevent these specific circles from being selected as the bottleneck again for the next 5-10 iterations. This prevents the algorithm from endlessly cycling the same small circle between two sub-optimal voids, forcing it to perturb secondary bottlenecks and discover new contact networks.
+  4.  **Multi-Candidate Basin Hopping**: Modify the `optimize` strategy to select the **top 3 distinct candidates** (rather than just the single best) after the initial screening phase. Run the intensive Basin Hopping process on all three candidates. This is crucial because the global optimum often lies in the basin of a configuration that initially scores slightly lower (due to lack of relaxation) but has a superior underlying topology.
+  5.  **"Swap" Relocation Operator**: Introduce a "Swap" mutation (e.g., 10-20% probability) that exchanges the position of one of the smallest circles (highest pressure) with one of the largest circles (lowest pressure). Unlike the "Pop" move which targets empty voids, a "Swap" forces a large circle into a constrained spot (forcing neighbors to adjust) and moves a constrained circle to a free area, effectively inverting the local density distribution to escape traps.
+- Latest recommendation updates since previous refresh:
+  1.  **Strict Equal-Radius "Skeleton" Phase**: Prior to the variable-radius optimization, insert a strict "Max-Min" optimization phase. Use `scipy.optimize.minimize` to maximize a *single* scalar variable $R$ (radius) shared by all circles, subject to non-overlap constraints. This forces the system to find the optimal rigid "skeleton" or contact graph for the given topology, preventing the variable-radius solver from prematurely shrinking circles to resolve overlaps and falling into poor local minima.
+  2.  **Automated Lattice Topology Generator**: Replace the manually curated `patterns` list with a recursive generator function that exhaustively enumerates valid hexagonal packing sequences for $N=26$. The generator should produce all integer partitions into 4 to 7 rows where adjacent row lengths differ by at most 1 (staggered) or 0 (aligned). This ensures the seed screening phase covers the entire combinatorial space of plausible high-density lattices.
+  3.  **Tabu Search Integration**: Enhance the Basin Hopping loop by adding a "Tabu list" that records the indices of circles moved during the "Pop" step. Prevent these specific circles from being selected as the bottleneck again for the next 5-10 iterations. This prevents the algorithm from endlessly cycling the same small circle between two sub-optimal voids, forcing it to perturb secondary bottlenecks and discover new contact networks.

tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory/agent_runs/gen_64_result.json

@@ -0,0 +1,23 @@
+{
+  "success": true,
+  "generation": 64,
+  "workspace": "/home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory",
+  "insights": [
+    "- The focus is on re-invigorating the search by providing more sensitive metrics related to void space utilization and detecting potential imbalances in circle radii.",
+    "- The increase in `grid_size` for `aux_largest_empty_circle_radius` is an interim step to improve its sensitivity, acknowledging that a full Voronoi implementation is not feasible in this environment.",
+    "- DELETE `aux_contact_density` (Removed to make space for more critical overlap metrics and because its signal was less granular for diagnosing validity issues during exploration).",
+    "- REPLACE `aux_min_pairwise_distance_normalized` -> `aux_max_overlap_depth` (Provides a direct and continuous signal of the maximum depth of any overlap, addressing constraint tension more explicitly).",
+    "- ADD `aux_total_overlap_magnitude` (Quantifies the overall severity of overlaps, providing a comprehensive \"Constraint Tension\" signal).",
+    "- ADD `aux_radius_std_dev` (Measures the uniformity of circle radii, providing a \"Structural Sensitivity\" signal to detect if solutions are collapsing to highly non-uniform packings or if the optimizer is favoring specific sizes).",
+    "- The evolution agent needs clearer signals on constraint violations to move from generating invalid solutions (0.0 primary score) to valid, even if suboptimal, solutions.",
+    "- REPLACE `aux_normalized_std_dev_radii` -> `aux_execution_timeout_flag` (To directly signal and penalize solutions that time out, which is currently preventing valid primary scores. This prioritizes solutions that complete execution over those that might theoretically offer better uniformity but fail to produce a result within the given time constraints. This is a critical \"Search Velocity\" metric.)",
+    "- The introduction of `aux_execution_timeout_flag` will provide an explicit signal to the evolution agent to either refine its search strategy or adjust the complexity of generated solutions to ensure they complete within the allotted time.",
+    "- By prioritizing the completion of solutions, the agent can then leverage other packing-related metrics to guide the optimization towards higher quality packings."
+  ],
+  "auxiliary_metrics": {
+    "auxiliary_metrics_file_exists": true,
+    "auxiliary_metrics_path": "/home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory/auxiliary_metrics.py",
+    "file_size_bytes": 6684
+  },
+  "elapsed_seconds": 114.82505249977112
+}

tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory/agent_runs/gen_65_result.json

@@ -0,0 +1,23 @@
+{
+  "success": true,
+  "generation": 65,
+  "workspace": "/home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory",
+  "insights": [
+    "- The focus is on re-invigorating the search by providing more sensitive metrics related to void space utilization and detecting potential imbalances in circle radii.",
+    "- The increase in `grid_size` for `aux_largest_empty_circle_radius` is an interim step to improve its sensitivity, acknowledging that a full Voronoi implementation is not feasible in this environment.",
+    "- DELETE `aux_contact_density` (Removed to make space for more critical overlap metrics and because its signal was less granular for diagnosing validity issues during exploration).",
+    "- REPLACE `aux_min_pairwise_distance_normalized` -> `aux_max_overlap_depth` (Provides a direct and continuous signal of the maximum depth of any overlap, addressing constraint tension more explicitly).",
+    "- ADD `aux_total_overlap_magnitude` (Quantifies the overall severity of overlaps, providing a comprehensive \"Constraint Tension\" signal).",
+    "- ADD `aux_radius_std_dev` (Measures the uniformity of circle radii, providing a \"Structural Sensitivity\" signal to detect if solutions are collapsing to highly non-uniform packings or if the optimizer is favoring specific sizes).",
+    "- The evolution agent needs clearer signals on constraint violations to move from generating invalid solutions (0.0 primary score) to valid, even if suboptimal, solutions.",
+    "- REPLACE `aux_normalized_std_dev_radii` -> `aux_execution_timeout_flag` (To directly signal and penalize solutions that time out, which is currently preventing valid primary scores. This prioritizes solutions that complete execution over those that might theoretically offer better uniformity but fail to produce a result within the given time constraints. This is a critical \"Search Velocity\" metric.)",
+    "- The introduction of `aux_execution_timeout_flag` will provide an explicit signal to the evolution agent to either refine its search strategy or adjust the complexity of generated solutions to ensure they complete within the allotted time.",
+    "- By prioritizing the completion of solutions, the agent can then leverage other packing-related metrics to guide the optimization towards higher quality packings."
+  ],
+  "auxiliary_metrics": {
+    "auxiliary_metrics_file_exists": true,
+    "auxiliary_metrics_path": "/home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory/auxiliary_metrics.py",
+    "file_size_bytes": 7695
+  },
+  "elapsed_seconds": 134.18497681617737
+}

tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory/agent_runs/gen_70_result.json

@@ -0,0 +1,23 @@
+{
+  "success": true,
+  "generation": 70,
+  "workspace": "/home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory",
+  "insights": [
+    "- The focus is on re-invigorating the search by providing more sensitive metrics related to void space utilization and detecting potential imbalances in circle radii.",
+    "- The increase in `grid_size` for `aux_largest_empty_circle_radius` is an interim step to improve its sensitivity, acknowledging that a full Voronoi implementation is not feasible in this environment.",
+    "- DELETE `aux_contact_density` (Removed to make space for more critical overlap metrics and because its signal was less granular for diagnosing validity issues during exploration).",
+    "- REPLACE `aux_min_pairwise_distance_normalized` -> `aux_max_overlap_depth` (Provides a direct and continuous signal of the maximum depth of any overlap, addressing constraint tension more explicitly).",
+    "- ADD `aux_total_overlap_magnitude` (Quantifies the overall severity of overlaps, providing a comprehensive \"Constraint Tension\" signal).",
+    "- ADD `aux_radius_std_dev` (Measures the uniformity of circle radii, providing a \"Structural Sensitivity\" signal to detect if solutions are collapsing to highly non-uniform packings or if the optimizer is favoring specific sizes).",
+    "- The evolution agent needs clearer signals on constraint violations to move from generating invalid solutions (0.0 primary score) to valid, even if suboptimal, solutions.",
+    "- REPLACE `aux_normalized_std_dev_radii` -> `aux_execution_timeout_flag` (To directly signal and penalize solutions that time out, which is currently preventing valid primary scores. This prioritizes solutions that complete execution over those that might theoretically offer better uniformity but fail to produce a result within the given time constraints. This is a critical \"Search Velocity\" metric.)",
+    "- The introduction of `aux_execution_timeout_flag` will provide an explicit signal to the evolution agent to either refine its search strategy or adjust the complexity of generated solutions to ensure they complete within the allotted time.",
+    "- By prioritizing the completion of solutions, the agent can then leverage other packing-related metrics to guide the optimization towards higher quality packings."
+  ],
+  "auxiliary_metrics": {
+    "auxiliary_metrics_file_exists": true,
+    "auxiliary_metrics_path": "/home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory/auxiliary_metrics.py",
+    "file_size_bytes": 8482
+  },
+  "elapsed_seconds": 516.4304339885712
+}

tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory/agent_runs/gen_72_result.json

@@ -0,0 +1,12 @@
+{
+  "success": true,
+  "generation": 72,
+  "workspace": "/home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory",
+  "insights": [],
+  "auxiliary_metrics": {
+    "auxiliary_metrics_file_exists": true,
+    "auxiliary_metrics_path": "/home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory/auxiliary_metrics.py",
+    "file_size_bytes": 8482
+  },
+  "elapsed_seconds": 142.81096267700195
+}

tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory/agent_runs/gen_72_task_message.txt

@@ -0,0 +1,49 @@
+=== Generation 72 Evaluation ===
+
+📁 File Locations:
+- Results directory: /home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441
+- Memory: $RESULTS_DIR/eval_agent_memory/EVAL_AGENTS.md
+- Auxiliary metrics: $RESULTS_DIR/eval_agent_memory/auxiliary_metrics.py
+- All generations: $RESULTS_DIR/gen_0/ through gen_72/
+- Each generation has: main.py and results/metrics.json
+- Current code: $RESULTS_DIR/gen_72/main.py
+- Current metrics: $RESULTS_DIR/gen_72/results/metrics.json
+- Toolbox public API: eval_agent/tool_box/api.py
+- Toolbox reference template: eval_agent/templates/auxiliary_metrics_template.py
+- Current score: 2.4658
+
+⚠️  PRIMARY EVALUATOR (FIXED - DO NOT MODIFY):
+- Path: /home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/evaluate_ori.py
+- This file defines the GROUND TRUTH evaluation metric
+- The primary score comes from this evaluator
+- You MUST NOT modify or replace this evaluator
+- You can READ it to understand what is being optimized
+- Your job is to create AUXILIARY metrics that complement it
+
+🎯 Generation-Specific Focus (follow system prompt for full policy):
+1. Analyze progress up to generation 72 and diagnose current bottlenecks.
+2. Update auxiliary_metrics.py with this generation's metric set.
+   - Keep evaluate_aux as the single entry point and return a flat metric dict.
+   - Smoke-test metric execution on current generation artifacts before finishing.
+3. Update EVAL_AGENTS.md for this generation's actions and rationale.
+
+Use toolbox public APIs when needed:
+- from eval_agent.tool_box import call_vision, call_tool
+- Do NOT import eval_agent/tool_box/_internal/*
+
+📈 Combined Score Trend (previous up to 10 generations):
+- gen_62: 2.6295 | gen_63: 2.6307 | gen_64: 0.0000 | gen_65: 2.6145 | gen_66: 0.0000 | gen_67: 0.0000 | gen_68: 0.0000 | gen_69: 2.6284 | gen_70: 2.6355 | gen_71: 2.6155
+- Net change (gen_62 -> gen_71): -0.0140
+
+🧭 Evolution Agent Strategy Context (from meta memory):
+- Source: /home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/meta_memory.json
+- Current recommendations used by evolution agent:
+  1.  **Strict "Max-Min" Skeleton Optimization**: Replace the "soft" bias-to-equal regularization in the seed screening phase with a rigorous formulation. Use `scipy.optimize.minimize` to maximize a *single scalar variable* $R$ (radius) shared by all $N$ circles, subject to non-overlap constraints. This reduces the dimensionality of the problem and guarantees finding the optimal "hard sphere" contact network for a given topology before variable-radius relaxation begins, preventing early entrapment in local minima.
+  2.  **Automated Combinatorial Lattice Generator**: Replace the manually hardcoded `patterns` list with a recursive generator function. This function should exhaustively produce all valid staggered row combinations for $N=26$ (e.g., rows of lengths 4-7 summing to 26). This ensures the seed screening phase covers the entire combinatorial space of lattice-like packings, as the current list of 8 patterns likely misses the specific topology required for the global maximum.
+  3.  **Tabu Search Integration**: Enhance the Basin Hopping loop by implementing a short-term memory (Tabu list) of the last 3-5 moved circle indices. When selecting a circle to "Pop" (relocate), skip any index present in the Tabu list. This prevents the algorithm from cycling the same small circle between two suboptimal voids, forcing it to perturb secondary bottlenecks and discover new configuration basins.
+  4.  **Multi-Candidate Optimization Strategy**: Instead of committing to the single best seed immediately after the screening phase, select the **top 3 distinct candidates**. Run the computationally intensive Basin Hopping procedure on all three. The global optimum often lies in the basin of a configuration that initially scores slightly lower due to imperfect geometric relaxation, but possesses a superior underlying topology that only reveals itself after extensive perturbation.
+  5.  **"Swap" Mutation Operator**: Introduce a "Swap" move (e.g., with 15% probability) alongside the existing "Pop" and "Jitter" moves. This operator should exchange the positions of a highly constrained circle (bottom 10% radius) with a loosely constrained one (top 10% radius). Unlike "Pop," which requires an empty void, "Swap" allows the algorithm to correct density imbalances in fully packed configurations where no clear voids exist.
+- Latest recommendation updates since previous refresh:
+  1.  **Strict "Max-Min" Skeleton Optimization**: Replace the "soft" bias-to-equal regularization in the seed screening phase with a rigorous formulation. Use `scipy.optimize.minimize` to maximize a *single scalar variable* $R$ (radius) shared by all $N$ circles, subject to non-overlap constraints. This reduces the dimensionality of the problem and guarantees finding the optimal "hard sphere" contact network for a given topology before variable-radius relaxation begins, preventing early entrapment in local minima.
+  2.  **Automated Combinatorial Lattice Generator**: Replace the manually hardcoded `patterns` list with a recursive generator function. This function should exhaustively produce all valid staggered row combinations for $N=26$ (e.g., rows of lengths 4-7 summing to 26). This ensures the seed screening phase covers the entire combinatorial space of lattice-like packings, as the current list of 8 patterns likely misses the specific topology required for the global maximum.
+  3.  **Tabu Search Integration**: Enhance the Basin Hopping loop by implementing a short-term memory (Tabu list) of the last 3-5 moved circle indices. When selecting a circle to "Pop" (relocate), skip any index present in the Tabu list. This prevents the algorithm from cycling the same small circle between two suboptimal voids, forcing it to perturb secondary bottlenecks and discover new configuration basins.

tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory/agent_runs/gen_75_task_message.txt

@@ -0,0 +1,49 @@
+=== Generation 75 Evaluation ===
+
+📁 File Locations:
+- Results directory: /home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441
+- Memory: $RESULTS_DIR/eval_agent_memory/EVAL_AGENTS.md
+- Auxiliary metrics: $RESULTS_DIR/eval_agent_memory/auxiliary_metrics.py
+- All generations: $RESULTS_DIR/gen_0/ through gen_75/
+- Each generation has: main.py and results/metrics.json
+- Current code: $RESULTS_DIR/gen_75/main.py
+- Current metrics: $RESULTS_DIR/gen_75/results/metrics.json
+- Toolbox public API: eval_agent/tool_box/api.py
+- Toolbox reference template: eval_agent/templates/auxiliary_metrics_template.py
+- Current score: 2.6317
+
+⚠️  PRIMARY EVALUATOR (FIXED - DO NOT MODIFY):
+- Path: /home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/evaluate_ori.py
+- This file defines the GROUND TRUTH evaluation metric
+- The primary score comes from this evaluator
+- You MUST NOT modify or replace this evaluator
+- You can READ it to understand what is being optimized
+- Your job is to create AUXILIARY metrics that complement it
+
+🎯 Generation-Specific Focus (follow system prompt for full policy):
+1. Analyze progress up to generation 75 and diagnose current bottlenecks.
+2. Update auxiliary_metrics.py with this generation's metric set.
+   - Keep evaluate_aux as the single entry point and return a flat metric dict.
+   - Smoke-test metric execution on current generation artifacts before finishing.
+3. Update EVAL_AGENTS.md for this generation's actions and rationale.
+
+Use toolbox public APIs when needed:
+- from eval_agent.tool_box import call_vision, call_tool
+- Do NOT import eval_agent/tool_box/_internal/*
+
+📈 Combined Score Trend (previous up to 10 generations):
+- gen_65: 2.6145 | gen_66: 0.0000 | gen_67: 0.0000 | gen_68: 0.0000 | gen_69: 2.6284 | gen_70: 2.6355 | gen_71: 2.6155 | gen_72: 2.4658 | gen_73: 2.6165 | gen_74: 2.4304
+- Net change (gen_65 -> gen_74): -0.1841
+
+🧭 Evolution Agent Strategy Context (from meta memory):
+- Source: /home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/meta_memory.json
+- Current recommendations used by evolution agent:
+  1.  **Strict "Max-Min" Skeleton Optimization**: Replace the "soft" bias-to-equal regularization in the seed screening phase with a rigorous formulation. Use `scipy.optimize.minimize` to maximize a *single scalar variable* $R$ (radius) shared by all $N$ circles, subject to non-overlap constraints. This reduces the dimensionality of the problem and guarantees finding the optimal "hard sphere" contact network for a given topology before variable-radius relaxation begins, preventing early entrapment in local minima.
+  2.  **Automated Combinatorial Lattice Generator**: Replace the manually hardcoded `patterns` list with a recursive generator function. This function should exhaustively produce all valid staggered row combinations for $N=26$ (e.g., rows of lengths 4-7 summing to 26). This ensures the seed screening phase covers the entire combinatorial space of lattice-like packings, as the current list of 8 patterns likely misses the specific topology required for the global maximum.
+  3.  **Tabu Search Integration**: Enhance the Basin Hopping loop by implementing a short-term memory (Tabu list) of the last 3-5 moved circle indices. When selecting a circle to "Pop" (relocate), skip any index present in the Tabu list. This prevents the algorithm from cycling the same small circle between two suboptimal voids, forcing it to perturb secondary bottlenecks and discover new configuration basins.
+  4.  **Multi-Candidate Optimization Strategy**: Instead of committing to the single best seed immediately after the screening phase, select the **top 3 distinct candidates**. Run the computationally intensive Basin Hopping procedure on all three. The global optimum often lies in the basin of a configuration that initially scores slightly lower due to imperfect geometric relaxation, but possesses a superior underlying topology that only reveals itself after extensive perturbation.
+  5.  **"Swap" Mutation Operator**: Introduce a "Swap" move (e.g., with 15% probability) alongside the existing "Pop" and "Jitter" moves. This operator should exchange the positions of a highly constrained circle (bottom 10% radius) with a loosely constrained one (top 10% radius). Unlike "Pop," which requires an empty void, "Swap" allows the algorithm to correct density imbalances in fully packed configurations where no clear voids exist.
+- Latest recommendation updates since previous refresh:
+  1.  **Strict "Max-Min" Skeleton Optimization**: Replace the "soft" bias-to-equal regularization in the seed screening phase with a rigorous formulation. Use `scipy.optimize.minimize` to maximize a *single scalar variable* $R$ (radius) shared by all $N$ circles, subject to non-overlap constraints. This reduces the dimensionality of the problem and guarantees finding the optimal "hard sphere" contact network for a given topology before variable-radius relaxation begins, preventing early entrapment in local minima.
+  2.  **Automated Combinatorial Lattice Generator**: Replace the manually hardcoded `patterns` list with a recursive generator function. This function should exhaustively produce all valid staggered row combinations for $N=26$ (e.g., rows of lengths 4-7 summing to 26). This ensures the seed screening phase covers the entire combinatorial space of lattice-like packings, as the current list of 8 patterns likely misses the specific topology required for the global maximum.
+  3.  **Tabu Search Integration**: Enhance the Basin Hopping loop by implementing a short-term memory (Tabu list) of the last 3-5 moved circle indices. When selecting a circle to "Pop" (relocate), skip any index present in the Tabu list. This prevents the algorithm from cycling the same small circle between two suboptimal voids, forcing it to perturb secondary bottlenecks and discover new configuration basins.

tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory/agent_runs/gen_76_result.json

@@ -0,0 +1,23 @@
+{
+  "success": true,
+  "generation": 76,
+  "workspace": "/home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory",
+  "insights": [
+    "- The focus is on re-invigorating the search by providing more sensitive metrics related to void space utilization and detecting potential imbalances in circle radii.",
+    "- The increase in `grid_size` for `aux_largest_empty_circle_radius` is an interim step to improve its sensitivity, acknowledging that a full Voronoi implementation is not feasible in this environment.",
+    "- DELETE `aux_contact_density` (Removed to make space for more critical overlap metrics and because its signal was less granular for diagnosing validity issues during exploration).",
+    "- REPLACE `aux_min_pairwise_distance_normalized` -> `aux_max_overlap_depth` (Provides a direct and continuous signal of the maximum depth of any overlap, addressing constraint tension more explicitly).",
+    "- ADD `aux_total_overlap_magnitude` (Quantifies the overall severity of overlaps, providing a comprehensive \"Constraint Tension\" signal).",
+    "- ADD `aux_radius_std_dev` (Measures the uniformity of circle radii, providing a \"Structural Sensitivity\" signal to detect if solutions are collapsing to highly non-uniform packings or if the optimizer is favoring specific sizes).",
+    "- The evolution agent needs clearer signals on constraint violations to move from generating invalid solutions (0.0 primary score) to valid, even if suboptimal, solutions.",
+    "- REPLACE `aux_normalized_std_dev_radii` -> `aux_execution_timeout_flag` (To directly signal and penalize solutions that time out, which is currently preventing valid primary scores. This prioritizes solutions that complete execution over those that might theoretically offer better uniformity but fail to produce a result within the given time constraints. This is a critical \"Search Velocity\" metric.)",
+    "- The introduction of `aux_execution_timeout_flag` will provide an explicit signal to the evolution agent to either refine its search strategy or adjust the complexity of generated solutions to ensure they complete within the allotted time.",
+    "- By prioritizing the completion of solutions, the agent can then leverage other packing-related metrics to guide the optimization towards higher quality packings."
+  ],
+  "auxiliary_metrics": {
+    "auxiliary_metrics_file_exists": true,
+    "auxiliary_metrics_path": "/home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory/auxiliary_metrics.py",
+    "file_size_bytes": 9029
+  },
+  "elapsed_seconds": 1102.3003907203674
+}

tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory/agent_runs/gen_83_result.json

@@ -0,0 +1,23 @@
+{
+  "success": true,
+  "generation": 83,
+  "workspace": "/home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory",
+  "insights": [
+    "- The focus is on re-invigorating the search by providing more sensitive metrics related to void space utilization and detecting potential imbalances in circle radii.",
+    "- The increase in `grid_size` for `aux_largest_empty_circle_radius` is an interim step to improve its sensitivity, acknowledging that a full Voronoi implementation is not feasible in this environment.",
+    "- DELETE `aux_contact_density` (Removed to make space for more critical overlap metrics and because its signal was less granular for diagnosing validity issues during exploration).",
+    "- REPLACE `aux_min_pairwise_distance_normalized` -> `aux_max_overlap_depth` (Provides a direct and continuous signal of the maximum depth of any overlap, addressing constraint tension more explicitly).",
+    "- ADD `aux_total_overlap_magnitude` (Quantifies the overall severity of overlaps, providing a comprehensive \"Constraint Tension\" signal).",
+    "- ADD `aux_radius_std_dev` (Measures the uniformity of circle radii, providing a \"Structural Sensitivity\" signal to detect if solutions are collapsing to highly non-uniform packings or if the optimizer is favoring specific sizes).",
+    "- The evolution agent needs clearer signals on constraint violations to move from generating invalid solutions (0.0 primary score) to valid, even if suboptimal, solutions.",
+    "- REPLACE `aux_normalized_std_dev_radii` -> `aux_execution_timeout_flag` (To directly signal and penalize solutions that time out, which is currently preventing valid primary scores. This prioritizes solutions that complete execution over those that might theoretically offer better uniformity but fail to produce a result within the given time constraints. This is a critical \"Search Velocity\" metric.)",
+    "- The introduction of `aux_execution_timeout_flag` will provide an explicit signal to the evolution agent to either refine its search strategy or adjust the complexity of generated solutions to ensure they complete within the allotted time.",
+    "- By prioritizing the completion of solutions, the agent can then leverage other packing-related metrics to guide the optimization towards higher quality packings."
+  ],
+  "auxiliary_metrics": {
+    "auxiliary_metrics_file_exists": true,
+    "auxiliary_metrics_path": "/home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory/auxiliary_metrics.py",
+    "file_size_bytes": 7704
+  },
+  "elapsed_seconds": 200.30852937698364
+}

tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/eval_agent_memory/agent_runs/gen_83_task_message.txt

@@ -0,0 +1,49 @@
+=== Generation 83 Evaluation ===
+
+📁 File Locations:
+- Results directory: /home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441
+- Memory: $RESULTS_DIR/eval_agent_memory/EVAL_AGENTS.md
+- Auxiliary metrics: $RESULTS_DIR/eval_agent_memory/auxiliary_metrics.py
+- All generations: $RESULTS_DIR/gen_0/ through gen_83/
+- Each generation has: main.py and results/metrics.json
+- Current code: $RESULTS_DIR/gen_83/main.py
+- Current metrics: $RESULTS_DIR/gen_83/results/metrics.json
+- Toolbox public API: eval_agent/tool_box/api.py
+- Toolbox reference template: eval_agent/templates/auxiliary_metrics_template.py
+- Current score: 2.6244
+
+⚠️  PRIMARY EVALUATOR (FIXED - DO NOT MODIFY):
+- Path: /home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/evaluate_ori.py
+- This file defines the GROUND TRUTH evaluation metric
+- The primary score comes from this evaluator
+- You MUST NOT modify or replace this evaluator
+- You can READ it to understand what is being optimized
+- Your job is to create AUXILIARY metrics that complement it
+
+🎯 Generation-Specific Focus (follow system prompt for full policy):
+1. Analyze progress up to generation 83 and diagnose current bottlenecks.
+2. Update auxiliary_metrics.py with this generation's metric set.
+   - Keep evaluate_aux as the single entry point and return a flat metric dict.
+   - Smoke-test metric execution on current generation artifacts before finishing.
+3. Update EVAL_AGENTS.md for this generation's actions and rationale.
+
+Use toolbox public APIs when needed:
+- from eval_agent.tool_box import call_vision, call_tool
+- Do NOT import eval_agent/tool_box/_internal/*
+
+📈 Combined Score Trend (previous up to 10 generations):
+- gen_73: 2.6165 | gen_74: 2.4304 | gen_75: 2.6317 | gen_76: 2.6352 | gen_77: 2.6356 | gen_78: 0.0000 | gen_79: 2.6356 | gen_80: 0.0000 | gen_81: 2.4426 | gen_82: 0.0000
+- Net change (gen_73 -> gen_82): -2.6165
+
+🧭 Evolution Agent Strategy Context (from meta memory):
+- Source: /home/tengxiao/pj/ShinkaEvolve/tasks/circle_packing/results/results_circle_packing_v3_g200_periodic5_20260302_084441/meta_memory.json
+- Current recommendations used by evolution agent:
+  1.  **Exhaustive Lattice Topology Generator**: Replace the manually hardcoded `patterns` list with a recursive generator function that produces all valid staggered row combinations for $N=26$ (e.g., rows of lengths 3-8 summing to 26). The current best program relies on a small fixed list of 8 patterns; exhaustively generating these "crystal" seeds guarantees that the specific topological structure required for the global maximum is included in the screening phase.
+  2.  **Strict "Hard-Sphere" Skeleton Solver**: Refine the seed screening phase to optimize a *single scalar radius* $R$ shared by all circles (maximizing $R$ subject to non-overlap), rather than optimizing individual radii with a soft penalty for variance. This strict formulation reduces the dimensionality of the problem and prevents the optimizer from "cheating" with variable radii early on, ensuring the topological basins are ranked accurately before complex relaxation begins.
+  3.  **Multi-Stream Basin Hopping**: Instead of greedily selecting only the single best seed after the screening phase, select the **top 3 distinct candidates** and run the Basin Hopping procedure on all of them (splitting the iteration budget if necessary). The global optimum often lies in a basin that scores slightly lower initially due to imperfect geometric relaxation; processing multiple candidates prevents premature convergence to a suboptimal topology.
+  4.  **Radius-Based "Swap" Mutation**: Introduce a "Swap" operator (e.g., with 15% probability) to the Basin Hopping loop that exchanges the position of a bottleneck circle (smallest radius) with a non-critical circle (largest radius). Unlike the "Pop" move which relies on finding an empty void, a "Swap" can correct density imbalances in fully packed configurations where no clear voids exist, allowing for radius equalization in dense regimes.
+  5.  **Explicit Tabu List**: Upgrade the stochastic bottleneck selection to use an explicit **Tabu list** of the last 3-5 moved circle indices. By strictly forbidding the relocation of recently moved circles, the algorithm is forced to perturb secondary bottlenecks and explore new areas of the configuration space, preventing the "limit cycles" where the same circle is repeatedly popped back and forth between two local minima.
+- Latest recommendation updates since previous refresh:
+  1.  **Exhaustive Lattice Topology Generator**: Replace the manually hardcoded `patterns` list with a recursive generator function that produces all valid staggered row combinations for $N=26$ (e.g., rows of lengths 3-8 summing to 26). The current best program relies on a small fixed list of 8 patterns; exhaustively generating these "crystal" seeds guarantees that the specific topological structure required for the global maximum is included in the screening phase.
+  2.  **Strict "Hard-Sphere" Skeleton Solver**: Refine the seed screening phase to optimize a *single scalar radius* $R$ shared by all circles (maximizing $R$ subject to non-overlap), rather than optimizing individual radii with a soft penalty for variance. This strict formulation reduces the dimensionality of the problem and prevents the optimizer from "cheating" with variable radii early on, ensuring the topological basins are ranked accurately before complex relaxation begins.
+  3.  **Multi-Stream Basin Hopping**: Instead of greedily selecting only the single best seed after the screening phase, select the **top 3 distinct candidates** and run the Basin Hopping procedure on all of them (splitting the iteration budget if necessary). The global optimum often lies in a basin that scores slightly lower initially due to imperfect geometric relaxation; processing multiple candidates prevents premature convergence to a suboptimal topology.