diff --git a/.gitmodules b/.gitmodules
new file mode 100644
index 0000000..0f82088
--- /dev/null
+++ b/.gitmodules
@@ -0,0 +1,3 @@
+[submodule "ogbench"]
+	path = ogbench
+	url = ./ogbench
diff --git a/.vscode/launch.json b/.vscode/launch.json
new file mode 100644
index 0000000..690053b
--- /dev/null
+++ b/.vscode/launch.json
@@ -0,0 +1,21 @@
+{
+    // Use IntelliSense to learn about possible attributes.
+    // Hover to view descriptions of existing attributes.
+    // For more information, visit: https://go.microsoft.com/fwlink/?linkid=830387
+    "version": "0.2.0",
+    "configurations": [
+        {
+            "name": "Python Debugger: Current File",
+            "type": "debugpy",
+            "request": "launch",
+            "program": "${file}",
+            "console": "integratedTerminal",
+            // add python paths
+            "env": {
+                "PYTHONPATH": "${workspaceFolder}/ogbench:${workspaceFolder}/ogbench/ogbench:${workspaceFolder}/ogbench/ogbench/procgen"
+            }
+
+        },
+
+    ]
+}
\ No newline at end of file
diff --git a/ogbench b/ogbench
new file mode 160000
index 0000000..d750941
--- /dev/null
+++ b/ogbench
@@ -0,0 +1 @@
+Subproject commit d7509418e7a2243ebea3c5fc081ed57557e89719
diff --git a/prompts/__init__.py b/prompts/__init__.py
new file mode 100644
index 0000000..80835a2
--- /dev/null
+++ b/prompts/__init__.py
@@ -0,0 +1,5 @@
+"""Prompt condition sets for maze evaluation experiments."""
+
+from .exp_design import CONDITION_SETS
+
+__all__ = ["CONDITION_SETS"]
diff --git a/prompts/__pycache__/__init__.cpython-312.pyc b/prompts/__pycache__/__init__.cpython-312.pyc
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diff --git a/prompts/__pycache__/condition_set_1_prompt.cpython-312.pyc b/prompts/__pycache__/condition_set_1_prompt.cpython-312.pyc
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diff --git a/prompts/__pycache__/condition_set_6_in_context_learning.cpython-312.pyc b/prompts/__pycache__/condition_set_6_in_context_learning.cpython-312.pyc
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diff --git a/prompts/condition_set_1_prompt.py b/prompts/condition_set_1_prompt.py
new file mode 100644
index 0000000..947e3b6
--- /dev/null
+++ b/prompts/condition_set_1_prompt.py
@@ -0,0 +1,63 @@
+"""Condition set 1: prompt verbosity."""
+
+STANDARD_PROMPT = """You are the red triangular agent solving a maze. Your mission is to navigate to the green square.
+
+mechanisms present:
+{MAZE_SPECIFIC_MECHS}
+
+Available actions:
+{DOMAIN_SPECIFIC_ACTION_LIST}
+
+Current observation:
+{DOMAIN_SPECIFIC_OBSERVATION} # image for 2D and 3D; NL for NL
+
+Inventory:
+{INVENTORY}
+
+Choose exactly ONE action to take from the available actions.
+
+Output only the action name.
+"""
+
+EXPLICIT_PROMPT = """You are the red triangular agent solving a maze. Your mission is to navigate to the green square.
+
+mechanisms present:
+{MAZE_SPECIFIC_MECHS}
+
+Detailed rules:
+1. Keys only open doors with matching colors.
+2. Keys are consumed immediately after opening a matching door.
+3. Opened doors remain open permanently.
+4. Switches toggle associated gates between open and closed states.
+5. Walls and closed doors cannot be crossed.
+6. The agent occupies exactly one cell at a time.
+7. Invalid actions do not help progress toward the goal.
+
+Available actions:
+{DOMAIN_SPECIFIC_ACTION_LIST}
+
+Current observation:
+{DOMAIN_SPECIFIC_OBSERVATION}
+
+Inventory:
+{INVENTORY}
+
+Choose exactly ONE action to take from the available actions.
+
+Output only the action name.
+"""
+
+CONDITION_SET = {
+	"name": "Prompt",
+	"comparisons": [
+		"Standard: goal + mechanism descriptions + action list",
+		"Verbose: Standard + explicit rules",
+	],
+	"decision": "If delta < 5%, use Standard. If > 5%, use Verbose.",
+	"prompts": {
+		"standard": STANDARD_PROMPT,
+		"explicit": EXPLICIT_PROMPT,
+	},
+}
+
+PROMPTS = CONDITION_SET["prompts"]
diff --git a/prompts/condition_set_2_observation_format.py b/prompts/condition_set_2_observation_format.py
new file mode 100644
index 0000000..070aaad
--- /dev/null
+++ b/prompts/condition_set_2_observation_format.py
@@ -0,0 +1,39 @@
+"""Condition set 2: observation format."""
+
+from .condition_set_1_prompt import STANDARD_PROMPT
+
+IMAGE_PLUS_TEXT_PROMPT = STANDARD_PROMPT
+
+IMAGE_ONLY_PROMPT = """You are the red triangular agent solving a maze. Your mission is to navigate to the green square.
+
+mechanisms present:
+{MAZE_SPECIFIC_MECHS}
+
+Available actions:
+{DOMAIN_SPECIFIC_ACTION_LIST}
+
+Current observation:
+{DOMAIN_SPECIFIC_OBSERVATION}
+
+Inventory:
+{INVENTORY}
+
+Choose exactly ONE action to take from the available actions.
+
+Output only the action name.
+"""
+
+CONDITION_SET = {
+	"name": "Observation format",
+	"comparisons": [
+		"Image + text prompt",
+		"Image only (no text)",
+	],
+	"decision": "Does text add meaningful signal?",
+	"prompts": {
+		"image_plus_text": IMAGE_PLUS_TEXT_PROMPT,
+		"image_only": IMAGE_ONLY_PROMPT,
+	},
+}
+
+PROMPTS = CONDITION_SET["prompts"]
diff --git a/prompts/condition_set_3_context_window.py b/prompts/condition_set_3_context_window.py
new file mode 100644
index 0000000..3d45331
--- /dev/null
+++ b/prompts/condition_set_3_context_window.py
@@ -0,0 +1,69 @@
+"""Condition set 3: context window."""
+
+HISTORY_PROMPT = """You are the red triangular agent solving a maze. Your mission is to navigate to the green square.
+
+mechanisms present:
+{MAZE_SPECIFIC_MECHS}
+
+Available actions:
+{DOMAIN_SPECIFIC_ACTION_LIST}
+
+Observation history:
+
+Frame t-2:
+{FRAME_T_MINUS_2}
+
+Frame t-1:
+{FRAME_T_MINUS_1}
+
+Current frame:
+{CURRENT_FRAME}
+
+Inventory:
+{INVENTORY}
+
+Choose exactly ONE action to take from the available actions.
+
+Output only the action name.
+"""
+
+TEXT_SUMMARY_PROMPT = """You are the red triangular agent solving a maze. Your mission is to navigate to the green square.
+
+mechanisms present:
+{MAZE_SPECIFIC_MECHS}
+
+Available actions:
+{DOMAIN_SPECIFIC_ACTION_LIST}
+
+Current observation:
+{CURRENT_FRAME}
+
+Exploration summary:
+{MECHANISMS_INTERACTED_WITH}.{SUBGOALS_ACHIEVED}.{PATH_IN_LAST_10_FRAMES}.
+# Example: you've interacted with the yellow key and the yellow door.
+# You've opened the yellow door.
+# In the last 10 frames, you've traveled from [1, 1] to [1, 10]
+
+Inventory:
+{INVENTORY}
+
+Choose exactly ONE action to take from the available actions.
+
+Output only the action name.
+"""
+
+CONDITION_SET = {
+	"name": "Context window",
+	"comparisons": [
+		"0 history (current frame only)",
+		"Last 3 frames",
+		"Current frame + text summary of prior actions",
+	],
+	"decision": "Is there a cheap alternative to feeding multiple frames?",
+	"prompts": {
+		"history": HISTORY_PROMPT,
+		"text_summary": TEXT_SUMMARY_PROMPT,
+	},
+}
+
+PROMPTS = CONDITION_SET["prompts"]
diff --git a/prompts/condition_set_4_action_space.py b/prompts/condition_set_4_action_space.py
new file mode 100644
index 0000000..9ea8632
--- /dev/null
+++ b/prompts/condition_set_4_action_space.py
@@ -0,0 +1,62 @@
+"""Condition set 4: action space."""
+
+EGOCENTRIC_PROMPT = """You are the red triangular agent solving a maze. Your mission is to navigate to the green square.
+
+mechanisms present:
+{MAZE_SPECIFIC_MECHS}
+
+Available actions:
+- TURN_LEFT
+- TURN_RIGHT
+- MOVE_FORWARD
+- INTERACT
+
+Current observation:
+{DOMAIN_SPECIFIC_OBSERVATION}
+
+Inventory:
+{INVENTORY}
+
+Choose exactly ONE action to take from the available actions.
+
+Output only the action name.
+Output only the action name.
+"""
+
+CARDINAL_PROMPT = """You are the red triangular agent solving a maze. Your mission is to navigate to the green square.
+
+mechanisms present:
+{MAZE_SPECIFIC_MECHS}
+
+Available actions:
+- MOVE_NORTH
+- MOVE_SOUTH
+- MOVE_EAST
+- MOVE_WEST
+- INTERACT
+
+Current observation:
+{DOMAIN_SPECIFIC_OBSERVATION}
+
+Inventory:
+{INVENTORY}
+
+Choose exactly ONE action to take from the available actions.
+
+Output only the action name.
+"""
+
+CONDITION_SET = {
+	"name": "Action space",
+	"comparisons": [
+		"Egocentric: TURN_LEFT, TURN_RIGHT, MOVE_FORWARD, INTERACT",
+		"Cardinal: MOVE_NORTH/SOUTH/EAST/WEST, INTERACT",
+	],
+	"decision": "If delta is trivial (<5%), go egocentric. If massive (>15%), reassess.",
+	"prompts": {
+		"egocentric": EGOCENTRIC_PROMPT,
+		"cardinal": CARDINAL_PROMPT,
+	},
+}
+
+PROMPTS = CONDITION_SET["prompts"]
diff --git a/prompts/condition_set_5_querying_strategy.py b/prompts/condition_set_5_querying_strategy.py
new file mode 100644
index 0000000..cdcf7bf
--- /dev/null
+++ b/prompts/condition_set_5_querying_strategy.py
@@ -0,0 +1,60 @@
+"""Condition set 5: querying strategy."""
+
+SUBGOAL_PROMPT = """You are the red triangular agent solving a maze. Your mission is to navigate to the green square.
+
+mechanisms present:
+{MAZE_SPECIFIC_MECHS}
+
+Current observation:
+{DOMAIN_SPECIFIC_OBSERVATION}
+
+Inventory:
+{INVENTORY}
+
+Before acting, produce a short high-level plan.
+
+Your plan should identify:
+1. important keys
+2. important doors or gates
+3. likely exploration order
+4. important switches or bottlenecks
+
+Output concise numbered subgoals only.
+"""
+
+SUBGOAL_EXECUTION_PROMPT = """You are the red triangular agent solving a maze. Your mission is to navigate to the green square.
+
+mechanisms present:
+{MAZE_SPECIFIC_MECHS}
+
+Current high-level plan:
+{SUBGOAL_PLAN}
+
+Available actions:
+{DOMAIN_SPECIFIC_ACTION_LIST}
+
+Current observation:
+{DOMAIN_SPECIFIC_OBSERVATION}
+
+Inventory:
+{INVENTORY}
+
+Choose exactly ONE action to take from the available actions.
+
+Output only the action name.
+"""
+
+CONDITION_SET = {
+	"name": "Querying strategy",
+	"comparisons": [
+		"Step-by-step: one action per query",
+		"Subgoal planning: model outputs plan first, then executes per-subgoal",
+	],
+	"decision": "Does planning help? If yes, benchmark tests planning or execution?",
+	"prompts": {
+		"subgoal": SUBGOAL_PROMPT,
+		"subgoal_execution": SUBGOAL_EXECUTION_PROMPT,
+	},
+}
+
+PROMPTS = CONDITION_SET["prompts"]
diff --git a/prompts/condition_set_6_in_context_learning.py b/prompts/condition_set_6_in_context_learning.py
new file mode 100644
index 0000000..962ea21
--- /dev/null
+++ b/prompts/condition_set_6_in_context_learning.py
@@ -0,0 +1,80 @@
+"""Condition set 6: in-context learning."""
+
+from .condition_set_1_prompt import STANDARD_PROMPT
+
+ONE_SHOT_PROMPT = """Example maze interaction:
+
+mechanisms present:
+{ICL_MAZE_SPECIFIC_MECHS}
+
+Available actions:
+{DOMAIN_SPECIFIC_ACTION_LIST}
+
+Observation:
+{ICL_OBSERVATION_1}
+
+Inventory:
+{ICL_INVENTORY_1}
+
+Action:
+{ICL_ACTION_1}
+
+Observation:
+{ICL_OBSERVATION_2}
+
+Inventory:
+{ICL_INVENTORY_2}
+
+Action:
+{ICL_ACTION_2}
+
+Observation:
+{ICL_OBSERVATION_3}
+
+Inventory:
+{ICL_INVENTORY_3}
+
+Action:
+{ICL_ACTION_3}
+
+End of example.
+
+Now solve the following maze.
+
+You are the red triangular agent solving a maze. Your mission is to navigate to the green square.
+
+mechanisms present:
+{MAZE_SPECIFIC_MECHS}
+
+Available actions:
+{DOMAIN_SPECIFIC_ACTION_LIST}
+
+Current observation:
+{DOMAIN_SPECIFIC_OBSERVATION}
+
+Inventory:
+{INVENTORY}
+
+Choose exactly ONE action to take from the available actions.
+
+Output only the action name.
+"""
+
+CONDITION_SET = {
+	"name": "In-context learning",
+	"comparisons": [
+		"Zero-shot: no examples",
+		"1-shot: one example trajectory (different maze, same mechanism type)",
+	],
+	"decision": (
+		"If 1-shot dramatically improves performance, bottleneck is task "
+		"understanding, not capability. Determines zero-shot vs few-shot."
+	),
+	"constraint": "ICL examples must not use evaluation mazes.",
+	"prompts": {
+		"zero_shot": STANDARD_PROMPT,
+		"one_shot": ONE_SHOT_PROMPT,
+	},
+}
+
+PROMPTS = CONDITION_SET["prompts"]
diff --git a/prompts/exp_design.py b/prompts/exp_design.py
new file mode 100644
index 0000000..3bd3260
--- /dev/null
+++ b/prompts/exp_design.py
@@ -0,0 +1,17 @@
+"""Experiment 3 prompt condition-set registry."""
+
+from .condition_set_1_prompt import CONDITION_SET as CONDITION_SET_1
+from .condition_set_2_observation_format import CONDITION_SET as CONDITION_SET_2
+from .condition_set_3_context_window import CONDITION_SET as CONDITION_SET_3
+from .condition_set_4_action_space import CONDITION_SET as CONDITION_SET_4
+from .condition_set_5_querying_strategy import CONDITION_SET as CONDITION_SET_5
+from .condition_set_6_in_context_learning import CONDITION_SET as CONDITION_SET_6
+
+CONDITION_SETS = {
+	CONDITION_SET_1["name"]: CONDITION_SET_1,
+	CONDITION_SET_2["name"]: CONDITION_SET_2,
+	CONDITION_SET_3["name"]: CONDITION_SET_3,
+	CONDITION_SET_4["name"]: CONDITION_SET_4,
+	CONDITION_SET_5["name"]: CONDITION_SET_5,
+	CONDITION_SET_6["name"]: CONDITION_SET_6,
+}