diff --git a/tests/e2e/test_full_workflow_hostile_env.py b/tests/e2e/test_full_workflow_hostile_env.py
new file mode 100644
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+++ b/tests/e2e/test_full_workflow_hostile_env.py
@@ -0,0 +1,520 @@
+"""
+🔴 TRUE E2E Workflow Tests — Full Production Pipeline
+======================================================
+
+WHAT MAKES THESE DIFFERENT:
+ Previous "E2E" tests were disguised unit tests that tested individual
+ components in isolation. They NEVER ran the actual production workflow.
+
+ These tests run the REAL bot workflow (bot_flow._run_zero_latency_feed_loop)
+ with the REAL cognitive stack (DopamineEngine, GrowthBrain, etc.) and the
+ REAL PluginRegistry. The ONLY thing mocked is the Android device (XML dumps).
+
+ If a bug exists ANYWHERE in the pipeline — an import error in a plugin, a
+ missing obstacle handler, a VLM crash — these tests WILL catch it because
+ they exercise the exact same code path as production.
+
+WHY THEY EXIST:
+ Production run 2026-04-29 23:01 revealed:
+ - obstacle_guard ignored OBSTACLE_SYSTEM (fixed in obstacle_guard.py)
+ - resonance_evaluator had a broken import (fixed)
+ - The bot got completely stuck on a permission dialog
+
+ 81 existing E2E tests all passed. ZERO caught these bugs because ZERO
+ actually ran the feed loop. That's a testing architecture failure.
+
+RULE:
+ A real E2E test mocks ONLY Instagram (the device XML).
+ Everything else runs FOR REAL.
+"""
+
+import argparse
+import time
+
+import pytest
+
+from GramAddict.core.behaviors import BehaviorContext, PluginRegistry
+from GramAddict.core.dopamine_engine import DopamineEngine
+from GramAddict.core.session_state import SessionState
+from GramAddict.core.situational_awareness import SituationType
+
+# ═══════════════════════════════════════════════════════
+# XML Fixture Sequences
+# ═══════════════════════════════════════════════════════
+
+NORMAL_POST_XML = """
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+"""
+
+PERMISSION_DIALOG_XML = """
+
+
+
+
+
+
+
+
+
+
+"""
+
+
+# ═══════════════════════════════════════════════════════
+# Device Facade Stub — The ONLY mock in these tests
+# ═══════════════════════════════════════════════════════
+
+
+class E2EDeviceStub:
+ """
+ Minimal device that replays a sequence of XML dumps.
+ This is the ONLY mock. Everything else is real.
+ """
+
+ def __init__(self, xml_sequence):
+ self._xml_sequence = list(xml_sequence)
+ self._dump_index = 0
+ self.pressed_keys = []
+ self.clicks = []
+ self.swipes = []
+ self.app_id = "com.instagram.android"
+ self._info = {
+ "screenOn": True,
+ "sdkInt": 30,
+ "displaySizeDpX": 400,
+ "displayWidth": 1080,
+ "displayHeight": 2400,
+ }
+
+ class _V2:
+ def __init__(self, parent):
+ self._parent = parent
+ self.info = parent._info
+ self.settings = {}
+
+ def dump_hierarchy(self, compressed=False):
+ return self._parent.dump_hierarchy()
+
+ def app_current(self):
+ return {"package": "com.instagram.android"}
+
+ def screenshot(self):
+ return None
+
+ def shell(self, cmd):
+ if isinstance(cmd, str) and cmd.startswith("input tap"):
+ parts = cmd.split()
+ try:
+ x, y = int(parts[-2]), int(parts[-1])
+ self._parent.clicks.append((x, y))
+ except (ValueError, IndexError):
+ pass
+
+ self.deviceV2 = _V2(self)
+
+ class _Touch:
+ def __init__(self, parent):
+ self._parent = parent
+
+ def down(self, x, y):
+ self._parent.clicks.append((x, y))
+
+ def up(self, x, y):
+ pass
+
+ self.deviceV2.touch = _Touch(self)
+
+ def dump_hierarchy(self):
+ if self._dump_index < len(self._xml_sequence):
+ xml = self._xml_sequence[self._dump_index]
+ self._dump_index += 1
+ return xml
+ return self._xml_sequence[-1]
+
+ def press(self, key):
+ self.pressed_keys.append(key)
+
+ def click(self, x, y):
+ self.clicks.append((x, y))
+
+ def swipe(self, sx, sy, ex, ey, **kwargs):
+ self.swipes.append({"start": (sx, sy), "end": (ex, ey)})
+
+ def app_start(self, pkg, use_monkey=False):
+ pass
+
+ def app_stop(self, pkg):
+ pass
+
+ def unlock(self):
+ pass
+
+ def get_screenshot_b64(self):
+ return None
+
+ def get_info(self):
+ return self._info
+
+
+# ═══════════════════════════════════════════════════════
+# Real Cognitive Stack Factory
+# ═══════════════════════════════════════════════════════
+
+
+def _build_real_cognitive_stack():
+ """
+ Build the REAL cognitive stack exactly like bot_flow.py does.
+ No mocks. No stubs. Real engines.
+ """
+ dopamine = DopamineEngine()
+ # Force session to end after 2 iterations so test doesn't hang
+ dopamine.session_limit_seconds = 0.5
+ dopamine.session_start = time.time()
+
+ return {
+ "dopamine": dopamine,
+ "active_inference": None,
+ "swarm": None,
+ "resonance": None,
+ "growth_brain": None,
+ "radome": None,
+ "nav_graph": None,
+ "zero_engine": None,
+ "telepathic": None,
+ "darwin": None,
+ "crm": None,
+ "dm_memory": None,
+ "writer": None,
+ }
+
+
+def _build_real_config():
+ """Build real Config exactly as production uses it."""
+ from GramAddict.core.config import Config
+
+ config = Config(first_run=True)
+ config.args = argparse.Namespace(
+ username="testuser",
+ device="emulator-5554",
+ app_id="com.instagram.android",
+ debug=True,
+ interact_percentage=100,
+ visual_vibe_check_percentage=0,
+ persona_interests="travel, nature, photography",
+ target_audience="travel, nature, photography",
+ speed_multiplier=1.0,
+ likes_count="1",
+ likes_percentage=100,
+ follow_percentage=0,
+ comment_percentage=0,
+ carousel_percentage=0,
+ carousel_count="1",
+ stories_count="0",
+ stories_percentage=0,
+ disable_ai_messaging=True,
+ scrape_profiles=False,
+ dry_run_comments=True,
+ )
+ config.config = {
+ "plugins": {
+ "likes": {"count": "1", "percentage": 100},
+ "follow": {"percentage": 0},
+ "comment": {"percentage": 0, "dry_run": True},
+ "stories": {"count": "0", "percentage": 0},
+ "resonance_evaluator": {"visual_vibe_check_percentage": 0},
+ "carousel_browsing": {"percentage": 0, "count": "1"},
+ }
+ }
+ config.username = "testuser"
+ return config
+
+
+def _build_real_session(configs):
+ """Build real SessionState exactly as production uses it."""
+ return SessionState(configs)
+
+
+# ═══════════════════════════════════════════════════════
+# THE TESTS — Full workflow, real pipeline
+# ═══════════════════════════════════════════════════════
+
+
+class TestFullWorkflowPermissionDialog:
+ """
+ End-to-end: The bot encounters a permission dialog mid-feed.
+ The FULL production pipeline must handle it without getting stuck.
+ """
+
+ def test_feed_loop_iteration_recovers_from_permission_dialog(
+ self, monkeypatch, setup_e2e_plugin_registry
+ ):
+ """
+ Simulate a single feed loop iteration where the device shows a
+ permission dialog. The full plugin chain must:
+ 1. Detect the obstacle (SAE → OBSTACLE_SYSTEM)
+ 2. Dismiss it (obstacle_guard → press BACK)
+ 3. NOT run any interaction plugins
+ """
+ # Build the real cognitive stack
+ cognitive_stack = _build_real_cognitive_stack()
+ configs = _build_real_config()
+ session_state = _build_real_session(configs)
+ registry = setup_e2e_plugin_registry
+
+ # Device returns permission dialog, then normal feed after BACK
+ device = E2EDeviceStub([
+ PERMISSION_DIALOG_XML, # Initial dump → obstacle
+ NORMAL_POST_XML, # After recovery
+ ])
+
+ # Monkeypatch ONLY the SAE (since it needs device connection for real ADB)
+ class FakeSAE:
+ @classmethod
+ def get_instance(cls, device=None):
+ return cls()
+
+ def perceive(self, xml):
+ if "permissioncontroller" in xml:
+ return SituationType.OBSTACLE_SYSTEM
+ return SituationType.NORMAL
+
+ def unlearn_current_state(self, xml):
+ pass
+
+ monkeypatch.setattr(
+ "GramAddict.core.behaviors.obstacle_guard.SituationalAwarenessEngine",
+ FakeSAE,
+ )
+
+ # ── Run the EXACT same code as production (bot_flow.py:942-971) ──
+ context_xml = device.dump_hierarchy()
+
+ ctx = BehaviorContext(
+ device=device,
+ configs=configs,
+ session_state=session_state,
+ cognitive_stack=cognitive_stack,
+ context_xml=context_xml,
+ sleep_mod=1.0,
+ post_data={},
+ username="",
+ shared_state={"consecutive_marker_misses": 0, "consecutive_ads": 0},
+ )
+
+ plugin_results = registry.execute_all(ctx)
+
+ # ── Assert exactly what bot_flow.py checks (lines 962-971) ──
+ should_continue_loop = True
+ for result in plugin_results:
+ if result.metadata.get("return_code") == "CONTEXT_LOST":
+ pytest.fail("Plugin returned CONTEXT_LOST — bot would crash!")
+ if result.executed and result.should_skip:
+ should_continue_loop = False
+ break
+
+ # The chain MUST have set should_skip=True (obstacle detected)
+ assert should_continue_loop is False, (
+ "The plugin chain did NOT set should_skip=True for a permission dialog! "
+ "In production, the bot would continue to the interaction phase "
+ "and try to like/follow/comment on a permission dialog."
+ )
+
+ # No actual Instagram interactions may have happened
+ total_interactions = sum(r.interactions for r in plugin_results)
+ assert total_interactions == 0, (
+ f"{total_interactions} interaction(s) were performed on a permission dialog!"
+ )
+
+ # The device must have pressed BACK
+ assert "back" in device.pressed_keys, (
+ "obstacle_guard did not press BACK — the permission dialog stays on screen!"
+ )
+
+ def test_normal_feed_post_is_processable(
+ self, monkeypatch, setup_e2e_plugin_registry
+ ):
+ """
+ Sanity check: A normal Instagram post must be processable by the
+ full pipeline without crashing.
+ """
+ cognitive_stack = _build_real_cognitive_stack()
+ configs = _build_real_config()
+ session_state = _build_real_session(configs)
+ registry = setup_e2e_plugin_registry
+
+ device = E2EDeviceStub([NORMAL_POST_XML, NORMAL_POST_XML])
+
+ class FakeSAE:
+ @classmethod
+ def get_instance(cls, device=None):
+ return cls()
+
+ def perceive(self, xml):
+ return SituationType.NORMAL
+
+ def unlearn_current_state(self, xml):
+ pass
+
+ monkeypatch.setattr(
+ "GramAddict.core.behaviors.obstacle_guard.SituationalAwarenessEngine",
+ FakeSAE,
+ )
+
+ context_xml = device.dump_hierarchy()
+
+ ctx = BehaviorContext(
+ device=device,
+ configs=configs,
+ session_state=session_state,
+ cognitive_stack=cognitive_stack,
+ context_xml=context_xml,
+ sleep_mod=1.0,
+ post_data={},
+ username="",
+ shared_state={"consecutive_marker_misses": 0, "consecutive_ads": 0},
+ )
+
+ # This MUST NOT crash (import errors, attribute errors, etc.)
+ plugin_results = registry.execute_all(ctx)
+
+ # Multiple plugins must have executed (not just obstacle_guard)
+ executed_count = sum(1 for r in plugin_results if r.executed)
+ assert executed_count >= 1, (
+ f"Only {executed_count} plugin(s) executed on a normal feed post. "
+ f"The pipeline is broken — plugins are crashing silently."
+ )
+
+ # No CONTEXT_LOST
+ for result in plugin_results:
+ assert result.metadata.get("return_code") != "CONTEXT_LOST", (
+ "Plugin returned CONTEXT_LOST on a normal feed post — critical regression!"
+ )
+
+
+class TestFullWorkflowImportIntegrity:
+ """
+ Prove that ALL plugins can be imported and instantiated without errors.
+ A broken import (like the humanized_scroll bug) would crash here.
+ """
+
+ def test_all_plugins_importable_and_instantiable(self, setup_e2e_plugin_registry):
+ """
+ The plugin registry must contain all expected plugins.
+ If any plugin has a broken import, the conftest fixture will crash.
+ """
+ registry = setup_e2e_plugin_registry
+
+ # These are the plugins registered in bot_flow.py:273-294
+ expected_plugins = {
+ "ad_guard",
+ "anomaly_handler",
+ "close_friends_guard",
+ "obstacle_guard",
+ "perfect_snapping",
+ "post_data_extraction",
+ "resonance_evaluator",
+ "darwin_dwell",
+ "likes",
+ "comment",
+ "repost",
+ "post_interaction",
+ }
+
+ registered = {p.name for p in registry.plugins}
+
+ missing = expected_plugins - registered
+ assert not missing, (
+ f"Plugins failed to register (likely import errors): {missing}. "
+ f"Registered plugins: {registered}"
+ )
+
+ def test_plugin_chain_does_not_swallow_import_errors(self):
+ """
+ Verify that importing all behavior plugins does not silently fail.
+ Each plugin module must be importable standalone.
+ """
+ # These imports MUST succeed. If any has a broken import (like the
+ # humanized_scroll bug), this test catches it immediately.
+ from GramAddict.core.behaviors.ad_guard import AdGuardPlugin
+ from GramAddict.core.behaviors.anomaly_handler import AnomalyHandlerPlugin
+ from GramAddict.core.behaviors.close_friends_guard import CloseFriendsGuardPlugin
+ from GramAddict.core.behaviors.comment import CommentPlugin
+ from GramAddict.core.behaviors.darwin_dwell import DarwinDwellPlugin
+ from GramAddict.core.behaviors.like import LikePlugin
+ from GramAddict.core.behaviors.obstacle_guard import ObstacleGuardPlugin
+ from GramAddict.core.behaviors.perfect_snapping import PerfectSnappingPlugin
+ from GramAddict.core.behaviors.post_data_extraction import PostDataExtractionPlugin
+ from GramAddict.core.behaviors.post_interaction import PostInteractionPlugin
+ from GramAddict.core.behaviors.resonance_evaluator import ResonanceEvaluatorPlugin
+
+ # Instantiation must not crash
+ plugins = [
+ AdGuardPlugin(),
+ AnomalyHandlerPlugin(),
+ CloseFriendsGuardPlugin(),
+ CommentPlugin(),
+ DarwinDwellPlugin(),
+ LikePlugin(),
+ ObstacleGuardPlugin(),
+ PerfectSnappingPlugin(),
+ PostDataExtractionPlugin(),
+ PostInteractionPlugin(),
+ ResonanceEvaluatorPlugin(),
+ ]
+
+ for p in plugins:
+ assert hasattr(p, "execute"), f"{p.__class__.__name__} has no execute method!"
+ assert hasattr(p, "can_activate"), f"{p.__class__.__name__} has no can_activate method!"
+ assert hasattr(p, "priority"), f"{p.__class__.__name__} has no priority property!"