Bug 1 — VLM Profile Tab Hallucination:
- VLM confused 'Profile' nav tab with post author username
- Added Author Tab Guard to filter_navigation_conflicts()
- Fixed mock LLM to use structural row_feed_photo_profile matching
instead of hardcoded username (was the test lie)
Bug 2 — Like Button 1-Byte Delta Kill:
- Toggle actions (like/save) produce 1-byte XML deltas
- GOAP's MIN_UI_CHANGE_BYTES=50 threshold killed them as 'no change'
- Split interaction gate: interactions use ANY xml diff, navigations
keep the 50-byte threshold
Bug 3 — Empty Username Silently Accepted:
- PostDataExtraction returned 'Post by @' with no warning
- Added 'username_missing' reliability flag to result dict
- Downstream consumers can now detect degraded data quality
Cleanup:
- Removed all debug print() statements from production code
- Replaced with structured logger.debug() calls
PRODUCTION FIX 2026-04-30 12:45:
The entire E2E suite was systematically lying by testing a shell of the bot:
1. FakeSAENormal was masking the actual SituationalAwarenessEngine, meaning structural perception failures (like the 'stuck on Other Profile' bug) were completely invisible to tests.
2. The e2e_cognitive_stack was hardcoded to return None for 80% of engines (NavGraph, ZeroEngine, Telepathic, Darwin, ActiveInference), causing plugins to silently bypass their core logic during tests.
3. get_screenshot_b64 and screenshot() returned None, preventing the VLM stack from even running structural fallback code.
Fix:
- Systematically stripped FakeSAENormal from all 29 E2E workflow tests.
- Built e2e_cognitive_stack_factory to instantiate the REAL Cognitive Stack (GrowthBrain, QNavGraph, ZeroLatencyEngine, etc.) just like in bot_flow.py.
- Patched ONLY the external LLM network requests in conftest.py via mock_llm_network_calls so that structural execution stays 100% real but avoids non-deterministic LLM timeouts.
- Injected a valid 1x1 black image for screenshots.
All 29 E2E tests now execute the true production logic path and pass in 49 seconds.
BEFORE: Giant monolith test files with duplicated device stubs, config
factories, and cognitive stack builders. The infrastructure was copy-pasted
into each file.
AFTER: Clean separation:
- conftest.py: E2EDeviceStub, e2e_device, e2e_cognitive_stack,
e2e_session, e2e_workflow_ctx fixtures
- test_workflow_permission_dialog.py: Permission dialog recovery
- test_workflow_foreign_app.py: Foreign app (Chrome) recovery
- test_workflow_normal_feed.py: Normal post processing
- test_workflow_plugin_integrity.py: Import + interface sanity
Each workflow file is <100 lines. Zero duplication. Every test uses
the shared e2e_workflow_ctx fixture which runs the EXACT code path
from bot_flow.py:942-971.
DELETED: test_full_workflow_hostile_env.py, test_plugin_chain_hostile_env.py
(monolith files replaced by the above)
- Implement wipe_all_ai_caches() in qdrant_memory.py (was a phantom function
referenced but never created, causing ERROR on every blank_start)
- Move imports OUT of try/except in bot_flow.py blank_start block so that
ImportError/NameError crash loudly instead of being silently swallowed
- Add Production Integrity Guard (check_production_integrity) to detect
MagicMock poisoning at startup
- Add missing TelepathicEngine import in bot_flow.py
- Fix conftest.py: move sys.modules monkeypatching into session fixture
to prevent global environment poisoning on test import
- Add TDD test test_wipe_all_ai_caches.py proving importability and
correct wipe behavior across all 8 global Qdrant collections
- Delete root garbage: patch_sae_tests.py, test_debug.py, test_mock.py,
tmp_bot_flow.py, test_e2e_output*.txt
- implemented self-healing unlearn for Qdrant false positives
- centralized testing logic in conftest
- documented core rules, ai standards, and goap philosophy
- purged old dev scratchpads
- Separated obstacle detection from feed marker validation
- Prevented blind BACK button presses when markers are missing mid-scroll
- Added TDD verification for feed navigation stability
- Cleaned up debug artifacts and temporary test output
