ROOT CAUSE:
The bot would permanently softlock itself on UNKNOWN screens (like Trending Audio/Reels)
because 'is_trap' had NO time-decay, and UNKNOWN screen traps persisted forever.
Once 'press back' was trapped on an UNKNOWN screen, the bot was permanently blocked
from escaping any future UNKNOWN screen, causing endless restart loops.
FIXES:
1. Trap Time-Decay: 'is_trap' now forgives Qdrant-persisted traps older than 30 minutes.
This mirrors ContextMemory and prevents permanent dead-ends.
2. UNKNOWN Guard: 'learn_trap' now REFUSES to persist traps for UNKNOWN screens to Qdrant.
They only live in-memory to prevent breaking global navigation.
3. In-Memory Purge: 'force start instagram' now properly calls 'clear_traps()' to wipe
the planner's in-memory traps. Previously they survived restarts, immediately
re-trapping the bot.
Purged 6 ancient traps from Qdrant (one was 8 days old!).
TDD: 3 new tests, full suite 113/114 (1 infra flake)
FOLLOW PLUGIN SAFETY GUARD:
- Added pre-click XML guard: checks button text before clicking
- If button says 'Following'/'Requested'/'Message' → SKIP
(prevents opening dangerous Unfollow/Add-to-Favorites bottom sheet)
- Changed intent from 'tap Follow or Following button' to 'tap follow button'
- This was the root cause of adding users to Close Friends/Favorites
VLM VERIFICATION RESILIENCE:
- VLM false no longer shortcircuits to return False
- VLM verdict is now a SOFT SIGNAL that falls through to structural
delta verification as ground-truth tiebreaker
- Small local VLMs (7B llava) systematically return false for everything
- This was THE root cause of memory poisoning: every action got penalized
because VLM always said 'failed', regardless of actual screen state
- 22 total poisoned Qdrant entries purged across two sessions
ROOT CAUSE CHAIN:
VLM always says false → penalties on every action → confidence < 0.2 →
circuit breaker blocks ALL core actions → bot can't like/follow/comment
→ bot clicks random things → adds to favorites, opens bottom sheets
TDD: 4 new tests, full suite 110/111 (1 infra flake)
CLOSE FRIENDS GUARD:
- Replaced broken text-only detection ('enge freunde'/'close friend')
with STRUCTURAL resource-id marker detection:
* friendly_bubbles_component (feed posts)
* profile_header_close_friend (profile view)
* close_friends_badge (Reels)
* close_friends_star (green star)
- Kept legacy text fallback for edge cases
- TDD: 5 tests including meta-test enforcing structural detection
CONTEXT MEMORY CIRCUIT BREAKER:
- Old system: single failure permanently blocks action (confidence < 0.2 = dead)
- New system: time-based decay — failures older than 1 hour are auto-forgiven
and the poisoned entry is DELETED, allowing re-exploration
- This prevents catastrophic self-sabotage where the bot blocks its own
core actions (tap like, tap follow, tap comment) permanently
- Purged 14 poisoned entries from live Qdrant that were blocking ALL
fundamental interactions
- TDD: 2 meta-tests enforcing time-decay and no permanent blocking
Full suite: 106/107 passed (1 infra flake)
- Removed hardcoded (540,150) fallback in _plan_escape_via_llm
- Added _find_structural_dismiss_target: scans raw XML for clickable
dismiss/cancel/close buttons and extracts coords from bounds attrs
- LLM repeat detection now falls back to structural scan (not magic numbers)
- Temperature increases progressively when LLM is stubborn (0.1 → 0.7)
- Failure history injected as CRITICAL block into LLM system prompt
- Extended pre-commit test discovery to include tests/tdd/
- TDD: 7 new tests including meta-tests proving zero hardcoded coords
- Full suite: 100/100 passed
P0-2: Kill blank_start: true in config — the nuclear option that wipes ALL learned
knowledge on every run. Replaced with memory_hygiene() selective amnesia that
prunes low-confidence entries while preserving high-confidence learned patterns.
P0-3: Purge all root-level garbage scripts (scratch.py, test_run.py, profile_dump.xml,
resp_dump.json, pytest_output.log, test_output.log, coverage.xml, coverage_e2e.json).
Updated .gitignore to prevent reaccumulation.
P2-2: Replace piecemeal BANNED_SCREENS/REQUIRED_MARKERS with complete Action
Compatibility Matrix (VALID_SCREENS whitelist). Every interaction intent now has
an explicit set of valid screens. Covers like, comment, follow, unfollow, save,
repost across all 14 screen types.
P2-3: Remove non-deterministic 'press back' transitions from HD Map topology for
OTHER_PROFILE, POST_DETAIL, and SEARCH_RESULTS. Add tab transitions to POST_DETAIL.
P2-4: Replace ScreenMemoryDB nuclear 200-entry wipe with LRU eviction.
store_screen() now accepts confidence parameter.
TDD: 22 new tests (all GREEN), 240 unit/tdd/integration passed, 0 regressions.
E2E: 288 passed (+2 fixed), 6 pre-existing LIE DETECTED failures.
- Fixed .gitignore to correctly handle __pycache__ even when inside whitelisted directories (like tests/).
- Moved pycache ignore patterns to the end of the file to ensure they take absolute precedence over any directory-level whitelists.
- Purged all previously tracked .pyc and __pycache__ files from the git index.
- Cleaned up .hypothesis and .pytest_cache artifacts.
This enforces 'Militärische Git-Disziplin' (Rule 7) and keeps the repo clean of environment-specific junk.
- GrowthBrain.select_task() uses weighted random from concrete Task objects
- Removed self.goals from Config (no longer reads goals: from config.yml)
- Mission + plugins are now the SSOT for bot behavior
The bot no longer receives abstract strings like 'Nurture my community' that
the LLM Brain can't operationalize. Instead, the GoalDecomposer generates
Task(browse_feed, HomeFeed, budget=7) which routes to concrete feed loops.
18/18 TDD tests passing.
Introduces the GoalDecomposer class that bridges mission.strategy + plugin
capabilities into concrete, weighted Task objects. Each Task has a target
screen, budget, weight, and human-readable intent.
Key design decisions:
- Pure logic, zero LLM/device dependencies
- Strategy weights (aggressive_growth, community_builder, etc.) drive selection
- Plugins declare which screens they operate on (multi-screen map)
- Screens need BOTH an action route AND active plugin to be viable
- Frozen dataclass ensures Task immutability
12/12 TDD tests passing.
- 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
Summary of work:
- Resolved mass SystemExit: 2 failures by hardening Config against pytest CLI args.
- Fixed state leakage in test suite by implementing aggressive cache wiping in conftest.py.
- Fixed TypeErrors and UnboundLocalErrors in TelepathicEngine and bot_flow.
- Aligned MockTelepathicEngine signatures to resolve Mock Drift.
- Achieved 100% pass rate across 498 tests.
