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Run test suite with proper flags and coverage
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Based on SOC occupation classification
| name | test |
| description | Run test suite with proper flags and coverage |
.venv\Scripts\python.exe -m pytest tests/test_db_cleanup.py tests/test_database_schema.py tests/test_database_connection.py tests/test_premium_upgrade.py tests/test_forum_tips.py tests/test_check_secrets.py tests/test_friends_security.py tests/test_rate_limiting.py tests/test_race_conditions.py tests/test_xss_prevention.py tests/test_testmode_hardening.py tests/test_database_robustness.py tests/test_performance.py tests/test_orm.py tests/test_orm_repos.py tests/test_orm_startup.py --no-cov -q
.venv\Scripts\python.exe -m pytest tests/test_<name>.py --no-cov -v
.venv\Scripts\python.exe -m pytest tests/test_<name>.py::TestClass::test_method --no-cov -v
.venv\Scripts\python.exe -m pytest tests/e2e/ --no-cov -v
--no-cov — pytest.ini has coverage enabled which breaks SlowAPI inspect-v for verbose output when debugging-q for quick summary-x to stop at first failure| File | Tests | Phase |
|---|---|---|
| test_database_schema.py | 8 | Phase 0 |
| test_database_connection.py | 33 | Phase 0 |
| test_premium_upgrade.py | 11 | Phase 0 |
| test_forum_tips.py | 12 | Phase 0 |
| test_check_secrets.py | 9 | Phase 0 |
| test_friends_security.py | 16 | Phase 1 |
| test_rate_limiting.py | 19 | Phase 1 |
| test_race_conditions.py | 17 | Phase 1 |
| test_xss_prevention.py | 30 | Phase 1 |
| test_testmode_hardening.py | 8 | Phase 1 |
| test_database_robustness.py | 44 | Phase 2 |
| test_performance.py | 26 | Phase 3 |
| test_orm.py | 33 | Phase 5 |
| test_orm_repos.py | 98 | Phase 5 |
| test_orm_startup.py | 16 | Phase 5 |
| test_db_cleanup.py | 27 | DB Cleanup |
Debug frontend vanilla JS issues - console errors, rendering bugs, SPA navigation, WebSocket
Automates the process of setting up the first admin user or adding new admins via the bootstrap endpoint. Includes a Python script for easy execution.
Push to remote and wait for CI to pass. If CI fails, read logs, fix bugs, and re-push. Repeat until green.
Use when building or debugging LangGraph multi-agent systems - eval-first execution, task decomposition, model routing by complexity, and cost discipline
Use when AI agent modifies API routes or backend logic - catch systematic blind spots where the same model writes and reviews code
Use when making or recording significant architectural decisions - capture context, alternatives, and rationale as structured ADRs