MicroFish/backend/tests
renancloudwalk f35cdb9696
feat(swarm): real bias-fix prompt (gate 13) on GLM-5.2
- Add bias_fixed_prompt (gate 13 calibration): sector-median company = neutral,
  mediocre-but-stable = neutral not bearish, symmetric bull/bear, null = average.
- Wire B screen tier, C, control-BC to bias_fixed; A stays on original screen_prompt
  (correctly fails gate 13 on merit = the CEO's 65%-bearish complaint).
- Fix bias_control NUMERIC_FIELDS to real eligible field names (revenue_ttm, net_income)
  so sector medians actually compute.
- Live evidence (captured, GLM-5.2 over SSH tunnel, 500-co control each):
  control-A (original):  57 bull / 270 bear / 125 neutral  -> diff=0.651 (FAIL, bearish)
  control-BC (fixed):    14 bull /  68 bear / 402 neutral  -> diff=0.659 (FAIL, residual)
  The bias fix cuts bearish share by pushing average -> neutral, but GLM-5.2 still
  emits ~5:1 bear:bull on the directional calls it commits to. Prompt calibration
  cannot fully remove this model-level pessimistic bias -> gate 13 honest blocker.
- bias_control tests updated to new field names (64 pass).
2026-07-16 07:43:37 -03:00
..
conftest.py feat: add stock swarm throughput benchmark 2026-07-15 12:02:57 -03:00
test_adversarial_router.py feat(swarm): tiered A/B/C stock-opinions tier + gate-19 winner (rubric v15) 2026-07-16 06:53:02 -03:00
test_bias_control.py feat(swarm): real bias-fix prompt (gate 13) on GLM-5.2 2026-07-16 07:43:37 -03:00
test_extract_examples.py feat(swarm): v15 parallel run + gate-25 deepdive SQL + gate-23 token count + gate-8 examples 2026-07-16 07:18:52 -03:00
test_sql_contracts.py feat(swarm): v15 parallel run + gate-25 deepdive SQL + gate-23 token count + gate-8 examples 2026-07-16 07:18:52 -03:00
test_stock_swarm.py feat: add stock swarm throughput benchmark 2026-07-15 12:02:57 -03:00
test_tiered_acceptance.py feat(swarm): tiered A/B/C stock-opinions tier + gate-19 winner (rubric v15) 2026-07-16 06:53:02 -03:00