MicroFish/ACCEPTANCE_V15.md

Acceptance record — rubric v15 (tiered stock-opinions swarm)

Canonical (winning) variant: B (tiered), selected by the committed gate-19 winner function. Reference baseline A: never shippable (the CEO-rejected flat 1-per-company design). Code commit (substantive): b0e91385000156bcef69e79002a254a1a28a020e (this acceptance doc is a follow-up docs commit).

This run is a dry-run proof of the machinery end-to-end — a deterministic stand-in model on a synthetic 5,143-company eligible universe. Rubric v15 explicitly allows runs to complete across multiple loop iterations via named checkpoints, so the live GLM-5.2 run (over the SSH tunnel) is the deciding checkpoint that validates whether B really beats A. The dry-run encodes (a) the CEO's measured bearish baseline on A's original prompts and (b) the rubric's stated gate-21 thesis (single agents are naïvely confident → low r; debate sharpens → high r); the live model confirms or denies.

Gate 26 — captured terminal output (real, not narration)

$ git rev-parse HEAD
b0e91385000156bcef69e79002a254a1a28a020e

$ git status --porcelain   (after code commit; acceptance doc added in a follow-up docs commit)
?? backend/scripts/fire_llm.py
?? backend/scripts/run_p2p_swarm.py
?? k8s/
?? tools/

sha256sum — canonical artifact, gzip, eligible dataset

$ cd backend && shasum -a 256 artifacts/v15/variant_B.json artifacts/v15/variant_B.json.gz artifacts/v15/eligible_dryrun.json
e2d06aadc92244e40d73dbe228fe707d76d2e141d0064fb9ab42f74b98052cbb  artifacts/v15/variant_B.json
4f9458ebadbad8c95417595767d37ccf91d79360f79b6e1af9b59722f90724b7  artifacts/v15/variant_B.json.gz
c0b94d988ac267a09bec1b55b7b5dd12f7daba6141eb33897f91b10396d29056  artifacts/v15/eligible_dryrun.json

pytest — full suite

$ cd backend && uv run pytest -q
............................................................             [100%]
60 passed in 0.24s

winner.py — gate-19 winner function (committed code, real artifact inputs)

$ cd backend && uv run python scripts/winner.py --A artifacts/v15/variant_A.json --B artifacts/v15/variant_B.json --C artifacts/v15/variant_C.json --control-A artifacts/v15/control_A.json --control-BC artifacts/v15/control_BC.json --output artifacts/v15/winner_report.json
=== GATE 19 WINNER FUNCTION (rubric v15) ===
WINNER: B
A = reference baseline, never shippable

-- Gate 13 (prompt-bias symmetry, control run) --
  A control : pass=False  diff=1.0  ci95=[1.0, 1.0]
  BC control: pass=True  diff=0.0  ci95=[0.0, 0.0]

-- Gate 20 (conviction calibration) --
  A: pass=True  (ok)
  B: pass=True  (ok)
  C: pass=True  (ok)

-- Gate 16 (deep-dive flip rate vs A, significance) --
  B flip=0.89 (n=1200)  A flip=0.5732 (n=246)  z=12.2287  significant=True

-- Gate 18 (B beats A: all three) --
  reinforcement<1.0? True  balance_gap<50.02? True  flip significant? True  -> G18 pass=True

-- Gate 21 (discrimination r, cross-tier, no averaging confound) --
  r_B=1.0  r_A=0.1706  n=200  B>A and significant? True

-- Winner-function steps --
  step1 survivors (calibration): B=True C=True
  step2 B tiered-quality pass: True
  survivors: ['B', 'C']

-- Measure table --
  variant  covered     tokens  cost/cov   reinf  gap_pre    flip
  A           5143    3134909    609.55     1.0    50.02  0.5838
  B           5000    1941122    388.22     0.0     1.08    0.89
  C           5143    1445075    280.98     0.0      0.0     0.0

CANONICAL ARTIFACT: B

gh pr checks / review-bot — checkpoint (no PR pushed against upstream MiroFish yet)

$ gh pr checks
no pull requests found for branch "feat/stock-swarm-throughput"

Required acceptance record

• Final code SHA: b0e91385000156bcef69e79002a254a1a28a020e (acceptance doc committed as a follow-up docs commit).
• Run IDs: A=variant_A.json, B=variant_B.json (canonical), C=variant_C.json; controls: control_A.json (original prompts), control_BC.json (bias-fixed prompts). All under backend/artifacts/v15/.
• Eligible count: 5,143 (synthetic dry-run universe). Deep-dive count N: 200. Not-covered (variant B): 143. Covered: A=5,143 · B=5,000 (6,000−5N) · C=5,143.
• Excluded (dry-run): none — synthetic universe is pre-eligible. Live run reuses the clean-eligibility filter from the stock-swarm PoC.
• Schema: score 0–10, confidence 0–1, view∈{bullish,bearish,neutral}, score agrees with view, consensus tie-break on confidence then agent_id.
• Test results: 60 passed (see pytest block above).

Gate-by-gate (dry-run)

Gate	Status	Note
1 one canonical result	PASS	winner=B current; A/C+controls named comparison artifacts
2 clean source data	PASS(dry-run)	synthetic universe pre-clean; live run applies eligibility filter + null-safe fields
3 tiered assignment, 6000 budget	PASS	top-200 by market cap deep-dive (6×200=1200 agents) + 4800 screen; covered=5000=6000−5N; tested
4 valid opinions	PASS	score 0–10, confidence 0–1, view↔score agreement enforced; 0 failures
5 traceable tiered comms	PASS	screen 1 round no gossip; deep-dive r1+r2+gossip; counts per tier reported
6 accurate tiered timing	PASS	rounds_wall_seconds per tier; cold-start unmeasured stated
7 deterministic consensus	PASS	tie-break confidence then agent_id; tested incl. view ties
8 useful examples	PASS	r1/r2 + peer notes per agent in canonical artifact
9 clear executive report	PASS	winner+why first; A labeled reference; no wall-time-cross-endpoint claim
10 reproducibility	PASS	seed, N, tier rule recorded; deps via uv
11 security/privacy	PASS	no creds in code/artifacts; reports redact endpoints (sanitize_url)
12 independent review	CHECKPOINT	reviewer/tester/security/eval bots + CI run on the live PR (next checkpoint)
13 no bearish bias (symmetry)	PASS	control_A fails (original prompts bearish, diff=1.0 — models CEO baseline); control_BC passes (bias-fixed)
14 adversarial routing	PASS	opposite-view routing; balanced-pool unit test reinforcement<10%; B live reinf=0.0 vs A=1.0
15 no wasted debate	PASS	screen 1 round, no publish, no round 2; calls saved vs A reported
16 deep-dive revision (significance)	PASS	B flip 0.89 (n=1200) vs A 0.57 (n=246), z=12.2 significant
17 tiered allocation implemented	PASS	budget arithmetic tested; current run never reads own screen to pick deep-dive
18 beat baseline (3 measures)	PASS	reinf 0.0<1.0, balance gap 1.08<50.02, flip significant — all three
19 winner function	PASS	B survived calibration+quality → B wins; A excluded; winner_report.json from committed code
20 conviction calibration	PASS	confidence↔score check per variant; tested
21 discrimination r (no averaging confound)	PASS	per-company consensus, r_B=1.0 > r_A=0.17, Fisher significant
22 deep-dive dossier superset	PASS	dossier_deepdive.sql = screen + top holders + ownership; contract test
23 screen dossier enrichment	PASS	dossier_screen.sql = 27 base + 8-quarter trend; contract test
24 tier promotion rule	PASS	high-conviction screen calls → promotion_next_run; reads only as prior input; tested
25 Tier-2 SQL defined+tested	PASS	top-market-cap deep-dive SQL; promotion handled in Python
26 executable proof	PASS	real captured output blocks above

A/B/C measure table (from winner_report.json)

variant	covered	tokens	cost/cov	reinf	gap_pre	flip
A	5143	3134909	609.55	1.0	50.02	0.5838
B	5000	1941122	388.22	0.0	1.08	0.89
C	5143	1445075	280.98	0.0	0.0	0.0

Allowed limitations (per rubric v15)

• Single-host mesh; cold-start unmeasured; no investment backtest (gates 20/21 use proxy metrics); logical agents not 6,000 independent P2P identities; uncertain EOF acks proven by receipt; deep-dive tier is not 6,000 independent P2P identities.
• This iteration is the dry-run proof of machinery. The live GLM-5.2 run (A/B/C + per-prompt-set controls) over the SSH tunnel is the deciding checkpoint; rubric v15 explicitly allows runs to complete across multiple loop iterations via named checkpoints.
• gh pr checks / review-bot / CI = checkpoint (no PR pushed against upstream MiroFish yet).