SSM-AI – Appendix F — SSM-Audit CFO Pack (F3–F5)

"ssm_audit": {
  "eps_a": 1e-6, "eps_w": 1e-12,
  "weights": {"policy": "uniform"},                      # or {"policy":"abs_m_gamma","gamma":1.0}
  "bands": {"A++":0.90,"A+":0.60,"A0":-0.60,"A-":-0.90,"A--":-1.00},
  "gate_ref": "gate_preset_A",
  "kpi_lenses": {
    "cost": {"alpha_tok":1.0, "alpha_ret":1.0, "Unit":1.0, "c":1.0},
    "lat":  {"alpha_on":1.0, "beta_p95":1.0, "beta_p99":0.5, "Unit":1.0, "c":1.0},
    "qual": {"alpha_succ":1.0, "beta_retry":1.0, "beta_contra":1.0, "Unit":1.0, "c":1.0},
    "inc":  {"alpha_mttr":1.0, "alpha_mtbf":1.0, "beta_page":1.0, "Unit":1.0, "c":1.0}
  }
}

# Per service/week row (or per decision for fine granularity)
svc, iso_week, KPI, RSI, w, g, RSI_env, band,
U_dec := atanh(RSI), W_dec := w, knobs_hash

# Portfolio roll-up (per KPI)
U_port := sum U_dec
W_port := sum W_dec
RSI_port := tanh( U_port / max(W_port, eps_w) )

# With gating (per-row first)
RSI_env := g * RSI                 # or tanh(g * atanh(RSI)) per manifest
# then pool identically to get RSI_port_env

# Inputs (weekly)
requests, tokens_per_req_before, cost_per_1k,
retry_rate_before, retry_rate_after,
p95_before_ms, p95_after_ms, savings_pct_tokens

# Derived
tokens_before := requests * tokens_per_req_before
spend_before  := (tokens_before / 1000) * cost_per_1k
tokens_saved  := tokens_before * savings_pct_tokens
spend_saved   := (tokens_saved / 1000) * cost_per_1k
spend_after   := spend_before - spend_saved
latency_delta_ms := p95_before_ms - p95_after_ms
retry_delta      := retry_rate_before - retry_rate_after

# ROI (annualized)
annual_savings := 52 * spend_saved
ROI := (annual_savings - integration_cost) / max(integration_cost, eps)