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cost-counterfactual

Multi-baseline counterfactual cost analysis. Compares actual session spend to hypothetical always-haiku / always-sonnet / always-opus routing baselines. Answers "is the routing earning its keep?" Negative savings flag over-escalation; positive savings quantify the router's win.

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ruvnet/ruflo
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16 juin 2026 à 16:10
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cost-counterfactual
description
Multi-baseline counterfactual cost analysis. Compares actual session spend to hypothetical always-haiku / always-sonnet / always-opus routing baselines. Answers "is the routing earning its keep?" Negative savings flag over-escalation; positive savings quantify the router's win.
argument-hint
[--since 7d] [--baseline always-haiku|always-sonnet|always-opus|all] [--format table|json]
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Bash
Multi-baseline counterfactual cost analysis. Pairs with the existing observability surface: - **`cost-budget-check`** — "have we crossed a threshold?" (reactive) - **`cost-projection`** — "when will we cross a threshold?" (predictive) - **`cost-counterfactual`** — "is the routing earning its keep?" (comparative) ← this one ## Algorithm 1. Read all `session-*` records from the `cost-tracking` namespace. 2. Apply `--since` window filter (default all-time). 3. Sum tokens across `byModel[*]` entries for each session. 4. For each requested baseline (default: all three): - `counterfactualUsd = (input × tier.input + output × tier.output + cache_write × tier.cache_write + cache_read × tier.cache_read) / 1M` 5. Compute `savings = counterfactualUsd − actualUsd`. 6. Emit per-baseline totals + savings % across the comparison set. ## Smoke transcript (2 sessions: 50K haiku tokens + 50K sonnet tokens) ``` | Sessions considered | 2 | | Total input tokens | 100,000 | | Actual spend | $0.162500 | | Baseline | Hypothetical | Actual | Savings | % | | `always-haiku` | $0.025000 | $0.162500 | -$0.137500 | -550.00% | | `always-sonnet` | $0.300000 | $0.162500 | +$0.137500 | 45.83% | | `always-opus` | $1.500000 | $0.162500 | +$1.337500 | 89.17% | ``` ## How to read negative savings A negative `always-haiku` result means **the router chose more-expensive models than haiku** on tasks haiku could have handled. That's an over-escalation signal: - Maybe qualityBar is set too high - Maybe the sonnet/opus session was warranted by complexity but the baseline doesn't know that - Run `cost optimize` (or inspect specific sessions via `cost conversation`) to investigate Positive savings quantify the router's win against that baseline. The most informative number is usually `always-sonnet` — it's the standard "safe default" baseline most teams would pick if they didn't have routing. ## When to use - **Quarterly cost review**: "We saved $X vs always-Sonnet — here's the proof." - **CI gate**: `cost counterfactual --format json | jq '.baselines[1].savingsPct > 30'` — fail builds if routing isn't saving ≥30% vs sonnet baseline (workload-shift detector). - **Routing-config validation**: When introducing a new qualityBar or cost-ceiling, re-run counterfactual to confirm savings didn't regress. ## Stationarity caveat Like all counterfactual analyses, this assumes the same tokens at the same complexity would have produced the same outcome from the baseline model. That's an upper bound — the baseline might have failed and required retries, which the math doesn't capture. Treat the numbers as a quality-blind ceiling.
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