Skip to content
Back to skills

Cost Counterfactual

ASecurity

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.

  • 73,733 stars
  • 0 votes
  • 0 copies
  • 3 views
  • Added September 2, 2026
ai-agentsgobashreact

Security analysis

A100/100

Scanned September 2, 2026

npx -y skills add ruvnet/ruflo --skill cost-counterfactual --agent claude-code

Installs into .claude/skills of the current project.

Are you the author of Cost Counterfactual?

Add the live security badge to your README. It updates with every re-scan.

Security grade badge for Cost Counterfactual
[![Security: A — Skills Directory](https://www.skillsdirectory.com/api/skills/ruvnet-cost-counterfactual/badge)](https://www.skillsdirectory.com/skills/ruvnet-cost-counterfactual)

More formats (shields.io, HTML) on the badges page. Keep it an A: scan every change in CI with Pro.

Download with Pro
SKILL.md
---
name: 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]"
allowed-tools: 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.

Attribution

Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.

Comments

Loading comments…

Newsletter

Get the weekly list of safe new skills, and the ones we pulled.