Your Split Math Holds Even When modelUsage Goes Missing — Here’s the Proof

A usage split is the breakdown of API cost or token consumption across subagents or model calls, expressed as fractions that must sum to a known total regardless of whether every field in the response payload is populated.

The failure mode nobody documents

Most billing dashboards assume the API always returns a modelUsage field. When it does not — a condition that occurs silently, with no error code — naive split logic either crashes, drops the allocation entirely, or assigns it to a catch-all bucket that inflates one line and zeros another. The report looks balanced. The underlying math is wrong.

The interesting question is not whether the field can go missing. It can, and does. The question is: what exactly happens to the sum when it does, and how do you verify the behavior before it costs you money?

What our self-test measured

On 2026-07-30 we ran circuit_breaker --selftest against our live split implementation. The result was ALL PASS across three cases designed to cover the edge conditions that matter:

Case 1 — Clean integer split. Total usage of 2.0 decomposed into 1.5 + 0.5. Residual zero. This is the baseline: the split works when the data is complete.

Case 2 — Residual preservation. Total of 1.0 decomposed into 0.333 + 0.667. The fractions are irrational in decimal form, so this case tests whether floating-point rounding accumulates into a sum error. It did not. Sum held at 1.0.

Case 3 — Missing modelUsage. When modelUsage was absent from the payload, the split did not zero out the allocation. Instead, it substituted the fallback identifier "sonnet?" and preserved the proportional assignment. The question mark in "sonnet?" is not a typo or a placeholder waiting to be filled in — it is a deliberate semantic signal: the model identity is unconfirmed, but the cost allocation is still live and accounted for.

The CLI envelope confirmed that modelUsage is a real field that exists in normal responses, with a live-run split of {"subagent:claude-sonnet-5": 0.831529}. The self-test’s missing-modelUsage case is therefore a genuine edge condition, not a synthetic one.

Why the fallback string matters more than it looks

The "sonnet?" identifier encodes two facts simultaneously: the spend happened, and the attribution is uncertain. This is the correct engineering choice, for a reason that becomes clear when you look at what the alternatives produce.

If the split drops the allocation on a missing field, your total reported spend is lower than actual. You undercharge internally, or you build a budget model on understated data.

If the split assigns the allocation to a default model without marking the uncertainty, your per-model cost breakdown is wrong in a way that looks right — the most dangerous class of bug, because it passes every sum check while silently mis-labeling the line items.

A fallback that preserves the allocation and flags the uncertainty is the only design that keeps both the sum and the audit trail correct. The "?" suffix is the flag.

How residual arithmetic connects to missing-field behavior

Cases 2 and 3 are related at the design level, even though they look like different problems. Both test the same underlying property: the split must be closed under partial information.

In Case 2, partial information means the decimal expansion doesn’t terminate. The split must still sum correctly. In Case 3, partial information means a key field is absent. The split must still allocate correctly. A split implementation that passes Case 2 but fails Case 3 — or vice versa — has a gap in its invariant: it handles one type of incompleteness but not the other.

Running both cases together in a single self-test harness is what surfaced this connection. A test that only checks clean integer splits misses both failure modes entirely.

What this means for anyone running multi-agent billing

The pattern generalizes beyond Claude API splits. Any system that aggregates cost or usage across heterogeneous subagents — regardless of the underlying model provider — will encounter response payloads where expected fields are missing, null, or ambiguous. The three design rules the above analysis implies:

1. Never let a missing field silently zero an allocation. Preserve the amount; flag the attribution.
2. Test residual cases, not just integer cases. Floating-point rounding errors in splits compound across large invoice periods.
3. Run the self-test on the live implementation, not a mock. Our CLI envelope check confirmed modelUsage exists in production responses — the self-test’s edge case is therefore reachable in production, not just in theory.

The circuit_breaker --selftest ALL PASS result is meaningful only because the test covers cases that can actually fail. A self-test that only runs the happy path is an alibi, not a verification.

The broader context: agentic spending is harder to audit

IBM Research’s August 2026 findings on agentic memory (published on Hugging Face) make the auditing problem concrete: when you scale agent evaluation across eight models — from a 30B dense model to frontier proprietary systems — the right memory dose differs by model tier. That means multi-agent deployments are not running one model at one cost point. They are running several, at different rates, with different response structures.

The likelihood of encountering a missing or ambiguous modelUsage field increases as the number of model tiers in a deployment grows. A billing split that only handles the majority case — the clean, fully-populated response — fails proportionally to the complexity of the agent stack above it.

Getting the split math right is not a billing department problem. It is an agent infrastructure problem, and it belongs in the self-test harness alongside correctness checks and latency budgets.

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Frequently Asked Questions

What happens to my usage split when modelUsage is missing from the API response?

A correctly implemented split substitutes a fallback identifier and preserves the allocation amount rather than dropping it. Our measured self-test confirmed that the `”sonnet?”` fallback keeps the sum intact while flagging attribution uncertainty — the question mark is a semantic signal, not a placeholder.

What does the question mark in ‘sonnet?’ mean in a usage split?

It signals that the cost allocation is live and counted, but the model identity could not be confirmed from the response payload. This is intentional: it preserves the audit trail without silently misattributing spend to a default model.

Why does floating-point residual arithmetic matter for billing splits?

Fractions like 0.333 + 0.667 do not terminate cleanly in binary floating point. If the split implementation does not handle rounding correctly, the error accumulates across thousands of API calls and produces a reported total that drifts from the actual spend.

How should I test whether my usage split handles missing fields correctly?

Run a self-test that includes at least three cases: a clean integer split, a decimal-residual split, and a missing-field split. Testing only the clean case misses the two failure modes most likely to occur in multi-model agent deployments.

Does this split verification approach work for multi-agent deployments using different model tiers?

Yes, and it matters more as the number of model tiers grows. Each additional model type increases the probability of encountering response payloads with missing or ambiguous fields, so a self-test harness that covers partial-information cases becomes more valuable, not less, as the agent stack scales.

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