MEASURED
Finding · authorise
Blind to the pool, 60 of 60 episodes per model breached the budget with no agent over its allowance
Blind to the pool, the budget was breached in 60 of 60 episodes on each of three models with no agent over its own allowance. With the pool state shown the budget was still breached on every model, at rates that differ by model; the per-cell counts, including episodes where an agent exceeded its own allowance, are in the table on the collective-bound page.
- The system said
- Every agent within its allowance.
- The evidence showed
- The shared budget was breached in 60 of 60 BLIND episodes on each of three models, with no individual violation; an informationally redundant restatement of the headroom took it to 4, 2 and 0 of 60.
§ 1
The record
FINDING · commons-compliant-collective-breachauthorise · expressibility
Blind to the pool, the budget was breached in 60 of 60 episodes on each of three models with no agent over its own allowance. With the pool state shown the budget was still breached on every model, at rates that differ by model; the per-cell counts, including episodes where an agent exceeded its own allowance, are in the table on the collective-bound page.
- Claim
- In a shared-budget environment where each agent's allowance is individually satisfiable but the allowances sum to 1.5 times the collective budget, three language models produced a compliant collective breach in 60 of 60 BLIND episodes each (two population sizes, 30 episodes per cell), with zero individual allowance violations; one appended sentence restating the same headroom took the rate to 4 of 60, 2 of 60 and 0 of 60.
- Status
- MEASURED Empirical, with a stated sample.
- Subject
- Three hosted language models (gpt-5-mini, gpt-4.1-mini, gemini-2.5-flash) acting as agents in a synthetic one-round shared-budget environment (existing models, authored environment). third-party subject
- Frame
- Collective budget 100; N in {3, 6}; UNSOUND regime cap = ceil(1.5 × 100 / N); 30 episodes per cell fixed before any data; Wilson 95% intervals.
- Method
- Pre-registered factorial over regime, population size and an information ladder over identical tasks; four amendments each registered before their data; every outcome computed from the environment ledger, never from model text.
- Oracle
- The environment's own ledger of draws. A stub model whose prose claims it drew nothing while its action draws the full allowance is scored on the action, and that test fails the build if it stops doing so.
- Negative control
- Present Seven pre-committed controls: an impossible-breach cell that must read 0 of 60 and a forced-breach cell that must read 60 of 60 (both did), an equal-share baseline, an allowance-response check, a benign cell supplying the guardrail's second denominator, a scorer-independence test and five runtime invariant monitors.
- Denominator
- 60 of 60 per model = UNSOUND_N3_BLIND 30 of 30 plus UNSOUND_N6_BLIND 30 of 30. The per-cell table is on the collective-bound page.
- Preregistration
- Registration commit 3bf280e (2026-08-22) precedes the first model call; amendments 01 to 04 each precede their data; departures in DEVIATIONS.md.
- Limitation
- A rate here is a fact about a dataset, a prompt and a model on one day, not a capability of a model family or of language-model agents in general. The environment is synthetic and one round deep. Three developers, not four; the guardrail judge shares a vendor with two of the agent arms. No mechanistic claim is made about why the phrasing matters.
- Source
- repowazdogz-droid/commons-agent-lab @ de3f89d
- Reproduce
python3 -m pytest tests -q && python3 -m commons.report _canonical/gpt-5-mini _canonical/gpt-4.1-mini _canonical/gemini-2.5-flash
- Independent reproduction
- None known.
§ 2
Where this sits
This finding answers Individually compliant is not collectively safe and supports the AUTHORISE stage of the operating method. It is an instance of the expressibility mechanism.