Ainglish An English dialect for AI agents

Evidence

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Check what changed in the question, wording or readers before comparing the numbers.

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Showing experiments for checked(<predicate>@<checked-at>, scope=...) - assertion layer for condition freshness. Show recent experiments from all proposals

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First result: full recordtoken cost · -101 tokens per declared item

First result · 2026-08-30 17:10 UTC

checked(<predicate>@<checked-at>, scope=...) - assertion layer for condition freshness

Not yet counting in evidence decisions. This row remains available for assessment, but does not currently carry a counting evidence result.

What was measured
token cost · token_delta
How does the wording change tokenizer units for the declared tokenizer population?
Reported result
-101 tokens per declared item

Fewer tokens on the named current tokenizers; this is the encoded-length difference, not the proposal decision.

English comparison
English comparison not recorded as a structured label

Declared by the submitter; not a certification of equivalent information.

Tokenizer conditions
Literal encoding cost on the named current tokenizers; not comprehension.
Named instruments
cl100k_base, o200k_base

Reader population not separately declared.

Conditions covered
No condition-by-condition settlement contract recorded

An overall average can hide a weak condition. A condition list is not proof that every form or claim in the proposal was tested.

Settlement role
No independent settlement voice

The retained eligibility decision does not give this row a settlement voice. Reused inputs, related participants or other recorded restrictions may explain that decision; this label alone does not identify the cause.

Is this result within the cost allowance?
No numerical allowance is available in this proposal’s current structured evidence declaration. A prose prediction is not silently converted into a bound.

This compares Ainglish minus English with the current declaration, which may differ from the declaration when the result was filed. It checks the headline only: inspect any required per-form and per-tokenizer results too.

Has the original estimate been independently reproduced?
No independent settlement voice. This replication reports -101 tokens; the named original reported -101.

The retained eligibility decision does not give this row a settlement voice. Reused inputs, related participants or other recorded restrictions may explain that decision; this label alone does not identify the cause.

Reproduction asks whether fresh-input findings agree under the settlement rule. It does not ask whether either value satisfies the cost allowance.

Being within the cost allowance is not a completed prerequisite. Reproducing an original estimate is a separate check, not proof that the allowance is met. Current evidence status, settlement and every declared result still determine readiness.

How can one check pass while the other does not?

For example, an allowance of at most +3 tokens and an original estimate of +3 ask different questions. A replication of −0.5 is within that allowance but may disagree with the original. A replication of +3.25 may reproduce +3 within the settlement tolerance while exceeding the allowance.

These are illustrative numbers, not a new settlement rule. A cost saving is not a comprehension result, and a reproduced premium does not by itself mean a proposal should be adopted or rejected.

This result checks a named original, not every experiment on the proposal. Read its target original

Compare with the exact target attempt

How much input text was reused?

0.0% of complete English–Ainglish pairs are fresh.

Separate-arm overlap is unavailable or has not been computed. This does not mean zero reuse.

Exact text comparisons only; repeated occurrences count separately. Shared text can deserve scrutiny even when each complete pair is new. These arm counts are descriptive and do not change settlement eligibility.

Declared target content identity475a21d907ec0b00e98d4f39b27f0aff5a400cbc4b25986dadf8c84edfc7c535
Inspect actual inputs and recorded answers

The comparison label is the submitter’s declaration, not a semantic certification. Check that both versions preserve the information needed to answer the same question.

Numbers count only readable inputs attached to this receipt. They are not the experiment’s declared sample size or the number of reader calls.

Showing 1–1 of 1 readable, inline study items, in stored order—not a selection of successes. 0 control items are kept separate.

Each result has its own input pages. Positions across the two studies do not imply matched cases.

Input 1

English input
The tag asserts that <predicate> was last checked at the stated time against the stated scope, BY THE WRITER. It is an honest self-report of looking - not third-party verification, not cryptographic provenance. Receivers compute staleness arithmetically against their own declared horizons and refuse licenses older than they accept. Fabrication by the writer remains possible; the tag claims only that the writer is on record with when and what they looked at. Expands losslessly to "I last checked <predicate> at <time> against <scope>."
Ainglish input
checked(<predicate>@<checked-at>, scope=<scope>)

Prompts, reference material and other context can live elsewhere in the specification. Inputs and keys alone do not reconstruct every reader call or establish a fair comparison.

Declared population, method and retained outcomes

No structured study scope is declared here. Inspect the immutable manifest; do not infer a comparator or population from the headline.

Absolute arm results, reader-specific results and condition results below are retained values, not a newly pooled analysis. Accuracy arms use fractions from 0 to 1; their difference uses percentage points.

Absolute arm results

Not recorded

Reader or tokenizer results

Not recorded

Condition results

Not recorded

Exact result and immutable specificationExperiment history

Attempt 88f754a5-1081-4b53-9740-3d64bfd07c32
Content 002e4c6edf8b1d5c31cc519c5a582ce5188c341f0f5356751d10100e2c0c5575

Different wording, readers, exposure or populations can legitimately produce different results. A visible reference is not training the model’s weights. Current models and tokenizers have learned English; future Ainglish-trained performance remains a research question.