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.

This view keeps both results separate. It does not calculate a combined score or decide whether they reproduce each other.

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First result: full recordtoken cost · 1.75 tokens per declared item

First result · 2026-10-13 10:17 UTC

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

Counts in current evidence decisions. This row currently contributes to evidence decisions. Its direction is separate from whether the proposal is ready for adoption.

What was measured
token cost · token_delta
How does the wording change tokenizer units for the declared tokenizer population?
Reported result
1.75 tokens per declared item
Reported interval: -0.3125 to 1.75.

More 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, p50k_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
Agrees with the named original

This eligible row adds one agreement to the named original’s settlement tally.

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?
Agrees with the named original. This replication reports 1.75 tokens; the named original reported 1.875.

This eligible row adds one agreement to the named original’s settlement tally.

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?

100.0% of complete English–Ainglish pairs are fresh.

  • 0 of 16 English inputs reuse text from either side of the original.
  • 0 of 16 Ainglish inputs reuse text from either side of the original.

Declared item-bank digests: different. This compares bank identity, not shared sentences; different bank digests can still contain identical pairs.

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 identityf398df158f9e348c3aa4d2823ce2f0c386ddbd3bdf76795bcf57bac958a438d7
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 1–6 of 16 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
I last checked artifact-signed at 2026-10-13T06:12Z against release/candidate-12.
Ainglish input
checked(artifact-signed@2026-10-13T06:12Z, scope=release/candidate-12).

Input 2

English input
I last checked snapshot-readable at 2026-10-12T22:46Z against storage/snapshot-84.
Ainglish input
checked(snapshot-readable@2026-10-12T22:46Z, scope=storage/snapshot-84).

Input 3

English input
I last checked schema-compatible at 2026-10-11T14:32Z against catalog/revision-19.
Ainglish input
checked(schema-compatible@2026-10-11T14:32Z, scope=catalog/revision-19).

Input 4

English input
I last checked ingress-reachable at 2026-10-13T07:24Z against gateway/north-4.
Ainglish input
checked(ingress-reachable@2026-10-13T07:24Z, scope=gateway/north-4).

Input 5

English input
I last checked retention-satisfied at 2026-10-09T16:18Z against records/batch-63.
Ainglish input
checked(retention-satisfied@2026-10-09T16:18Z, scope=records/batch-63).

Input 6

English input
I last checked package-reproducible at 2026-10-12T13:51Z against build/recipe-28.
Ainglish input
checked(package-reproducible@2026-10-12T13:51Z, scope=build/recipe-28).

Recorded input digest: aef2c074a7597fdd7b98faf76e7b0c0e7f027dc0beda0e087d26019d62007d6b

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
Compared with
Ainglish arm carrying checked(<predicate>@<checked-at>, scope=<scope>) minus English arm carrying the row's served lossless expansion 'I last checked <predicate> at <checked-at> against <scope>'; the predicate name, ISO timestamp and scope string are transcribed verbatim in both arms, so slot-filler cost cancels and the delta prices the construct's wrapper against the expansion's words (comparator genre: complete careful English, narrow checking-event reading, no result claim in either arm)
Tested population
16 fresh author-written messages: 8 standalone check reports and 8 reports embedded in a two-sentence operational message; 16 distinct predicate/timestamp/scope triples drawn from release, infrastructure and compliance contexts; no item reused from any prior row on this proposal
Unit tested
message pair: one short English message and its Ainglish counterpart, byte-identical outside the construct
How results combine
maximum tokenizer mean over the three declared tiktoken encodings (least-favourable); per-pair delta = Ainglish tokens minus English tokens; unstratified, so the headline is the plain item mean of the worst encoding

These are the study author’s declarations. A finding applies to this tested scope; this summary does not establish that another study is comparable.

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

[
    {
        "model": "cl100k_base",
        "value": -0.25
    },
    {
        "model": "o200k_base",
        "value": -0.3125
    },
    {
        "model": "p50k_base",
        "value": 1.75
    }
]

Condition results

Not recorded

Exact result and immutable specificationExperiment history

Attempt 5c81f7ee-74b9-446f-8a6b-c5cf35c60068
Content 9611e732d0bd510cc5ea43bbd7d64cdddd78f024ce7baaf30f486b6f2915b10a

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.