Mac-local autocorrect foundation

Mac-local autocorrect foundation

Status: no-model foundation verified on 2026-07-25. No model was downloaded, loaded, calibrated, trained, compiled, or benchmarked.

Decision and boundary

The owner explicitly reprioritized finishing the OpenSpecs on 2026-07-25, so the foundation tranche of build-mac-local-autocorrect-specialist moved ahead of a model run. The boundary is deliberate:

• complete the correction contract, evaluator, provenance/split validation, keyboard simulator, tiny manifests, and comparator assessment;
• calibrate the frozen fixture with Codex while leaving every local model/GPU stage pending;
• do not claim that the 18-row smoke fixture is a production benchmark.

The machine-readable source of truth is evals/autocorrect/. The protocol accepts one English UTF-8 prose span of at most 512 bytes and returns only the minimally corrected span. URLs, numbers, backtick code, and fixture-declared names or rare words are protected. Grammar rewriting, style changes, translation, next-word prediction, and keyboard/UI integration are out of scope.

Tiny source and eval

The committed source is original, owner-authorized for this tranche, and licensed under the repository MIT license. Its revision is the SHA-256 of source-documents-v1.jsonl; no retrieval or network step exists. Private typing logs and external corpora with unverified revisions or terms are excluded.

The frozen eval has:

These are manually constructed and reviewed examples of ordinary typing mistakes. They are sufficient to prove evaluator and data-path behavior, but not to estimate real-world prevalence or support a headline model claim. Before a final model evaluation, add a larger independently verified permissive or consented natural source as a new fixture version; do not mutate v1 after candidate outputs exist.

Strict evaluator

scripts/autocorrect_foundation.py evaluate requires exactly one string prediction per frozen ID and rejects missing, duplicate, extra, or expanded records. It reports:

• micro error-reduction rate, including negative values without clamping;
• exact match and residual character error;
• byte-exact clean preservation;
• deterministic minimum-edit unnecessary-edit rate;
• protected-span preservation;
• every committed slice plus per-row distances.

Zero-error clean controls have a null error-reduction value instead of a division-by-zero surrogate. A changed clean control still counts as an unnecessary edit and protected-span failure.

Source-first data path

Clean documents are assigned to train, development, or test before any derivative exists. The validator enforces that the derivative inherits its source split and rejects exact or NFKC/case/whitespace-normalized overlap across splits. It also verifies source/license fields, source and dataset SHA-256 values, counts, lexical holdouts, edit-trace replay, and deterministic reproduction.

Only two future-training manifests exist:

No training dataset was expanded beyond these manifests.

Mac keyboard simulator and distribution

The simulator uses the committed US ANSI Mac layout and a SHA-256 counter stream, avoiding runtime-global PRNG state. It supports adjacent-key substitution, insertion, omission, transposition, repetition, space insertion/removal, and shift/case errors. Every result carries source/noisy offsets, source text, replacement text, family, and mode; clean controls have an empty trace.

The 12 reviewed error events and the 256-row deterministic simulator sample compare as follows:

The total-variation distance is 0.0547 after setting only the training-side family weights to the reviewed fixture counts. The natural fixture and its hash did not change. These weights are a smoke prior, not an empirical claim; a larger licensed natural sample must produce a new simulator config version.

Apple autocorrect assessment

Read-only inspection of the locally installed macOS 27 AppKit SDK found:

• NSSpellChecker.checkString returns checking results;
• NSSpellChecker.correctionForWordRange proposes one correction for an explicit word range;
• NSTextView.automaticSpellingCorrectionEnabled participates in an interactive text-view lifecycle.

No inspected public API accepts the same complete prose span and returns the final whole-span autocorrect output used during interactive typing. A custom loop that applies word corrections would be a new protocol, and interactive behavior may depend on language, user preferences, learned spellings, document state, and typing order. Apple autocorrect is therefore frozen as an observational, non-equivalent baseline. It must not appear in the direct v1 error-reduction or frontier-parity table. Exact SDK paths and hashes are in apple-autocorrect-assessment-v1.json.

Calibration and pending blockers

Task 2.5 is complete. Codex CLI 0.145.0 with gpt-5.6-sol received only the committed fixture, matched all 18 rows exactly, preserved every clean/protected span, and required no fixture repair or removal. Invocation provenance and hashes are in evals/autocorrect/frontier-calibration-v1.json. This establishes that the tiny smoke ruler is unambiguous; it does not make it representative.

Task 4.1 is also complete. The pinned three-candidate shortlist and exact resource gate are in autocorrect-model-shortlist.md.

• Tasks 4.2-4.5 require immediate approval before the recorded downloads, dependency installation, model loads, or bounded bake-off.
• Tasks 5.1-5.7: require a selected base and explicit approval for any dependency, compilation, model load, GPU lock, overfit, or pilot training.
• Tasks 6.1-6.4: require real greedy/beam decoding and resource/energy measurements.
• Tasks 7.1-7.6: require calibrated comparators, trained candidates, complete performance evidence, and a real decision. No package or archive is valid before those exist.