Conformance for the rules added in SPEC 0.2.0, 236 checks in all: - C5 (§5.1–§5.2): for the published response-time vectors (conformance/v1/scan_rate.json, 10 cases) the rate is at least the nearest-rank P95 and ⌊100·M/65⌋, within 300..5000 ms; nothing adapts before 10 responses or without opt-in; a proposal never applies itself; the 10% proposal rule is pinned at both edges. - C6 (§5.1, §5.3): dwell vectors (conformance/v1/dwell.json, 24 cases) — nothing changes without opt-in, shorter proposals respect the 300 ms floor, both directions are reachable, clean selections alone change nothing, and an opted-in engine applies exactly its proposal, once. A restored 30-selection ratchet fails. - C7 (§4.1): stable CoreStatus wire names, a record without a status reads as GlossOnly, and only English carries a natively studied core. C5 and C6 recompute every expected value from the raw inputs with an independent oracle (cross-checked with exact fractions) before comparing the engine, so the engine is held to the rule, not to itself. gen-vectors takes an output directory and regenerates all three vector files byte-for-byte; the harness takes a vector directory. A missing or unparseable vector is a FAIL. Co-Authored-By: Claude Opus 5.5 <[email protected]>
128 lines
2.2 KiB
JSON
128 lines
2.2 KiB
JSON
{
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"invariants": {
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"energy_strictly_monotonic": true,
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"offline_levels": [
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"L0",
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"L1",
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"L2"
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]
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},
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"levels": [
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{
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"energy_uj": 1,
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"index": 0,
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"name": "Cache",
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"offline": true,
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"tag": "L0"
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},
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{
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"energy_uj": 10,
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"index": 1,
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"name": "Symbol Lookup",
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"offline": true,
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"tag": "L1"
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},
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{
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"energy_uj": 100,
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"index": 2,
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"name": "Local Prediction",
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"offline": true,
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"tag": "L2"
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},
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{
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"energy_uj": 1000,
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"index": 3,
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"name": "Context Prediction",
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"offline": false,
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"tag": "L3"
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},
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{
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"energy_uj": 10000,
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"index": 4,
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"name": "Semantic Expansion",
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"offline": false,
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"tag": "L4"
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},
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{
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"energy_uj": 100000,
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"index": 5,
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"name": "Conversation AI",
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"offline": false,
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"tag": "L5"
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},
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{
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"energy_uj": 1000000,
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"index": 6,
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"name": "Generative Communication",
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"offline": false,
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"tag": "L6"
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},
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{
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"energy_uj": 5000000,
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"name": "Voice Clone",
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"offline": false,
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"tag": "L7"
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},
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{
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"energy_uj": 10000000,
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"index": 8,
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"name": "Multimodal Generation",
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"offline": false,
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"tag": "L8"
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},
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{
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"energy_uj": 15000000,
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"index": 9,
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"name": "Adaptive Model",
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"offline": false,
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"tag": "L9"
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}
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],
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"routing": [
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{
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"level": "L0",
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"operation": "CellSelect"
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},
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{
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"level": "L1",
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"operation": "SymbolSearch"
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},
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{
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"level": "L2",
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"operation": "WordPrediction"
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},
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{
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"level": "L3",
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"operation": "SocialScript"
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},
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{
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"level": "L4",
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"operation": "SentenceConstruction"
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},
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{
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"level": "L5",
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"operation": "ConversationRepair"
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},
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{
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"level": "L6",
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"operation": "ComposeLong"
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},
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{
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"level": "L7",
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"operation": "VoiceBanking"
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},
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{
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"level": "L8",
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"operation": "SymbolGeneration"
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},
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{
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"level": "L9",
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"operation": "ModelRetrain"
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}
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],
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"spec": "SPEC.md §6",
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"standard": "aac",
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"vector": "cascade",
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"version": "0.2.0"
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}
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