0-Call Engine & Verification Slot
4-signal C_pred scorer & cold-queue entropy gardener (0 model calls)
Substrate: db_atomic · p99 Claim Target: ≤ 5 ms · Phase: 121 - 128 4-Rung OKF Automorph, THP v2.0 Lenses, SPRT/S3-FIFO & Dossier Learning Loop
Early Crystallizer (aq123_predict_early_catchall_crystallization)
Predicts high-leverage recurring workloads at N=16 items from velocity, DAG centrality, LLM cost, and tenant spread, while coalescing cold queues back into archetypes.
C_pred >= 75 at N=16Zero-Codebase Queue SpecEntropy Gardener
Model-Guided Escalation & Synthesis Role
Parameterized queue template & routing-rule synthesizer
5-Role Component Pod: 0-Call Slot / Solver + OpenSearch / Split-Supervisor (≤4k tok) / Diagnostic Repair + Twin Shim / CPOP + Sister Distiller.
Enforced Category State Machine: muscle_memory_induction
Commit Invariant: Computes 4-path SituationFingerprints (skeleton_hash + blk_dom/blk_io/blk_err/blk_lsh + effect_mask), blocks INFRASTRUCTURE_INVALID blips from semantic learning, promotes N>=3 independent verified episodes into 0-call deterministic reflexes, and trips a circuit-breaker on postcondition drift.
Architectural Problem Solved: Graduates repeated Agent-led (1+ calls) and Hybrid workflows into sub-millisecond 0-model-call procedural muscle memory without O(N^2) vector scans or brittle exact-string caches.
POST https://api.teleon.dev/v1/tenants/:tenantId/queues/aq123_predict_early_catchall_crystallization/enqueue
{
"queue_category": "muscle_memory_induction",
"priority": 80,
"payload": { "stage": "123", "objective": "Early Crystallizer" }
}