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TELEON ARCHITECTURE MASTER BLUEPRINT & SEED PORTAL
← All 320 Atomic Work Queues STAGE 44 OF 320 muscle_memory_induction Async enhancement

Crystallize Pattern to Queue (aq44_crystallize_pattern_to_queue)

Detects recurring patterns inside catch-all documents and graduates them into dedicated flat queues, THP schemas, 5-role worker pods, and tuning grids.

Cluster Threshold >=3Dedicated cq_* QueueAuto Grid & Pod
TIER 1 · DETERMINISTIC (0 MODEL CALLS)

0-Call Engine & Verification Slot

Shape-cluster promoter, THP schema synthesizer & Store S8 grid seeder

Substrate: db_atomic · p99 Claim Target: ≤ 6 ms · Phase: 41 - 44 Supervise, Repair, Catch-All Intake & Crystallize

AI Agent (1..6)

Model-Guided Escalation & Synthesis Role

Domain queue architect & parameter-axis designer

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/aq44_crystallize_pattern_to_queue/enqueue
{
  "queue_category": "muscle_memory_induction",
  "priority": 80,
  "payload": { "stage": "44", "objective": "Crystallize Pattern to Queue" }
}
← Stage 43: Catch-All Document Intake View in Single-Page Master Blueprint Stage 45: Suggest SCD2 Context Pack →