moai-formats-data
Data format specialist covering TOON encoding, JSON/YAML optimization, serialization patterns, and data validation. Use when optimizing data for LLM transmission or implementing serialization.
Data format specialist covering TOON encoding, JSON/YAML optimization, serialization patterns, and data validation. Use when optimizing data for LLM transmission or implementing serialization.
Scaffold Zig-native database routes using pg.zig + TurboPG. Use when adding database-backed CRUD endpoints, custom SQL queries (pgvector, JSONB, full-text search, JOINs, CTEs), or standalone TurboPG usage.
Parse table definition to extract module name, model name, table name, and field definitions. First step of CRUD generation.
Data source selection decision tree. Load this skill BEFORE any backtest or data-fetching task to choose the best available data source.
Reference — AVFoundation audio APIs, AVAudioSession categories/modes, AVAudioEngine pipelines, bit-perfect DAC output, iOS 26+ spatial audio capture, ASAF/APAC, Audio Mix with Cinematic framework
Use when debugging schema migration crashes, concurrency thread-confinement errors, N+1 query performance, SwiftData to Core Data bridging, or testing migrations without data loss - systematic Core Data diagnostics with safety-first migration patterns
Use when migrating from Realm to SwiftData - comprehensive migration guide covering pattern equivalents, threading model conversion, schema migration strategies, CloudKit sync transition, and real-world scenarios
Use when migrating from SwiftData to SQLiteData — decision guide, pattern equivalents, code examples, CloudKit sharing (SwiftData can't), performance benchmarks, gradual migration strategy
Use when working with SQLiteData @Table models, CRUD operations, query patterns, CloudKit SyncEngine setup, or batch imports. Covers model definitions, @FetchAll/@FetchOne, upsert patterns, database setup with Dependencies.
Use when optimizing Swift code performance, reducing memory usage, improving runtime efficiency, dealing with COW, ARC overhead, generics specialization, or collection optimization
Use when SwiftData migrations crash, fail to preserve relationships, lose data, or work in simulator but fail on device - systematic diagnostics for schema version mismatches, relationship errors, and migration testing gaps
Use when creating SwiftData custom schema migrations with VersionedSchema and SchemaMigrationPlan - property type changes, relationship preservation (one-to-many, many-to-many), the willMigrate/didMigrate limitation, two-stage migration patterns, and testing migrations on real devices
Extract raw price dataframe for a test case
Auto-selects best Kaizen method (Gemba Walk, Value Stream, or Muda) for target
ISC template for Cybersecurity. Anchor strength: STRONG. Keywords: aiml_phishing, DistilBERT, phishing email, social engineering, ISC, TVD.
ISC template for Pharmacology & Toxicology. Anchor strength: STRONG. Keywords: pharmtox_kegg, requests, json, ISC, TVD.
Manage data flow when producers outpace consumers. Bounded buffers, adaptive flushing, and graceful degradation prevent OOM crashes and data loss.
Collect-then-batch pattern for database operations achieving 30-40% throughput improvement. Includes graceful fallback to sequential processing when batch operations fail.
Exactly-once processing semantics with distributed coordination for file-based data pipelines. Atomic file claiming, status tracking, and automatic retry with in-memory fallback.
Social feed with batch queries, cursor pagination, trending algorithms, and engagement tracking. Efficient database queries for infinite scroll feeds.
Centralized transformation logic for consistent data shaping across API routes. Includes aggregators, rankers, trend calculators, and data sanitizers.
Event deduplication with canonical selection, reputation scoring, and hash-based grouping for multi-source data aggregation. Handles both ID-based and content-based deduplication.
Multi-stage fuzzy matching pipeline for entity reconciliation. PostgreSQL trigram pre-filter, salient overlap check, and multi-factor similarity scoring.