data-integritylisted

# SKILL: data-integrity ## For: Agent 05 — DATA MODELER ## Version: 1.0.0 ## Global principles — apply to all projects 1. NEVER modify data directly — always via the access layer. 2. SINGLE WRITER — one write point per critical entity. 3. READ-ONLY READERS — separate the read layer from the write layer. 4. ALWAYS BACK UP — if the user can't recover the data, there is a backup. 5. EVERY MIGRATION HAS A ROLLBACK — defined and tested before running. ## Process STEP 1 — Identify entities: what exists, attributes, relationships, which are critical (irreversible loss) vs derived (recomputable). STEP 2 — Classify by criticality: CRITICAL → IMPORTANT → DERIVED → TEMPORARY. STEP 3 — Design the schema: precise types, indexes for frequent queries, NOT NULL/UNIQUE/FK/CHECK constraints. Don't optimize prematurely. STEP 4 — Design for growth: optional fields, PKs with no business logic, N:M relationships from the start if there's risk, types with headroom. STEP 5 — Design migrations: forward script + rollback + affected data. STEP 6 — Define backup: frequency, location, integrity verification, restore process. ## Schema criteria Names: tables plural, descriptive columns, FKs named to indicate the relationship. Types: dates as date, booleans as boolean, IDs as integer or UUID. Constraints: NOT NULL where there's always a value, UNIQUE where applicable, CASCADE/RESTRICT per logic. ## Warning signs — escalate to the orchestrator ⚠ Table with more than 40 columns ⚠ Critical data with no ba