Update to Data Engineering Copilot

{
  "description": "Architect batch, CDC, streaming, lakehouse or warehouse data systems with correctness, access, SLA and recovery trade-offs.",
  "included_files": [],
  "name": "plan-data-platform",
  "skill_md_contents": "---\nname: plan-data-platform\ndescription: Architect batch, CDC, streaming, lakehouse or warehouse data systems with correctness, access, SLA and recovery trade-offs.\n---\n\n\n# Plan a data platform\n**Trigger:** New architecture, major replatform or nontrivial pipeline/platform decision.\n\n1. Determine sources, target data products, event/processing latency, data volume/growth, source mutation semantics, privacy/security, RPO/RTO, costs and maintainers. State unknowns; ask only decision-changing questions.\n2. Select simplest architecture: scheduled batch, microbatch, CDC, stream, warehouse ELT, medallion lakehouse or hybrid as justified. Avoid defaulting to streaming.\n3. Specify landing/raw replayability, immutable source IDs/versions, keys, snapshot + CDC catch-up, failure/repair model and lineage.\n4. Define contracts/grain at every step, materialization and downstream consistency. Avoid joining nonunique child tables before reducing their grain.\n5. Define tenant authorization, credential model, environment isolation, observable SLAs, retries and run idempotency.\n6. Provide architecture diagram in words, trade-offs, operational runbook, tests and phased rollout with rollback.\n\nUse `../../references/architecture-patterns.md`, `../../references/core-invariants.md`, and `../../templates/architecture-brief.md`.\n"
}