| schemaVersion | 2026-04-11T00:00:00.000Z |
| skillId | backend/data-migration-backfill |
| name | data-migration-backfill |
| displayName | Data Migration Backfill |
| description | Use when working on schema migrations, data migrations, backfills, dual writes, and rollout plans. Focus on reversibility, idempotency, batching, verification, and rollback safety. |
| aliases | ["data-migration-backfill","Data Migration Backfill","datamigrationbackfill","迁移","数据迁移","migration","数据回填","补数据","backfill","服务端","server side","migration plan","backfill job"] |
| version | 0.1.0 |
| sourceHash | sha256:decda60aeed0e18fb3013aa1806903e5985575749f59e6a1c9625ef884b7e8de |
| domain | backend |
| departmentTags | ["backend-platform"] |
| sceneTags | ["architecture","release"] |
Data Migration Backfill
Use this skill when the task involves schema migrations, data migrations, backfills, dual writes, and rollout plans.
Goal: produce reliable engineering guidance and implementation steps focused on reversibility, idempotency, batching, verification, and rollback safety.
Working model
- Identify the affected system, data, users, and failure modes.
- Define invariants, inputs, outputs, ownership, and rollback needs.
- Prefer small, auditable changes with explicit validation.
- Call out security, performance, concurrency, and data-loss risks when relevant.
- Finish with concrete verification steps and residual risks.
Rules
- Ground recommendations in the current codebase or runtime evidence.
- Prefer explicit contracts, typed boundaries, and defensive validation.
- Do not hide operational concerns behind generic best practices.
- Include negative cases, edge cases, and failure behavior.
- For review tasks, list findings first with file and line references when possible.
- For test or performance tasks, define the workload, success criteria, and measurement method.
Checklist
- Are assumptions and ownership boundaries explicit?
- Are risky changes reversible or safely deployable?
- Are observability and diagnostics sufficient for production issues?
- Are tests or validation steps targeted to the actual risk?
- Are security and data-integrity concerns addressed?
