Install any skill in seconds. Free to start, no credit card required.
Get Started Free →Design and verify data contracts, schema changes, migrations, rollbacks, backfills, compatibility windows, tenant isolation, and API-to-database field mapping. Use when changing database schema, event payloads, persisted documents, analytics tables, multi-tenant data boundaries, or any user-visible data contract where silent fallback or undeclared fields would be dangerous.
.claude/skills/majiayu000-data-contract-migrations/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-01 | ✗→✓ | ▲ Improved | -10% | 0% |
| case-02 | ✗→✓ | ▲ Improved | -18% | 0% |
| case-03 | ✗→✓ | ▲ Improved | -10% | 0% |
| case-04 | ✗→✓ | ▲ Improved | -5% | 0% |
| case-05 | ✗→✓ | ▲ Improved | -63% | 0% |
Use this skill when data shape changes can break reads, writes, reports, tenants, or integrations. The goal is an explicit compatibility and migration plan, not just a SQL diff.
Gather these facts before proposing changes:
If the current data does not contain a field, treat it as absent. Do not invent fallback fields.
Use expand-migrate-contract for production systems:
For small systems, a direct migration is acceptable only when downtime, rollback, and data loss risks are explicitly low.
Every plan must include:
textcontract_change: affected_readers_writers: migration_strategy: backfill_plan: rollback_or_recovery: tenant_and_security_checks: verification_queries: test_commands: release_gate:
Raise errors for missing critical data rather than warning and falling back to incomplete output.
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→pass | 24,679 | 22,329 | -10% | 1 | 1 | 0% | 4,425 | 3,984 | -10% | 0 | 0 | — |
case-02 | fail→pass | 21,292 | 14,898 | -30% | 1 | 1 | 0% | 3,906 | 3,207 | -18% | 0 | 0 | — |
case-03 | fail→pass | 24,398 | 17,771 | -27% | 1 | 1 | 0% | 4,215 | 3,785 | -10% | 0 | 0 | — |
case-04 | fail→pass | 17,733 | 13,730 | -23% | 1 | 1 | 0% | 3,098 | 2,930 | -5% | 0 | 0 | — |
case-05 | fail→pass | 19,740 | 4,903 | -75% | 1 | 1 | 0% | 3,439 | 1,270 | -63% | 0 | 0 | — |
case-06 | fail→pass | 9,840 | 10,902 | +11% | 1 | 1 | 0% | 1,822 | 2,426 | +33% | 0 | 0 | — |
case-07 | fail→pass | 15,522 | 12,505 | -19% | 1 | 1 | 0% | 2,594 | 2,543 | -2% | 0 | 0 | — |
case-08 | fail→pass | 16,028 | 12,143 | -24% | 1 | 1 | 0% | 2,712 | 2,542 | -6% | 0 | 0 | — |
case-09 | fail→pass | 15,628 | 16,315 | +4% | 1 | 1 | 0% | 2,433 | 3,295 | +35% | 0 | 0 | — |
case-10 | fail→pass | 18,186 | 15,853 | -13% | 1 | 1 | 0% | 2,849 | 3,150 | +11% | 0 | 0 | — |
case-11 | fail→pass | 17,204 | 13,414 | -22% | 1 | 1 | 0% | 2,724 | 2,538 | -7% | 0 | 0 | — |
case-12 | pass→pass | 20,819 | 17,922 | -14% | 1 | 1 | 0% | 3,335 | 3,528 | +6% | 0 | 0 | — |
case-13 | fail→pass | 15,174 | 14,819 | -2% | 1 | 1 | 0% | 2,436 | 2,885 | +18% | 0 | 0 | — |
case-14 | pass→pass | 18,408 | 17,255 | -6% | 1 | 1 | 0% | 3,287 | 3,723 | +13% | 0 | 0 | — |
case-15 | pass→pass | 17,541 | 12,033 | -31% | 1 | 1 | 0% | 2,966 | 2,576 | -13% | 0 | 0 | — |
case-16 | pass→pass | 12,183 | 9,268 | -24% | 1 | 1 | 0% | 2,034 | 1,955 | -4% | 0 | 0 | — |
case-17 | fail→fail | 14,695 | 5,618 | -62% | 1 | 1 | 0% | 2,210 | 1,290 | -42% | 0 | 0 | — |
case-18 | fail→pass | 11,640 | 8,841 | -24% | 1 | 1 | 0% | 1,687 | 1,713 | +2% | 0 | 0 | — |
case-19 | pass→pass | 10,412 | 12,149 | +17% | 1 | 1 | 0% | 1,765 | 2,412 | +37% | 0 | 0 | — |
case-20 | pass→fail | 15,552 | 5,442 | -65% | 1 | 1 | 0% | 2,577 | 1,366 | -47% | 0 | 0 | — |
case-21 | pass→fail | 24,085 | 23,877 | -1% | 1 | 1 | 0% | 3,837 | 4,363 | +14% | 0 | 0 | — |
case-22 | pass→pass | 15,290 | 15,821 | +3% | 1 | 1 | 0% | 3,070 | 3,498 | +14% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted. The headline lift of +33 percentage points is the difference between those two pass rates over the 22 comparable cases. 2 cases got worse with the skill loaded, and they are included in that figure.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.