Persistence Query Review
SkillDatabases & dataDesign and review Ayunis Core database access for avoidable round trips, check-then-act races, N+1 queries, and stale writes. Use when modifying or reviewing repositories, finders, QueryBuilder code, or application code that issues database calls in loops.
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What this skill tells your AI
The instructions your AI receives, as published by ayunis-core/ayunis-core in .claude/skills/persistence-query-review/SKILL.md and read by ahel’s review.
Choose the simplest database operation that preserves the required behavior under concurrency. Minimize round trips as part of that design; do not trade correctness or clear module boundaries for fewer queries.
Review the SQL Shape
For every changed persistence path:
- Trace the complete request-to-database call path, not only the changed method.
- Enumerate the SQL statements and network round trips on the happy path and relevant error paths.
- State what each read contributes: authorization data, domain decisions, existence detection, returned state, or relationship loading.
- Remove or combine reads that do not contribute independently observable behavior.
Challenge these patterns explicitly:
- A read used only to check existence before a write. Prefer the write's affected-row count or returned rows; a pre-read creates a check-then-act race.
- A write followed by a read used only to obtain the updated row. On PostgreSQL, prefer one
UPDATE ... RETURNINGorINSERT ... RETURNINGstatement. save()for an update-only contract. It may select or insert and can write stale aggregate fields; use an update operation that cannot create a missing record.- Database calls inside loops. Replace N+1 access with a join, relation load, batched
INquery, or set-based write when that preserves behavior. - Detached aggregates writing fields owned by another operation. Update only fields owned by the current operation, or use explicit concurrency control.
Preserve Semantics
Before combining statements, identify the actual contract:
- If current data is needed for authorization or a domain decision, the read is meaningful. Use a transaction or conditional write when the decision must remain valid through the write.
- If missing data must produce a domain error, derive it from zero affected or returned rows when possible.
- Use an upsert only when creation on absence is explicitly intended.
- If multiple statements are genuinely required to maintain an invariant, use the appropriate transaction and isolation or locking strategy. Do not remove them merely to reduce a query count.
- Treat QueryBuilder and database-specific SQL as infrastructure-adapter details. Keep application ports and domain code persistence-agnostic.
For TypeORM on PostgreSQL, Repository.update() is suitable when only the affected-row result is needed. Use QueryBuilder with .returning(...) when the operation must atomically return the authoritative stored row.
Verify the Decision
- Add behavioral coverage for the contract: success, missing row, concurrent/stale-field risk, and returned database-owned fields where relevant.
- When query count is a material performance contract, verify emitted SQL or round trips with a repository integration test or scoped instrumentation. Do not make domain tests depend on QueryBuilder call chains.
- Use
EXPLAIN (ANALYZE, BUFFERS)with representative data before claiming a query or new index is faster. Do not add indexes speculatively. - Report the before-and-after query shape and round-trip count in the review or PR summary.
Review Outcome
Flag a persistence change when an avoidable round trip, N+1 pattern, stale write, or check-then-act race remains. If extra statements are necessary, record the behavior or invariant that requires them.
Signals
- GitHub stars
- 33
- Forks
- 3
- Last commit
- Sep 2026
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persistence-query-review- Source
- github.com/ayunis-core/ayunis-core