SKILL.md
db-query-patterns (M13)
How queries are written decides whether the indexes from M11 can even be used. This module inspects query shape in ORM source and raw SQL. Feeds the Performance & Scale score (axis performance, relational Query w18, shared with M3/M19).
What it checks
- **
SELECT *** — fetching all columns defeats covering indexes, bloats network/cache, and couples
code to column order. Flag in hot paths.
- Structural N+1 — a query inside a loop / per-row lazy relation load that should be a single
join or batched IN. Static detection is directional (the loop's runtime cardinality is unknown) — it points at the structure, never claims a row count.
- OFFSET pagination —
LIMIT n OFFSET mdegrades linearly with depth; deep pagination should use
keyset/seek (WHERE id > $last ORDER BY id LIMIT n).
- Non-SARGable predicates — wrapping the indexed column in a function (
WHERE lower(email)=…,
WHERE date(createdat)=…, leading-wildcard LIKE '%x', implicit type cast) so the index can't be used. Recommend an expression index or rewriting the predicate. For the leading-wildcard / LIKE '%x%' case a B-tree can never help — name the remedy: a pgtrgm GIN/GiST index on the column (or a dedicated search engine for heavy full-text search).
Score / axis
Feeds performance only (relational Query w18; Query category in document/time-series/graph profiles).
Tier-0 (static)
Grep ORM call sites and raw SQL for SELECT *, function-wrapped indexed columns, leading-wildcard LIKE, and OFFSET; detect query calls inside loops/.map/per-item relation access for N+1. All query-pattern findings are at most directional from source — confirming the actual plan/cost needs runtime (needs_api / Tier-2).
Tier-1/2 (verification query)
EXPLAIN (ANALYZE, BUFFERS) <the suspect query>;
Method explainplan. A Seq Scan where an index exists confirms a non-SARGable predicate; the actual rows × loops confirms an N+1 amplification. Tier-2 pgstatstatements (ordered by totalexec_time) surfaces the real hot queries — without it, hotness is directional.
Findings
Emit findings per schema/finding.schema.json. Examples:
M13.orders.selectstarhot_path—SELECT *in a frequent read (severity:2,warn, axis
performance, confidence directional, fixable: proposed).
M13.users.nplusone_posts— per-row relation load in a loop (severity:3,warn,directional,
fixable: advisory — requires app-side eager load / batching).
M13.feed.offsetdeeppagination—OFFSETdeep paging (severity:2,warn,directional,
fixable: proposed — keyset rewrite).
M13.users.nonsargablelower_email— function-wrapped indexed column (severity:3,warn,
directional, fixable: proposed — expression index or predicate rewrite).
Each finding: evidence.observed quotes the query / call site verbatim (secrets redacted); verification.reproduce is the EXPLAIN above referencing $DATABASEURL, or a grep for the pattern; expectedimpact is banded + confidence-tagged (no naked %).
Honesty
- N+1 is directional by design: a loop running twice is fine, the same loop over 10k rows is not —
static analysis cannot tell which, so it never caps and never quotes a multiplier.
SELECT *is harmless on a small lookup or a one-shot admin query — scope severity to hot paths.- Rewrites that change result semantics (keyset, predicate restructure) are
proposed/advisory,
never auto; expression-index additions can be proposed.