Sizes database connection pools for Postgres/MySQL apps from a short JSON of services, pods, workers, threads and pool settings - worst-case connections at autoscale max and during deploy surges vs max_connections, busy connections from rps x hold time, per-process wait odds (Erlang C), CPU and memory limits, PgBouncer client and server limits. Recommends pool sizes or proxy settings. Includes an offline stdlib Python calculator with --self-test. 来源：https://prompts.chat/prompts/cmvxi8kpe0008l508b4ttzkaq
Reviews SQL queries and optional EXPLAIN output for common performance problems such as SELECT *, functions or casts on indexed columns, leading-wildcard LIKE, N+1 query loops, OR across columns vs UNION ALL, AND/OR precedence slips, NOT IN subqueries, deep OFFSET paging, seq scans and disk sorts. Explains each problem and gives a rewritten query. Includes a stdlib Python checker with --self-test. 来源：https://prompts.chat/prompts/cmvni9hqj000gi308xwj9rj0t
Checks pip requirements and constraints files offline before they break a build - unpinned and lower-bound-only packages, PEP 440 specifier conflicts across files and markers, git refs without a commit hash, editable and local paths, partial hash mode, pre-releases, --extra-index-url dependency confusion, http indexes, stdlib backports, dev tools in runtime files and pip freeze drift. Includes a stdlib Python checker with --self-test. 来源：https://prompts.chat/prompts/cmvyxzied0001k108wkm9h02b
Reviews a schema and slow SQL queries, proposes composite indexes in the right column order (equality, sort, range) with covering columns and tradeoffs, flags non-sargable filters like functions on columns and leading-wildcard LIKE, and warns about duplicate, redundant, and low-selectivity indexes. Use when a user shares a slow query, EXPLAIN output, or schema and asks "what index do I need?" or "too many indexes?". Includes a tested stdlib Python helper. 来源：https://prompts.chat/prompts/cmv6dyatr000bl80667elnhdv
Reads Postgres EXPLAIN and EXPLAIN ANALYZE plans (text or JSON) and finds why a query is slow - sequential scans on large relations, nested loops with huge row estimates, misestimates (estimated vs actual), high buffer reads, Sort/Hash that spill to disk, missing LIMIT pushdown and expensive nodes by actual time. Ranks fixes (index, rewrite, stats). Offline stdlib Python analyzer. 来源：https://prompts.chat/prompts/cmw4o8kqi000bl907icyyseeq
