with one click
postgres-patterns
쿼리 최적화, 스키마 설계, 인덱싱, 보안을 위한 PostgreSQL 데이터베이스 패턴. Supabase 모범 사례 기반.
Menu
쿼리 최적화, 스키마 설계, 인덱싱, 보안을 위한 PostgreSQL 데이터베이스 패턴. Supabase 모범 사례 기반.
Create reproducible, cross-platform (macOS/Linux) development environments with Flox, a declarative Nix-based environment manager. Use when setting up project toolchains for any language, installing system-level dependencies (compilers, databases, native libs like openssl/BLAS), pinning exact package versions for a team, running local services (PostgreSQL, Redis, Kafka), onboarding developers with one command, or solving 'works on my machine' problems — including agent/vibe-coding setups that need project-scoped tools without sudo. Also use when the user mentions .flox/, manifest.toml, flox activate, or FloxHub.
Commercial-grade Python installer expert for Windows: Nuitka extreme compilation, dist slimming, DLL footprint analysis, and Inno Setup packaging to ship the smallest, fastest installers. Use only for advanced packaging/optimization (minimal size, fast startup), not basic script-to-exe conversion. 中文触发:Nuitka 极限优化、Python 商业打包、极限编译 Python、dist 瘦身、DLL 分析、最小安装包、最快启动、商业级打包风格
Use when a brand needs to discover or articulate its identity through structured multi-session interviews. Covers purpose, positioning, audience, personality, voice, narrative, and founder-brand tension across 8 modules using laddering, 5 Whys, and projective techniques. Produces a resumable session with disk-persisted state and a master brandbook (90_SYNTHESIS.md).
Use when a brand needs to discover or articulate its identity through structured multi-session interviews. Covers purpose, positioning, audience, personality, voice, narrative, and founder-brand tension across 8 modules using laddering, 5 Whys, and projective techniques. Produces a resumable session with disk-persisted state and a master brandbook (90_SYNTHESIS.md).
Use this skill to automate visual testing and UI interaction verification using browser automation after deploying features.
Visualize whether skills, rules, and agent definitions are actually followed — auto-generates scenarios at 3 prompt strictness levels, runs agents, classifies behavioral sequences, and reports compliance rates with full tool call timelines
| name | postgres-patterns |
| description | 쿼리 최적화, 스키마 설계, 인덱싱, 보안을 위한 PostgreSQL 데이터베이스 패턴. Supabase 모범 사례 기반. |
| origin | ECC |
PostgreSQL 모범 사례 빠른 참조. 자세한 가이드는 database-reviewer 에이전트를 사용하세요.
| 쿼리 패턴 | 인덱스 유형 | 예시 |
|---|---|---|
WHERE col = value | B-tree (기본값) | CREATE INDEX idx ON t (col) |
WHERE col > value | B-tree | CREATE INDEX idx ON t (col) |
WHERE a = x AND b > y | Composite | CREATE INDEX idx ON t (a, b) |
WHERE jsonb @> '{}' | GIN | CREATE INDEX idx ON t USING gin (col) |
WHERE tsv @@ query | GIN | CREATE INDEX idx ON t USING gin (col) |
| 시계열 범위 | BRIN | CREATE INDEX idx ON t USING brin (col) |
| 사용 사례 | 올바른 타입 | 지양 |
|---|---|---|
| ID | bigint | int, random UUID |
| 문자열 | text | varchar(255) |
| 타임스탬프 | timestamptz | timestamp |
| 금액 | numeric(10,2) | float |
| 플래그 | boolean | varchar, int |
복합 인덱스 순서:
-- Equality columns first, then range columns
CREATE INDEX idx ON orders (status, created_at);
-- Works for: WHERE status = 'pending' AND created_at > '2024-01-01'
커버링 인덱스:
CREATE INDEX idx ON users (email) INCLUDE (name, created_at);
-- Avoids table lookup for SELECT email, name, created_at
부분 인덱스:
CREATE INDEX idx ON users (email) WHERE deleted_at IS NULL;
-- Smaller index, only includes active users
RLS 정책 (최적화):
CREATE POLICY policy ON orders
USING ((SELECT auth.uid()) = user_id); -- Wrap in SELECT!
UPSERT:
INSERT INTO settings (user_id, key, value)
VALUES (123, 'theme', 'dark')
ON CONFLICT (user_id, key)
DO UPDATE SET value = EXCLUDED.value;
커서 페이지네이션:
SELECT * FROM products WHERE id > $last_id ORDER BY id LIMIT 20;
-- O(1) vs OFFSET which is O(n)
큐 처리:
UPDATE jobs SET status = 'processing'
WHERE id = (
SELECT id FROM jobs WHERE status = 'pending'
ORDER BY created_at LIMIT 1
FOR UPDATE SKIP LOCKED
) RETURNING *;
-- Find unindexed foreign keys
SELECT conrelid::regclass, a.attname
FROM pg_constraint c
JOIN pg_attribute a ON a.attrelid = c.conrelid AND a.attnum = ANY(c.conkey)
WHERE c.contype = 'f'
AND NOT EXISTS (
SELECT 1 FROM pg_index i
WHERE i.indrelid = c.conrelid AND a.attnum = ANY(i.indkey)
);
-- Find slow queries
SELECT query, mean_exec_time, calls
FROM pg_stat_statements
WHERE mean_exec_time > 100
ORDER BY mean_exec_time DESC;
-- Check table bloat
SELECT relname, n_dead_tup, last_vacuum
FROM pg_stat_user_tables
WHERE n_dead_tup > 1000
ORDER BY n_dead_tup DESC;
-- Connection limits (adjust for RAM)
ALTER SYSTEM SET max_connections = 100;
ALTER SYSTEM SET work_mem = '8MB';
-- Timeouts
ALTER SYSTEM SET idle_in_transaction_session_timeout = '30s';
ALTER SYSTEM SET statement_timeout = '30s';
-- Monitoring
CREATE EXTENSION IF NOT EXISTS pg_stat_statements;
-- Security defaults
REVOKE ALL ON SCHEMA public FROM public;
SELECT pg_reload_conf();
database-reviewer - 전체 데이터베이스 리뷰 워크플로우clickhouse-io - ClickHouse 분석 패턴backend-patterns - API 및 백엔드 패턴Supabase Agent Skills 기반 (크레딧: Supabase 팀) (MIT License)