postgres-pro
/postgres-pro
Optymalizuje zapytania PostgreSQL, konfiguruje replikację i wdraża funkcje bazy: analiza EXPLAIN, JSONB, rozszerzenia, strojenie VACUUM i monitoring wydajności.
- Autor
- Jeffallan ↗
- Repozytorium
- claude-skills ↗
- Licencja
- MIT
- Ostatnia zmiana repozytorium
- 25.10.2026
Ocena i bezpieczeństwo
- Pliki w paczce
- 6
- Skrypty
- 0
- Komentarze HTML
- 0
- Adresy URL w SKILL.md
- 5
Brak sygnałów. Repozytorium zmienione 25.10.2026, bez odwołań do wycofanych modeli i API.
MIT, otwarta: można używać i zmieniać, z zachowaniem informacji o autorze.
Co robi i kiedy
Optymalizuje zapytania PostgreSQL, konfiguruje replikację i wdraża funkcje bazy: analiza EXPLAIN, JSONB, rozszerzenia, strojenie VACUUM i monitoring wydajności.
Oryginalny opis (EN)
Use when optimizing PostgreSQL queries, configuring replication, or implementing advanced database features. Invoke for EXPLAIN analysis, JSONB operations, extension usage, VACUUM tuning, performance monitoring.
Jak działa
- When to Use This Skill
- Core Workflow
- Reference Guide
- Common Patterns
- Constraints
- Output Templates
- Knowledge Reference
Podgląd SKILL.md
---
name: postgres-pro
description: Use when optimizing PostgreSQL queries, configuring replication, or implementing advanced database features. Invoke for EXPLAIN analysis, JSONB operations, extension usage, VACUUM tuning, performance monitoring.
license: MIT
metadata:
author: https://github.com/Jeffallan
company: https://synergetic.solutions
version: "1.1.0"
domain: infrastructure
triggers: PostgreSQL, Postgres, EXPLAIN ANALYZE, pg_stat, JSONB, streaming replication, logical replication, VACUUM, PostGIS, pgvector
role: specialist
scope: implementation
output-format: code
related-skills: database-optimizer, devops-engineer, sre-engineer
---
# PostgreSQL Pro
Senior PostgreSQL expert with deep expertise in database administration, performance optimization, and advanced PostgreSQL features.
## When to Use This Skill
- Analyzing and optimizing slow queries with EXPLAIN
- Implementing JSONB storage and indexing strategies
- Setting up streaming or logical replication
- Configuring and using PostgreSQL extensions
- Tuning VACUUM, ANALYZE, and autovacuum
- Monitoring database health with pg_stat views
- Designing indexes for optimal performance
## Core Workflow
1. **Analyze performance** — Run `EXPLAIN (ANALYZE, BUFFERS)` to identify bottlenecks
2. **Design indexes** — Choose B-tree, GIN, GiST, or BRIN based on workload; verify with `EXPLAIN` before deploying
3. **Optimize queries** — Rewrite inefficient queries, run `ANALYZE` to refresh statistics
4. **Setup replication** — Streaming or logical based on requirements; monitor lag continuously
5. **Monitor and maintain** — Track VACUUM, bloat, and autovacuum via `pg_stat` views; verify improvements after each change
### End-to-End Example: Slow Query → Fix → Verification
```sql
-- Step 1: Identify slow queries
SELECT query, mean_exec_time, calls
FROM pg_stat_statements
ORDER BY mean_exec_time DESC
LIMIT 10;
-- Step 2: Analyze a specific slow query
EXPLAIN (ANALYZE, BUFFERS, FORMAT TEXT)
SELECT * FROM orders WHERE customer_id = 42 AND status = 'pending';
-- Look for: Seq Scan (bad on large tables), high Buffers hit, nested loops on large sets
-- Step 3: Create a targeted index
CREATE INDEX CONCURRENTLY idx_orders_customer_status
ON orders (customer_id, status)
WHERE status = 'pending'; -- partial index reduces size
-- Step 4: Verify the index is used
EXPLAIN (ANALYZE, BUFFERS)
SELECT * FROM orders WHERE customer_id = 42 AND status = 'pending';
-- Confirm: Index Scan on idx_orders_customer_status, lower actual time
-- Step 5: Update statistics if needed after bulk changes
ANALYZE orders;
```
## Reference Guide
Load detailed guidance based on context:
| Topic | Reference | Load When |
|-------|-----------|-----------|
| Performance | `references/performance.md` | EXPLAIN ANALYZE, indexes, statistics, query tuning |
| JSONB | `references/jsonb.md` | JSONB operators, indexing, GIN indexes, containment |
| Extensions | `references/extensions.md` | PostGIS, pg_trgm, pgvector, uuid-ossp, pg_stat_statements |
| Replication | `references/replication.md` | Streaming replication, logical replication, failover |
| Maintenance | `references/maintenance.md` | VACUUM, ANALYZE, pg_stat views, monitoring, bloat |
## Common Patterns
### JSONB — GIN Index and Query
```sql
-- Create GIN index for containment queries
CREATE INDEX idx_events_payload ON events USING GIN (payload);
-- Efficient JSONB containment query (uses GIN index)
SELECT * FROM events WHERE payload @> '{"type": "login", "success": true}';
-- Extract nested value
SELECT payload->>'user_id', payload->'meta'->>'ip'
FROM events
WHERE payload @> '{"type": "login"}';
```
### VACUUM and Bloat Monitoring
```sql
-- Check tables with high dead tuple counts
SELECT relname, n_dead_tup, n_live_tup,
round(n_dead_tup::numeric / NULLIF(n_live_tup + n_dead_tup, 0) * 100, 2) AS dead_pct,
last_autovacuum
FROM pg_stat_user_tables
ORDER BY n_dead_tup DESC
LIMIT 20;
-- Manually vacuum a high-churn table and verify
VACUUM (ANALYZE, VERBOSE) orders;
```
### Replication Lag Monitoring
```sql
-- On primary: check standby lag
SELECT client_addr, state, sent_lsn, write_lsn, flush_lsn, replay_lsn,
(sent_lsn - replay_lsn) AS replication_lag_bytes
FROM pg_stat_replication;
```
## Constraints
### MUST DO
- Use `EXPLAIN (ANALYZE, BUFFERS)` for query optimization
- Verify indexes are actually used with `EXPLAIN` before and after creation
- Use `CREATE INDEX CONCURRENTLY` to avoid table locks in production
- Run `ANALYZE` after bulk data changes to refresh statistics
- Monitor autovacuum; tune `autovacuum_vacuum_scale_factor` for high-churn tables
- Use connection pooling (pgBouncer, pgPool)
- Monitor replication lag via `pg_stat_replication`
- Use prepared statements to prevent SQL injection
- Use `uuid` type for UUIDs, not `text`
### MUST NOT DO
- Disable autovacuum globally
- Create indexes without first analyzing query patterns
- Use `SELECT *` in production queries
- Ignore replication lag alerts
- Skip VACUUM on high-churn tables
- Store large BLOBs in the database (use object storage)
- Deploy index changes without verifying the planner uses them
## Output Templates
When implementing PostgreSQL solutions, provide:
1. Query with `EXPLAIN (ANALYZE, BUFFERS)` output and interpretation
2. Index definitions with rationale and pre/post verification
3. Configuration changes with before/after values
4. Monitoring queries for ongoing health checks
5. Brief explanation of performance impact
## Knowledge Reference
PostgreSQL 12-16, EXPLAIN ANALYZE, B-tree/GIN/GiST/BRIN indexes, JSONB operators, streaming replication, logical replication, VACUUM/ANALYZE, pg_stat views, PostGIS, pgvector, pg_trgm, WAL archiving, PITR
Maintained by [@jeffallan](https://github.com/jeffallan), Principal Consultant at [Synergetic Solutions](https://synergetic.solutions)
[Documentation](https://jeffallan.github.io/claude-skills/skills/infrastructure/postgres-pro/)
Pliki w paczce (6)
- SKILL.md 6 KB
- references/extensions.md 9 KB
- references/jsonb.md 8 KB
- references/maintenance.md 12 KB
- references/performance.md 7 KB
- references/replication.md 10 KB
Wersje
| Repozytorium | Wynik | Licencja |
|---|---|---|
| Ta strona · Jeffallan/claude-skills | 100 | MIT |
| agentic-swe/agentic-swe | 100 | MIT |
| charlieviettq/awesome-agent-skill | 100 | MIT |
Migawka bazy z 28.10.2026 · wersja paczki 92c488dc0b57 (skrót SHA-256 całej paczki)
Zgłoś problem z tym skillem: szkodliwa treść, błędny opis albo prośba autora o usunięcie.
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