「vacuum」の検索結果

Designs and audits data retention and file compaction for an embedded SQLite datastore in a long-lived service — a unified retention registry (one declared policy per table), TTL / absolute-age / row-count-cap policies, a fail-loud coverage guard, WAL/checkpoint tuning, and auto_vacuum/incremental-vacuum so pruning actually shrinks the file. Use when a SQLite DB grows unbounded, a table has an index but no DELETE, a pruned DB never shrinks on disk, metrics are stored as raw events forever, or a new table needs bounding. Keywords retention policy, TTL, reaper, prune, VACUUM, auto_vacuum, incremental_vacuum, WAL checkpoint, freelist, DB bloat, row cap, per-tenant quota. NOT for Postgres/MySQL/server-DB partitioning or TTL, log-line rate-limiting/sampling, backup/replication, schema migrations, or query-performance indexing.

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Control Ecovacs DEEBOT robot vacuums through the Ecovacs Open Platform: device list, status, battery, cleaning start/pause/stop, dock return. Trigger phrases: ecovacs, deebot, robot vacuum, start cleaning, dock vacuum.

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PostgreSQL database administration — backup/restore (pg_dump, PITR, WAL archiving), health monitoring (connections, bloat, cache hit ratio, dead tuples), connection pooling (PgBouncer), replication (streaming, logical), vacuum/autovacuum tuning, and scheduled backups with retention. Use when user asks to backup a database, restore from backup, monitor database health, set up replication, or perform DBA tasks. Do NOT use for schema design (use db-sculptor), query optimization (use db-sculptor), or migration planning (use db-sculptor).

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Expert en optimisation de bases de données (query plans, indexing strategies, partitioning, vacuum)

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Diagnóstico e tuning de PostgreSQL — EXPLAIN ANALYZE, índice, VACUUM, bloat, lock, replicação, WAL, PITR e particionamento. Use quando o usuário disser "postgres", "query lenta", "índice", "EXPLAIN", "vacuum", "lock", "deadlock", "replicação", "conexões", "banco lento".

日本語の概要は準備中です。原文の説明を表示しています。

Use when optimizing PostgreSQL queries, configuring replication, or implementing advanced database features. Invoke for EXPLAIN analysis, JSONB operations, extension usage, VACUUM tuning, performance monitoring.

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Amazon Redshift is NOT PostgreSQL; corrects LLM mistakes; covers SQL, metadata, connectivity/auth, storage, query performance, and operations. Applies ONLY to Redshift (provisioned or Serverless). Pushes back on: CREATE INDEX, string_agg, pg_catalog, text type, SERIAL, stl_query. Triggers on: Redshift SQL, Redshift CREATE TABLE, Redshift COPY/UNLOAD, slow or suddenly slow Redshift query, EXPLAIN plan, queue wait, stale statistics/ANALYZE, result cache, Redshift permission denied, Redshift disk full, storage growth, snapshot/backup cost, ghost rows/bloat, VACUUM, spill to disk, distribution skew, Redshift system views, QUALIFY, PIVOT, MERGE, materialized views, Redshift Data API (Python/boto3), Redshift workload management (WLM), concurrency scaling, Redshift resize, Spectrum, awsdatacatalog, connection failures (SSL/TLS, ODBC/JDBC, connection limit), IAM/SAML federation, IAM Identity Center, datashares. Does NOT apply to: S3 policies, Athena, Glue/Iceberg outside Redshift, Aurora, RDS, DynamoDB.

日本語の概要は準備中です。原文の説明を表示しています。

Optimizes PostgreSQL queries, configures replication, implements advanced features including EXPLAIN analysis, JSONB operations, extension usage, and VACUUM tuning.

日本語の概要は準備中です。原文の説明を表示しています。

This skill should be used when performing maintenance or diagnostics on remote Linux systems. Triggers on "remote server", "Linux maintenance", "Ubuntu cleanup", "Debian", "disk space", "apt cleanup", "journal vacuum", "snap cleanup", "system diagnostics". Provides structured three-phase checklists with quantification.

日本語の概要は準備中です。原文の説明を表示しています。

Use when the user wants to turn a static scene, character images, aerial map, drawn path, or route-control image into an immersive first-person FPV AI video prompt, especially Seedance/Kling/Runway/Veo style one-shot videos with numbered stop markers, red-line path control, world-map flythroughs, camera route planning, variable character counts, non-human POVs such as drones, pets, robot vacuums, character references, timed interactions, dialogue, spatial audio, and negative constraints.

日本語の概要は準備中です。原文の説明を表示しています。

Use when working with Redshift — amazon Redshift query performance, WLM configuration, table design analysis, vacuum/analyze status, and cluster health.

日本語の概要は準備中です。原文の説明を表示しています。