'sqlite' 검색 결과

Guide SQLite database design and performance tuning for applications. Covers concurrent reads and writes, indexes that speed up queries, full-text search, JSON processing, analytical queries, and versioned changes to database structure.

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• Investigating slow SQLite queries
• Reducing contention between database reads and writes
• Designing full-text search and JSON queries

Handle system backups and restore data from backup files while managing a SQLite database. The skill also covers data export, import, and incremental snapshots, which capture changes since an earlier saved state.

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• Create a system backup
• Restore data from a backup file
• Export or import SQLite data

Plan and implement a unified AgentDB memory backend for agents. Migrate SQLite and Markdown data, add HNSW indexing for similarity search, and support shared memory and SONA learning patterns while preserving compatibility with existing systems.

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• Consolidating separate agent memory systems
• Migrating SQLite and Markdown data to AgentDB
• Finding stored information with similar meaning

Plan and implement a unified AgentDB memory backend for agents. Migrate SQLite and Markdown data, add HNSW indexing for similarity search, and support shared memory and SONA learning patterns while preserving compatibility with existing systems.

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• Consolidating separate agent memory systems
• Migrating SQLite and Markdown data to AgentDB
• Finding stored information with similar meaning

Build and review Cloudflare Durable Objects for applications that retain shared state, such as chat rooms, games, and booking systems. Covers SQLite storage, remote method calls, WebSockets, scheduled work, Workers integration, configuration, and Vitest tests.

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• Build shared state for chat rooms, games, and bookings
• Implement remote methods, SQLite storage, WebSockets, and alarms
• Configure Workers bindings and migrations

Track shared work across AI agents using a SQLite database. The skill claims tasks, records progress and evidence for each step, skips completed work, and checks required procedures before marking a task complete.

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• Assigning work from a shared queue to multiple agents
• Resuming tasks while skipping completed steps
• Checking required procedures before task completion

Build Python MCP servers that let AI agents use APIs, databases, and file workflows. MCP is a connection standard for agent tools. The skill covers starter templates, local testing, client registration, and deployment as HTTP endpoints.

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• Making an existing API available to AI agents
• Exposing read-only SQLite queries
• Providing text-file inspection and search tools

Implement core TypeScript modules for claude-flow v3 using domain-driven design, which organizes code around distinct responsibilities. Build task and session domains, connect storage and services, and add unit and integration tests.

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• Build the core structure for claude-flow v3
• Implement task assignment and status rules
• Connect SQLite storage through dependency injection

Implement core TypeScript modules for claude-flow v3 using domain-driven design, which organizes code around distinct responsibilities. Build task and session domains, connect storage and services, and add unit and integration tests.

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• Build the core structure for claude-flow v3
• Implement task assignment and status rules
• Connect SQLite storage through dependency injection

Patterns for SQLite databases in Python projects - state management, caching, and async operations. Triggers on: sqlite, sqlite3, aiosqlite, local database, database schema, migration, wal mode.

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Check opencode commands, HTTP server behavior, lifecycle events, and terminal startup with purpose-built scripts. Find stored sessions by ID, title, or scoped message searches, and export conversations as JSON for further inspection.

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• Check CLI commands and HTTP server health
• Observe lifecycle events associated with plugin hooks
• Check terminal startup and keyboard input

Wire the Prisma Next runtime — `db.ts` setup using `postgres<Contract>(...)` from `@prisma-next/postgres/runtime`, `sqlite<Contract>(...)` from `@prisma-next/sqlite/runtime`, or `mongo<Contract>(...)` from `@prisma-next/mongo/runtime`; middleware composition (telemetry from `@prisma-next/middleware-telemetry`; lints and budgets), `DATABASE_URL` config, per-environment branching, switching between Postgres, SQLite, and Mongo façades. Use for db.ts, postgres(), sqlite(), mongo(), middleware, telemetry, lints, budgets, DATABASE_URL, .env, connection pool, poolOptions, dev vs prod config, transactions, db.transaction, read replicas, multi-database, script won't exit, hangs, close connection, db.end, db.close, pool.end, [Symbol.asyncDispose], await using.

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Write Prisma Next queries for Postgres, SQLite, or Mongo — pick a lane (Postgres/SQLite `db.orm.<Model>` + `db.sql.<table>`; Mongo `db.orm.<root>` + `db.query.from(...)` pipeline builder), filter / project / sort / paginate, eager-load with `.include(...)`, Postgres/SQLite `db.transaction(...)`, Postgres/SQLite ORM `.aggregate(...)`, Mongo aggregations via query builder, namespace-aware accessors (`db.orm.<ns>.<Model>`, `db.sql.<ns>.<table>`). Triggers: query, where, match, select, project, orderBy, take, skip, include, lookup, first, all, count, aggregate, group, create, update, delete, upsert, returning, transaction, db.close, script teardown, variant, polymorphism, drizzle-style, kysely-style. Notes: `.all()` is a Thenable (just `await` it), iterators are single-use (`RUNTIME.ITERATOR_CONSUMED`), Postgres `count` is `number` while sum/avg/min/max are `number | null`, ranges use chained `.where()` or `and(...)` (no `.between(...)`).

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Analyze Chrome, Edge, and other Chromium browser profiles with Hindsight to reconstruct web activity. Combine browsing history, downloads, cookies, and other stored records into a chronological timeline, with XLSX, JSON, or SQLite output for investigation.

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• Reconstructing browsing activity during incident response
• Checking download times and source URLs
• Comparing cookies and history in insider threat investigations

Turn a written app specification into a runnable starter project using the requested technology stack. Generate implemented features, tests, configuration files, and setup instructions, then check the project for common omissions.

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• Turning a requirements document into a starter project
• Creating a task API with FastAPI and SQLite
• Building a recipe-sharing website with Next.js

Collect operation events across an AI agent workflow and link them into traceable execution records. Search by tracking ID, time range, or responsible agent, with semantic indexing and local event storage to support audits and investigation.

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• Auditing handoffs and processing steps across multiple agents
• Tracing related operations with a tracking ID
• Finding past events by time range or responsible agent

Record operations across multiple AI agents and connect events into a traceable history. Search records by tracking ID, time window, or responsible component to support audits and investigations, with local storage available when the vector database fails.

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• Trace task dispatch and execution across agents
• Search audit records by time or responsible component
• Keep recording events during vector database failures

Diagnose excessive Codex local SQLite diagnostic log writes with read-only evidence by default. Use when a user mentions logs_2.sqlite, logs_2.sqlite-wal, block_log_inserts, SSD/TBW wear, or explicitly asks to protect, clean up, verify, or restore Codex diagnostic logging.

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Use for bun:sqlite, SQLite operations, prepared statements, transactions, and queries.

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Build serverless applications with Cloudflare D1 — SQLite at the edge. Use when someone asks to "serverless database", "Cloudflare D1", "SQLite at the edge", "database for Workers", "edge database", or "serverless SQL". Covers schema setup, queries, migrations, Workers integration, and Drizzle ORM.

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SQLite database expertise for migrations, multi-tenant patterns, transactional safety, FTS5 virtual tables, and schema evolution. Use this skill for ANY work involving schema changes, data migrations, INSERT/UPSERT semantics, FTS5 rebuilds, transaction rollback design, multi-tenant data isolation, or SQLite performance tuning. Triggers include: writing migration SQL, modifying `_import_table`-style importers, designing UNIQUE/PK constraints, adding indexes for JOINs, debugging "rows missing" / "wrong count" / "stuck for hours" symptoms in SQLite-backed systems.

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High concurrent SQLite access causing lock contention and missing indexes Keywords: sqlite, wal, indexes, performance

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Expert in SQLite embedded database development for Tauri/desktop applications with focus on SQL injection prevention, migrations, FTS search, and secure data handling

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Use when a SQLite database in WAL mode has a growing -wal file, repeated incomplete checkpoints, SQLITE_BUSY, disk-pressure risk, or reader slowdowns that may indicate checkpoint starvation.

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