ORM

Expert search specialist mastering advanced information retrieval, query optimization, and knowledge discovery. Specializes in finding needle-in-haystack information across diverse sources with focus on precision, comprehensiveness, and efficiency.

Expert performance engineer specializing in system optimization, bottleneck identification, and scalability engineering. Masters performance testing, profiling, and tuning across applications, databases, and infrastructure with focus on achieving optimal response times and resource efficiency.

AGGRESSIVELY use TOON v2.0 format for biggish regular data (≥5 items, ≥60% uniform). Auto-applies to tables, logs, events, transactions, analytics, API responses, database results. Supports 3 array types (inline, tabular, expanded), 3 delimiters (comma, tab, pipe), key folding for nested objects. Triggers on structured data, arrays, repeated patterns. Use TOON by default when tokens matter - RAG pipelines, tool calls, agents, benchmarks. Keywords "data", "array", "list", "table", "log", "transaction", "metric", "analytics", "API", "database", "query", "TOON".

Complete guide to Next.js 16 features, breaking changes, and migration from v15. Use when building new Next.js projects or upgrading existing ones to leverage Turbopack, Cache Components, and latest performance optimizations.

Activate when users ask about Claude Code installation, slash commands (/cook, /plan, /fix, /test, /docs, /design, /git), creating/managing Agent Skills, configuring MCP servers, setting up hooks/plugins, IDE integration (VS Code, JetBrains), CI/CD workflows, enterprise deployment (SSO, RBAC, sandboxing), troubleshooting authentication/performance issues, or advanced features (extended thinking, caching, checkpointing).

Copilot agent that assists with performance analysis, bottleneck detection, optimization strategies, and benchmarking Trigger terms: performance optimization, performance tuning, profiling, benchmark, bottleneck analysis, scalability, latency optimization, memory optimization, query optimization Use when: User requests involve performance optimizer tasks.

Use when receiving code review feedback (especially if unclear or technically questionable), when completing tasks or major features requiring review before proceeding, or before making any completion/success claims. Covers three practices - receiving feedback with technical rigor over performative agreement, requesting reviews via code-reviewer subagent, and verification gates requiring evidence before any status claims. Essential for subagent-driven development, pull requests, and preventing false completion claims.

Copilot agent that assists with database operations, performance tuning, backup/recovery, monitoring, and high availability configuration Trigger terms: database administration, DBA, database tuning, performance tuning, backup recovery, high availability, database monitoring, query optimization, index optimization Use when: User requests involve database administrator tasks.

Copilot agent that assists with performance analysis, bottleneck detection, optimization strategies, and benchmarking Trigger terms: performance optimization, performance tuning, profiling, benchmark, bottleneck analysis, scalability, latency optimization, memory optimization, query optimization Use when: User requests involve performance optimizer tasks.

Optimize performance with profiling, caching strategies, database query optimization, and bottleneck analysis. Use when improving response times, implementing caching layers, or scaling for high load.

Advanced SOQL skill with natural language to query generation, query optimization, relationship traversal, aggregate functions, and performance analysis. Build efficient queries that respect governor limits and security requirements.

Kafka Connect integration expert. Covers source and sink connectors, JDBC, Elasticsearch, S3, Debezium CDC, SMT (Single Message Transforms), connector configuration, and data pipeline patterns. Activates for kafka connect, connectors, source connector, sink connector, jdbc connector, debezium, smt, data pipeline, cdc.

Intelligent serverless platform recommendation expert. Detects project context (pet-project, startup, enterprise), analyzes workload suitability, ranks platforms (AWS Lambda, Azure Functions, GCP Cloud Functions, Firebase, Supabase), and provides comprehensive recommendations with cost estimates. Activates for serverless recommendations, platform selection, AWS vs Azure vs GCP, Firebase vs Supabase, serverless architecture, should I use serverless, which serverless platform, serverless cost, serverless free tier, Lambda vs Functions, cloud functions comparison.

Expert cloud cost optimization strategies for AWS, Azure, GCP, and serverless platforms. Covers FinOps principles, right-sizing, reserved instances, savings plans, spot instances, storage optimization, database cost reduction, serverless cost modeling, budget management, cost allocation, chargeback models, and continuous cost optimization. Activates for cost optimization, cloud costs, reduce costs, save money, finops, cost analysis, budget overrun, expensive cloud bill, cost savings, reserved instances, spot instances, savings plans, right-sizing, cost allocation tags, chargeback, showback.

Creates or updates .daiv.yml configuration file with sandbox settings (base_image and format_code commands) based on repository content. Use when users request DAIV configuration setup or sandbox configuration.

Detect and warn about breaking API/schema changes before implementation. Auto-trigger when modifying API routes, database schemas, or public interfaces. Validates changes against api-strategy.md versioning rules. Suggests migration paths for breaking changes. Prevents removing endpoints, changing request/response formats, dropping database columns, modifying function signatures without deprecation.

Comprehensive performance analysis and optimization for algorithms (O(n²)→O(n)), databases (N+1 queries, indexes), React (memoization, virtual lists), bundles (code splitting), API caching, and memory leaks. 85%+ improvement rate. Use when application is slow, response times exceed SLA, high CPU/memory usage, performance budgets needed, or when user mentions 'performance', 'slow', 'optimization', 'bottleneck', 'speed up', 'latency', 'memory leak', or 'performance tuning'.

Apply Grey Haven Studio's TypeScript/React and Python/FastAPI coding standards from production templates. Use when writing code, reviewing PRs, fixing linting errors, formatting files, or when the user mentions 'code standards', 'Grey Haven style', 'linting', 'Prettier', 'ESLint', 'Ruff', 'formatting rules', or 'coding conventions'. Includes exact Prettier/ESLint/Ruff configs, naming conventions, project structure, and multi-tenant database patterns.

Specialized testing for React applications using TanStack ecosystem (Query, Router, Table, Form) with Vite and Vitest. Use when testing React + TanStack apps, mocking server state, testing router, or validating query behavior. Triggers: 'TanStack testing', 'React Query testing', 'test TanStack', 'mock query', 'router test'.

Performs code review following team's quality assurance guidelines. Use when the user asks to "review code", "check this code", "리뷰해줘", "코드 리뷰", "코드 검토", "이 코드 봐줘", "이거 괜찮아?", "확인해줘", "문제 없어?", or after writing code when they want feedback on the changes just made.