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By JosiahSiegel
Optimize T-SQL queries on SQL Server and Azure SQL Database by analyzing SARGability issues, execution plans, and performance bottlenecks; receive index suggestions, advanced pattern recommendations like recursive CTEs and window functions, and Azure-specific tuning strategies via skills, commands, and an expert agent.
npx claudepluginhub josiahsiegel/claude-plugin-marketplace --plugin tsql-masterUses power tools
Uses Bash, Write, or Edit tools
Has parse errors
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Analyze a T-SQL query for optimization opportunities, SARGability issues, and index recommendations
Help interpret SQL Server execution plan operators and identify performance issues
Suggest optimal indexes for a T-SQL query or table based on query patterns
Advanced T-SQL patterns and techniques for SQL Server. Use this skill when: (1) User needs help with CTEs or recursive queries, (2) User asks about APPLY operator, (3) User wants MERGE or OUTPUT clause help, (4) User works with temporal tables, (5) User needs In-Memory OLTP guidance, (6) User asks about advanced grouping (ROLLUP, CUBE, GROUPING SETS).
Azure SQL Database optimization and platform-specific features. Use this skill when: (1) User asks about Azure SQL Database optimization, (2) User needs DTU/vCore guidance, (3) User wants to use automatic tuning, (4) User asks about Hyperscale or serverless, (5) User needs Azure SQL performance monitoring.
SQL Server index design and optimization strategies. Use this skill when: (1) User needs help designing indexes, (2) User asks about clustered vs nonclustered indexes, (3) User wants to optimize columnstore indexes, (4) User needs filtered or covering indexes, (5) User asks about index maintenance and fragmentation.
T-SQL query optimization techniques for SQL Server and Azure SQL Database. Use this skill when: (1) User needs to optimize slow queries, (2) User asks about SARGability or index seeks, (3) User needs help with query hints, (4) User has parameter sniffing issues, (5) User needs to understand execution plans, (6) User asks about statistics and cardinality estimation.
Complete T-SQL function reference for SQL Server and Azure SQL Database. Use this skill when: (1) User asks about T-SQL string, date, math, or conversion functions, (2) User needs help with window/ranking functions, (3) User works with JSON or XML in T-SQL, (4) User asks about aggregate functions or GROUP BY, (5) User needs system or metadata functions.
Complete SQL Server Data Tools (SSDT) expertise system with SQL Server 2025 RC and SqlPackage 170.2.70 support. PROACTIVELY activate for: (1) ANY SSDT task (database projects/SqlPackage/schema compare), (2) SQL Server 2025 features (Optimized Locking, Fabric Mirroring, native JSON, RegEx, REST APIs), (3) Vector databases with DiskANN indexing and hybrid AI search, (4) SDK-style (Microsoft.Build.Sql 2.0.0 GA) and legacy project management, (5) DACPAC/BACPAC operations with data virtualization and parquet support, (6) SqlPackage 170.x all 7 actions (publish/extract/export/import/deployreport/driftreport), (7) CI/CD best practices 2025 (tSQLt unit testing, state-based deployment, Windows auth), (8) Microsoft Fabric Data Warehouse deployment with zero-ETL, (9) Cross-platform builds (.NET 8+ required), (10) Windows/Git Bash path handling (MSYS_NO_PATHCONV, shell detection), (11) Production-ready enterprise database development. Provides: SqlPackage 170.2.70 complete reference, Microsoft.Build.Sql 2.0.0 GA SDK guidance, SQL Server 2025 RC features (TID Locking, LAQ, change feed), tSQLt unit testing patterns, deployment safety (BlockOnPossibleDataLoss), refactoring workflows, GitHub Actions/Azure DevOps 2025 patterns with Windows auth, Git Bash/MINGW path conversion workarounds (MSYS_NO_PATHCONV, double-slash), shell detection for cross-platform scripts, and Visual Studio 2022 17.12+ support. Ensures safe, modern database development following 2025 Microsoft best practices.
DevsForge SQL optimization specialist for improving query performance and database efficiency
Official Claude plugin for Azure Cosmos DB (NoSQL). Bundles skills for data modeling, partition key design, query optimization, SDK best practices, indexing, vector search, full-text search, global distribution, security, and more.
Expert bash/shell scripting system with Bash 5.3 features, 2025 security-first practices, advanced array patterns, parallel processing, and comprehensive cross-platform support. PROACTIVELY activate for: (1) ANY bash/shell script task, (2) Windows Git Bash path conversion (MSYS_NO_PATHCONV, cygpath), (3) Bash 5.3 features (${ } in-shell substitution, ${| } REPLY syntax, BASH_TRAPSIG, GLOBSORT, fltexpr, BASH_MONOSECONDS), (4) Security-first patterns (input validation, command injection prevention), (5) ShellCheck v0.11.0 validation (SC2327/SC2328, POSIX.1-2024), (6) Advanced arrays (mapfile, readarray, associative arrays, set operations), (7) Parallel processing (GNU Parallel, xargs -P, job pools, worker patterns), (8) Process substitution and FIFOs (coprocesses, named pipes, streaming), (9) String manipulation mastery (parameter expansion, regex, pattern matching), (10) Modern automation (containers/CI/CD/cloud), (11) Scripts under 50 lines (Google Style), (12) Debugging and profiling (tracing, performance optimization), (13) DevOps/deployment automation. Provides: bash-expert agent for complex tasks, /bash-analyze for script analysis, /bash-template for production-ready templates, /bash-optimize for performance optimization, utility scripts (parallel-runner, shellcheck-batch, script-profiler), comprehensive skills for array patterns, process substitution, parallel processing, and string manipulation. Ensures secure, optimized, cloud-native scripts following 2025 standards.
Complete Azure Data Factory expertise for pipeline JSON development, validation, and optimization (2025-2026). This plugin should be used for ADF pipeline creation, activity configuration, linked services, datasets, triggers, expressions, CI/CD, Microsoft Fabric integration, Databricks orchestration, ML pipeline patterns, and debugging.
Complete Vitest 4.0 Playwright 1.56 MSW 2.x testing system with 2025 best practices and Windows/Git Bash support. PROACTIVELY activate for: (1) ANY testing task (unit/integration/E2E/visual), (2) Browser Mode testing (Vitest 4.0 stable release Oct 2025), (3) Visual regression testing (toMatchScreenshot), (4) Playwright AI Test Agents (planner/generator/healer), (5) Test annotation and metadata (Vitest 3.2+), (6) Mutation testing for quality assurance, (7) Test creation and scaffolding, (8) Playwright Traces debugging with titlePath, (9) Coverage analysis and optimization, (10) MSW 2.x mock management with happy-path-first patterns, (11) Role-based locator patterns, (12) CI/CD test setup, (13) Multi-project test architecture, (14) Line-number filtering, (15) Windows/Git Bash cross-platform testing. Provides: Vitest 4.0 features (stable browser mode, visual regression with toMatchScreenshot, Playwright trace integration, toBeInViewport matcher), Playwright 1.56 features (AI agents - Planner/Generator/Healer, VS Code 1.105+ integration, titlePath hierarchy, Debian 13), MSW 2.x best practices (Fetch API primitives, domain-based handlers), Windows/Git Bash path conversion awareness and shell detection, mutation testing capabilities, intelligent test running, auto-scaffolding with boilerplate, coverage gap analysis, advanced snapshot management, parallel execution optimization, and comprehensive cross-platform 2025-compliant test infrastructure. Ensures production-ready testing with latest patterns across all platforms including Windows Command Prompt, PowerShell, Git Bash, macOS, and Linux.
Complete Azure DevOps and Azure Pipelines expertise system with Sprint 254-262 features and Windows/Git Bash compatibility (2025). PROACTIVELY activate for: (1) ANY Azure DevOps/Pipelines task, (2) YAML pipeline creation/editing with expression functions (iif, trim), (3) Windows agent Git Bash path conversion issues, (4) Cross-platform pipeline scripts (Windows/Linux/macOS), (5) Workload identity federation (OIDC) passwordless authentication, (6) Pipeline performance analytics and monitoring, (7) Template management and reusability, (8) Microsoft Security DevOps (MSDO) integration, (9) Stage dependencies visualization, (10) Agent v4 with ARM64 support, (11) New OS images (Ubuntu-24.04, Windows-2025, macOS-15), (12) GitHub Copilot integration (Sprint 262), (13) OAuth apps migration to Entra ID (Sprint 261), (14) Continuous Access Evaluation (CAE), (15) Pipeline debugging/troubleshooting, (16) CI/CD optimization, (17) Security/compliance implementation, (18) Azure DevOps CLI operations. Provides: Windows/Git Bash path handling mastery (MSYS_NO_PATHCONV, cygpath, shell detection), cross-platform script patterns, MINGW path conversion guidance, Windows agent troubleshooting, Sprint 254-262 latest features, workload identity federation setup and migration guidance (2025 security standard), pipeline performance analytics and cost tracking, Agent v4 on .NET 8 with ARM64 platform support, Microsoft Defender for DevOps with MSDO extension (replaces deprecated CredScan), GitHub Advanced Security integration, template patterns for code reuse, iif() ternary operator and trim() function, stage-level variables and dependency visualization, Ubuntu-24.04/Windows-2025/macOS-15 hosted agents, GitHub Copilot work item integration, latest YAML schema (always researches current docs), Microsoft best practices, multi-stage pipeline patterns, caching/parallelization, Azure Key Vault integration, comprehensive security scanning (SAST/dependency/container/IaC/secrets), deployment strategies, performance optimization, systematic debugging, and cost efficiency analysis. Ensures production-ready, secure, efficient, cross-platform pipelines following Microsoft 2025 standards.
Complete FFmpeg expertise system with comprehensive coverage of FFmpeg 8.0.1 (2025-11-20) features, VIRAL VIDEO CREATION for TikTok/YouTube Shorts/Instagram Reels/Twitter, KINETIC CAPTIONS (word-grow karaoke, bounce, pop, elastic, spring physics), hardware acceleration (NVIDIA NVENC, Intel QSV, AMD AMF, VAAPI, Vulkan), Docker/container usage, Modal.com serverless containers (CPU/GPU), Cloudflare Workers/WebAssembly (ffmpeg.wasm), CI/CD runner optimization (GitHub Actions), live streaming (RTMP/HLS/DASH/SRT/WebRTC/WHIP), audio processing and normalization, encoding optimization (CRF, presets, quality tuning), FFmpeg + OpenCV integration, PyAV Python bindings (FFmpeg 8.0+ compatible), and common gotchas/troubleshooting. PROACTIVELY activate for: (1) ANY FFmpeg task (encoding, transcoding, streaming, filtering), (2) VIRAL VIDEO creation (TikTok, YouTube Shorts, Instagram Reels, Twitter/X), (3) Short-form vertical video (9:16 aspect ratio), (4) Auto-captions and animated subtitles (CapCut-style), (5) KINETIC CAPTIONS with word-grow, bounce, pop, elastic effects, (6) Karaoke-style word highlighting with animations, (7) Video hook optimization (first 3 seconds), (8) Multi-platform batch export, (9) Social media video optimization, (10) Video format conversion (MP4, WebM, MKV, AVI), (11) Hardware acceleration setup (NVENC, CUDA, QSV, VAAPI, AMF, Vulkan), (12) Docker container FFmpeg usage (jrottenberg/ffmpeg, linuxserver/ffmpeg), (13) Modal.com serverless video processing (GPU/CPU containers, parallel processing, volumes), (14) Browser/WebAssembly FFmpeg (ffmpeg.wasm), (15) Cloudflare Workers video processing, (16) GitHub Actions/CI pipeline video processing, (17) Live streaming setup (RTMP ingest, HLS/DASH/WHIP/WebRTC delivery), (18) Audio encoding/normalization (AAC, MP3, loudnorm, EBU R128), (19) Quality optimization (CRF, bitrate, presets), (20) FFmpeg debugging and error resolution, (21) VVC/H.266, AV1, HEVC encoding, (22) Filter graphs and complex filtergraphs, (23) Batch processing and automation, (24) Whisper AI subtitle generation, (25) Content creator workflows, (26) FFmpeg to OpenCV frame handoff, (27) cv2.VideoCapture vs ffmpeg subprocess, (28) BGR RGB color format conversion gotchas, (29) Frame dimension order img[y,x] vs img[x,y], (30) ffmpegcv GPU-accelerated video I/O, (31) VidGear multi-threaded streaming, (32) Decord batch video loading for ML, (33) PyAV frame-level processing (av.open, VideoFrame, AudioFrame, filter graphs), (34) Pipe frames between FFmpeg and OpenCV, (35) OpenCV + FFmpeg + Modal parallel processing, (36) PyAV installation on Ubuntu 20.04/22.04/24.04, (37) Building PyAV against custom FFmpeg, (38) PyAV FFmpeg 8.0+ compatibility and features. Provides: KINETIC CAPTIONS skill (word-grow karaoke, spring physics, elastic bounce, platform-specific timing), VIRAL VIDEO skills (platform specs, hook templates, animated captions, batch social export), PyAV integration skill (installation guides, FFmpeg 8.0+ compatibility, av.open patterns, VideoFrame/AudioFrame NumPy conversion, filter graphs, encoding/decoding, seeking, RTSP streaming, memory management, thread safety, error handling), FFmpeg 8.0.1 patch release features, FFmpeg 8.0 Huffman features (Whisper AI filter, Vulkan compute codecs for FFv1/ProRes RAW/AV1/VP9, APV codec, VVC VA-API/QSV decoding, WHIP muxer for WebRTC, colordetect/pad_cuda/scale_d3d11 filters, ProRes RAW decoder, RealVideo 6.0, G.728), FFmpeg 7.1 LTS features (VVC decoder, MV-HEVC for Apple Vision Pro, xHE-AAC, Vulkan H.264/H.265), hardware acceleration guides, Docker best practices, Modal.com parallel processing patterns, WebAssembly limitations and workarounds, CI/CD optimization strategies, streaming protocol guidance, audio processing workflows, encoding presets and recommendations, systematic debugging approaches, FFmpeg + OpenCV integration patterns, BGR/RGB color conversion, ffmpegcv/VidGear/Decord/PyAV library guidance, and production-ready 2025-2026 configurations for all platforms.
Share bugs, ideas, or general feedback.
Profile and optimize database queries for performance
Database query optimization with index recommendations and EXPLAIN analysis
Use this agent when you need to optimize database performance for B2B applications at enterprise scale. This agent specializes in multi-tenant database optimization, query performance tuning, indexing strategies, connection pooling, and database scaling for SaaS platforms. Handles PostgreSQL, MySQL, MongoDB, and cloud database optimizations. Examples: