আপনার এজেন্টের জন্য উপযুক্ত সক্ষমতা খুঁজে নিন।
Deep analysis debugging mode for complex issues. Activates methodical investigation protocol with evidence gathering, hypothesis testing, and rigorous verification. Use when standard troubleshooting fails or when issues require systematic root cause analysis.
Systematic debugging with 5-step loop for issues in spaces/[project]/. Use when encountering bugs, test failures, or unexpected behavior.
Bundle size optimization including tree shaking, code splitting, and dependency analysis. Use when reducing bundle size.
This skill should be used when debugging full-stack issues that span UI, backend, and database layers. It provides a systematic workflow to detect errors, analyze root causes, apply fixes iteratively, and verify solutions through automated server restarts and browser-based testing. Ideal for scenarios like failing schedulers, import errors, database issues, or API payload problems where issues originate in backend code but manifest in the UI.
Debug Laravel applications systematically with this comprehensive troubleshooting skill. Covers class/namespace errors, database SQLSTATE issues, route problems (404/405), Blade template errors, middleware issues (CSRF/auth), queue job failures, and cache/session problems. Provides structured four-phase debugging methodology with Laravel Telescope, Debugbar, Artisan tinker, and logging best practices for development and production environments.
Analyzes Ecto queries for N+1 problems, missing preloads, and performance issues.
分析后端性能问题，检测 N+1 查询、无分页查询、全表扫描、AI 服务超时等。使用此 Skill 来评估系统性能瓶颈、检测数据库查询问题、或优化 API 响应时间。
This skill should be used when the user asks to "test Electron app", "automate Electron desktop app", "debug Electron renderer", "test VS Code extension", "E2E test Electron", or needs Chrome DevTools Protocol automation for Electron applications. Use for renderer process debugging, main process control, native menu automation, and file dialog testing.
Four-phase debugging methodology with root cause analysis. Use when investigating bugs, fixing test failures, or troubleshooting unexpected behavior. Emphasizes NO FIXES WITHOUT ROOT CAUSE FIRST.
Analyze reproduction evidence to identify the root cause of bugs. Use after reproduction to trace execution and find the exact location and reason for the failure.
Analyze Cloudflare architecture and predict monthly costs with optimization recommendations. Use this skill when the user asks about costs, billing, pricing, or wants to understand their Cloudflare spend. Works with wrangler configs, observability data, and AI Gateway logs.
Expert Polyglot Frontend Engineer (20+ years exp). Strict adherence to documentation/references. Obsessed with performance, implementation details, and evidence-based coding.
Four-phase debugging methodology with root cause analysis. Use when investigating bugs, fixing test failures, or troubleshooting unexpected behavior. Emphasizes NO FIXES WITHOUT ROOT CAUSE FIRST.
Expert-level Rust performance optimization guidelines for build profiles, allocation, synchronization, async/await, and I/O. This skill should be used when writing, reviewing, or optimizing Rust code for performance. Triggers on tasks involving slow Rust code, large binary size, long compile times, LTO configuration, release profile tuning, allocation reduction, clone avoidance, lock contention, BufReader/BufWriter, flamegraph analysis, async runtime issues, Tokio performance, spawn_blocking, parking_lot vs std sync, or any Rust performance investigation.
Use when you need to inspect detailed execution flow of a Python program, stepping through functions and inspecting variable contents with pdb. Triggers include requests to debug Python scripts, trace execution, or inspect runtime state using the pdb debugger.
4-phase debugging framework preventing "guess-and-check" fixing. Load when debugging fails or for complex bug investigation.
Use when Python code runs slowly, needs profiling, requires async/await patterns, or needs concurrent execution - covers profiling tools, optimization patterns, and asyncio; measure before optimizing (plugin:python@dot-claude)
