Total 46,766 skills
Showing 12 of 46766 skills
Debugs Windows applications using WinDbg and crash dump analysis including MCP server integration, live process attach, dump file triage, hang detection, high-CPU diagnosis, memory leak investigation, kernel debugging, symbol configuration, scenario command packs, diagnostic report generation, and SOS extension workflows for .NET runtime inspection.
Schema validation with Valibot, the modular and type-safe schema library. Use when the user needs to validate data, create schemas, parse inputs, or work with Valibot in their project. Also use when migrating from Zod to Valibot.
Scan multiple symbols with indicator conditions. Find stocks matching RSI oversold, EMA crossovers, Supertrend signals, and custom filter combinations.
Monitor repo changes made by another Claude Code instance, accumulate observations, and deliver a final review on request
This skill should be used when the agent needs to give a spoken voice update to the user, or when reminded by a Stop hook to provide audio feedback. Use this skill to speak a short summary of what was accomplished.
Use when a repo has `.xit/` or the user asks for xit: translate git-like intents to non-interactive `xit` CLI commands (`status/diff/log --cli`, add/commit/branch/merge/cherry-pick), avoid the TUI, and do not use git unless explicitly requested.
Create a custom technical indicator using Numba JIT + NumPy. Generates production-grade, O(n) optimized indicator functions with charting and benchmarking.
Perform image understanding and analysis using GLM Vision MCP. Trigger conditions: (1) Users request image analysis, image understanding, or description of image content (2) Need to identify objects, text, or scenes in images (3) Use GLM's visual understanding capabilities
Deploy applications to Vercel with automatic framework detection
Implements WPF data validation using ValidationRule, IDataErrorInfo, and INotifyDataErrorInfo. Use when building forms, validating user input, or displaying validation errors in UI.
Prompt engineering and optimization for AI/LLMs. Capabilities: transform unclear prompts, reduce token usage, improve structure, add constraints, optimize for specific models, backward-compatible rewrites. Actions: improve, enhance, optimize, refactor, compress prompts. Keywords: prompt engineering, prompt optimization, token efficiency, LLM prompt, AI prompt, clarity, structure, system prompt, user prompt, few-shot, chain-of-thought, instruction tuning, prompt compression, token reduction, prompt rewrite, semantic preservation. Use when: improving unclear prompts, reducing token consumption, optimizing LLM outputs, restructuring verbose requests, creating system prompts, enhancing prompt clarity.
Frontend development patterns for React, Next.js, state management, performance optimization, and UI best practices.