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Found 946 Skills
Use when the task asks for a visually strong landing page, website, app, prototype, demo, or game UI. This skill enforces restrained composition, image-led hierarchy, cohesive content structure, and tasteful motion while avoiding generic cards, weak branding, and UI clutter.
Find function callees with GrepAI trace. Use this skill to discover what functions a specific function calls.
Find function callers with GrepAI trace. Use this skill to discover what code calls a specific function.
Reference for all GrepAI MCP tools. Use this skill to understand available MCP tools and their parameters.
Best practices for Home Assistant automations, helpers, scripts, and device controls. TRIGGER THIS SKILL WHEN: - Creating or editing HA automations, scripts, or scenes - Choosing between template sensors and built-in helpers - Writing or restructuring triggers, conditions, or automation modes - Setting up Zigbee button/remote automations (ZHA or Zigbee2MQTT) - Renaming entities or migrating device_id references to entity_id SYMPTOMS THAT TRIGGER THIS SKILL: - Agent uses Jinja2 templates where native conditions, triggers, or helpers exist - Agent uses device_id instead of entity_id in triggers/actions - Agent modifies entity IDs or config objects without checking all consumers - Agent chooses wrong automation mode (e.g., single for motion lights)
Use when the user asks for text-to-speech narration or voiceover, accessibility reads, audio prompts, or batch speech generation via the OpenAI Audio API; run the bundled CLI (`scripts/text_to_speech.py`) with built-in voices and require `OPENAI_API_KEY` for live calls. Custom voice creation is out of scope.
Guidance for solving ARC-AGI style pattern recognition tasks that involve git operations (fetching bundles, merging branches) and implementing algorithmic transformations. This skill applies when tasks require merging git branches containing different implementations of pattern-based algorithms, analyzing input-output examples to discover transformation rules, and implementing correct solutions. (project)
Usability heuristics and principles based on Steve Krug's "Don't Make Me Think" and Jakob Nielsen's 10 heuristics. Use when you need to: (1) audit a UI for usability problems, (2) identify why users are confused or frustrated, (3) simplify navigation and information architecture, (4) conduct heuristic evaluations, (5) prioritize UX fixes by severity, (6) review designs before development, (7) improve form usability, (8) validate that interfaces follow established UX principles.
Ensures alignment between user and Claude during feature/spec planning through a structured interview process. Use this skill when the user invokes /plan-interview before implementing a new feature, refactoring, or any non-trivial implementation task. The skill runs an upfront interview to gather requirements across technical constraints, scope boundaries, risk tolerance, and success criteria before any codebase exploration. Do NOT use this skill for: pure research/exploration tasks, simple bug fixes, or when the user just wants standard planning without the interview process.
Create distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, artifacts, posters, or applications (examples include websites, landing pages, dashboards, React components, HTML/CSS layouts, or when styling/beautifying any web UI). Generates creative, polished code and UI design that avoids generic AI aesthetics.
Conduct comprehensive AI-powered research with citations via the Tavily CLI. Use this skill when the user wants deep research, a detailed report, a comparison, market analysis, literature review, or says "research", "investigate", "analyze in depth", "compare X vs Y", "what does the market look like for", or needs multi-source synthesis with explicit citations. Returns a structured report grounded in web sources. Takes 30-120 seconds. For quick fact-finding, use tavily-search instead.
Guidance for extracting and processing data from ELF (Executable and Linkable Format) binary files. This skill should be used when tasks involve parsing ELF headers, reading program segments, extracting memory contents, or converting binary data to structured formats like JSON. Applicable to reverse engineering, binary analysis, and memory dump extraction tasks.