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Found 588 Skills
This skill should be used when the user asks to "create a ReAct agent", "build an agent with tools", "implement tool-calling agent", "use dspy.ReAct", mentions "agent with tools", "reasoning and acting", "multi-step agent", "agent optimization with GEPA", or needs to build production agents that use tools to solve complex tasks.
Serves as a reviewer of the codebase with instructions on looking for Apple App Store optimizations or rejection reasons.
Detect buying intent from job postings. When a company posts a job in your problem area, they've allocated budget and are actively thinking about the problem. This skill finds those companies, qualifies them, extracts personalization context, and outputs everything to a Google Sheet. Does NOT do outreach — just delivers qualified leads with reasoning.
Sistema de planificación basado en archivos estilo Manus para organizar y rastrear el progreso de tareas complejas. Crea task_plan.md, findings.md y progress.md. Cuando el usuario solicita planificación, desglose u organización de proyectos multipaso, tareas de investigación o trabajos que requieren más de 5 llamadas a herramientas. Soporta recuperación automática de sesión tras /clear. Palabras clave: planificación de tareas, planificación de proyecto, crear plan de trabajo, analizar tareas, organizar proyecto, seguimiento de progreso, planificación multipaso, ayúdame a planificar, desglosar proyecto
AI-first coding guidelines for projects maintained by LLMs. Use when creating new code, refactoring, or reviewing code to optimize for model reasoning, regenerability, and debugging; applies to layout, architecture, functions, naming, logging, platform use, and tests.
Apply exponential smoothing methods for time series forecasting with weighted moving averages. Use this skill when the user needs simple, robust forecasts, implement Holt-Winters for seasonal data, or build lightweight forecasting without complex models — even if they say 'simple forecast', 'moving average prediction', or 'smoothing method'.
Information Question Generator. Given an article, paper, or book, extract its core viewpoints into Q-A pairs — Questions get straight to the point, no textbook-style phrasing; Answers are concise and clear, with formalized conclusions and complete logical chains. As readers follow the Q chain, each Answer drives home a key point, reproducing the author's entire reasoning process. Activate when the user says '问答', 'Q&A', 'QA', '提问', '抽取问题', '/ljg-qa', or shares an article, paper, or book and requests Q-A extraction. This tool triggers when the user wants ideas extracted not as a summary but as a sequence of incisive questions paired with answers. NOT FOR FAQ generation, glossary creation, or comprehension quizzes — this is intellectual scaffolding, not a study aid.
A cross-cutting cognitive mode for sitting with design problems before rushing to solve them. Part of the Intent design strategy system. Activates expansive brainstorming: hyperassociativity, beginner's mind, cross-domain pattern recognition, and suppression of premature idea-dismissal. Works alongside every Intent skill — strategize uses it to reframe briefs, blueprint to question structural assumptions, journey to rethink interaction models, and specify to stress-test specs. Trigger when the user invokes "expansive mode", "philosopher mode", "sit with this", "brainstorm", "explore this problem", or says things like "go weird with it", "don't filter yourself", "what connections are you not making", "think about this differently", or "I'm stuck". This is a reasoning protocol, not a persona — Claude's voice stays grounded but the cognitive process changes significantly.
Find and evaluate research datasets for any scientific question. Teaches how to reason about data needs, search across public repositories, evaluate dataset fitness, and identify access requirements. Use whenever users ask to find data, search for datasets, identify cohort studies, or need data for analysis. Also use when users ask about a specific survey or cohort (NHANES, HRS, UK Biobank, TCGA, etc.), when they want to know what data exists for a research question, or when they need to compare available data sources. If the user mentions "where can I get data" or "is there a dataset for X", this is the right skill.
[QianWen] Generate text, have conversations, write code, reason, and call functions with Qwen models. TRIGGER when: user asks to chat with Qwen, generate text, write code with Qwen, use Qwen function calling, or explicitly invokes this skill by name (e.g. use qianwen-text). DO NOT TRIGGER when: general coding questions without Qwen, non-Qwen AI model usage (OpenAI, Gemini, etc.), image/video understanding (use qianwen-vision), image/video/audio generation.
Build AI applications with OpenAI Agents SDK - text agents, voice agents, multi-agent handoffs, tools with Zod schemas, guardrails, and streaming. Prevents 11 documented errors. Use when: building agents with tools, voice agents with WebRTC, multi-agent workflows, or troubleshooting MaxTurnsExceededError, tool call failures, reasoning defaults, JSON output leaks.
Intelligent Prompt Generator v2.0 - Supports three modes: Portrait/Cross-Domain/Design, with semantic understanding, common sense reasoning, and consistency checking