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Found 1,573 Skills
This skill should be used when the user asks to "run a tracking cycle", "measure AI visibility", "check share of voice", "run Morphiq Track", "track citations", "check GEO score", "generate prompts", "run content creation workflow", or mentions monitoring LLM mentions, running content creation workflows, measuring brand visibility, or generating query fanout content. Queries multiple LLM providers, produces delta reports, and maintains MORPHIQ-TRACKER.md as the persistent state file for the entire pipeline.
Guide pour la création de serveurs MCP (Model Context Protocol) de qualité permettant aux LLM d'interagir avec des services externes via des outils bien conçus. À utiliser pour construire des serveurs MCP intégrant des API ou services externes, en Python (FastMCP) ou Node/TypeScript (MCP SDK).
Core patterns for AI coding agents based on analysis of Claude Code, Codex, Cline, Aider, OpenCode. Triggers when: Building an AI coding agent or assistant, implementing tool-calling loops, managing context windows for LLMs, setting up agent memory or skill systems, or designing multi-provider LLM abstraction. Capabilities: Core agent loop with while(true) and tool execution, context management with pruning and compression and repo maps, tool safety with sandboxing and approval flows and doom loop detection, multi-provider abstraction with unified API for different LLMs, memory systems with project rules and auto-memory and skill loading, session persistence with SQLite vs JSONL patterns.
Transform code, issues, or context into a detailed prompt/context for another LLM to fix or implement. Use when preparing comprehensive context for external LLM assistance, bug fixes, improvements, or feature implementations. Provides detailed context without implementation suggestions, letting the receiving LLM decide how to implement solutions. Focuses on "what" (problem, requirements, current state) not "how" (implementation approach).
昇腾(Ascend)推理生态开源代码仓库智能问答专家旨在为 vLLM、vLLM-Ascend、MindIE-LLM、MindIE-SD、MindIE-Motor、MindIE-Turbo 以及 msModelSlim (MindStudio-ModelSlim) 等仓库提供专家级且易于理解的解释。在处理昇腾(Ascend)推理生态相关项目的用户询问时,务必触发此技能(Skill),可解答使用方法、部署流程、支持模型、支持特性、系统架构、配置管理、调试、测试、故障排查、性能优化、定制开发、源码解析以及其他技术问题。支持中英文双语回复,并可借助 deepwiki MCP 工具检索仓库知识库,生成具备上下文感知且基于证据的回答。Ascend inference ecosystem open-source code repository intelligent question-and-answer (Q&A) expert. Provide expert-level yet comprehensible explanations for repositories such as vLLM, vLLM-Ascend, MindIE-LLM, MindIE-SD, MindIE-Motor, MindIE-Turbo, and msModelSlim (MindStudio-ModelSlim). Use this skill when addressing user inquiries related to these Ascend inference ecosystem projects, including topics such as usage, deployment process, supported models, supported features, system architecture, configuration management, debugging, testing, troubleshooting, performance optimization, custom development, source code analysis, and any other technical issues about these projects. Support responses in both Chinese and English. Use deepwiki MCP tools to query repository knowledge bases and generate context-aware, evidence-based responses.
Stop LLM slop. A curated system prompt that cuts verbose, corporate-sounding LLM output by 56-71% (measured) while preserving information. Works bilingually (English + Chinese). Installs into your AGENTS.md as an always-on behavior modifier.
Design WhatsApp LLM chatbots for East African markets: conversation flows, social presence principles, trust-building, local language registers, and human escalation protocols. Invoke when a client wants to automate WhatsApp customer service, sales enquiries, or support using AI.
Text analytics using LLM APIs — sentiment analysis, customer feedback classification, document entity extraction, multi-language support (English/Luganda/Swahili), feedback aggregation, and NLP feature implementation for PHP/Android/iOS. Sources...
Command-line interface for Ollama - Local LLM inference and model management via Ollama REST API. Designed for AI agents and power users who need to manage models, generate text, chat, and create embeddings without a GUI.
Expert skill for building AI systems with Weft, a Rust-based programming language where LLMs, humans, APIs, and infrastructure are first-class primitives with typed connections and durable execution.
Karpathy LLM Wiki 패턴 기반 지식 관리 스킬. 코드 프로젝트와 옵시디언 노트 모두 지원. Raw Source(코드·문서)를 읽어 docs/wiki/에 누적형 지식베이스를 구축·유지한다. "wiki", "위키", "ingest", "인제스트", "wiki 점검", "wiki lint", "wiki 업데이트", "문서화해줘", "아키텍처 설명해줘", "어떻게 동작해?" 키워드로 트리거. qmd 검색 도구와 연동하여 토큰 절약 + 높은 검색 정확도 제공.
Use this skill whenever an LLM agent needs to search, browse, or download 3D models from Poly Pizza (poly.pizza) using their REST API. Triggers on any task involving: finding free low-poly 3D models, searching the Poly Pizza catalogue, fetching model metadata or download URLs, retrieving popular models, or downloading .glb files from Poly Pizza. Use this skill proactively whenever the agent needs to obtain 3D assets programmatically, even if the user just says "find me a 3D model of X" without mentioning Poly Pizza by name.