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Found 1,267 Skills
Searches and retrieves MLflow documentation from the official docs site. Use when the user asks about MLflow features, APIs, integrations (LangGraph, LangChain, OpenAI, etc.), tracing, tracking, or requests to look up MLflow documentation. Triggers on "how do I use MLflow with X", "find MLflow docs for Y", "MLflow API for Z".
Fully local multi-agent swarm intelligence simulation engine using Neo4j + Ollama for public opinion, market sentiment, and social dynamics prediction.
Use when users provide vague, underspecified, or unclear requests where they need help defining WHAT they actually want - across ANY domain (writing, analysis, code, documentation, proposals, reports, presentations, creative work). Trigger aggressively when users express VAGUE GOALS ("make this better", "improve our X", "figure out what to include", "I don't know where to start", "kinda lost on what to do", "not sure what this means"), UNDEFINED SUCCESS ("should look professional", "explain this clearly", "make it convincing", "whatever works best", missing constraints/audience/format), COMMUNICATION UNCLEAR ("how do I explain/communicate this", "my team gets confused when I describe it", "help me figure out what to ask about X"), AMBIGUOUS REQUIREMENTS ("analyze the data" without saying what to look for, "improve documentation" without saying how, "make it more robust" without defining robustness, any request with multiple valid interpretations), or META-PROMPTING ("optimize this prompt", "improve my prompt", "make this clearer", "review my instructions", learning about prompt frameworks like CO-STAR/RISEN/RODES, understanding what makes prompts effective). Trigger for non-technical users and ANY situation where the request needs refinement, structure, or clarification before execution can begin. When in doubt about whether a request is clear enough - trigger.
Agent skill for sona-learning-optimizer - invoke with $agent-sona-learning-optimizer
Use when managing AI Hub account, API keys, balance, usage, or API endpoints. Use when user says "AI Hub", "add AI credits", "create API key", "check AI usage", "auto-recharge", "AI Hub endpoint", "AI Hub base URL", "how to use AI Hub API", "LLM API", "AI API", "OpenAI compatible", "Anthropic API", "GPT", "Claude", "Gemini", "DeepSeek", or "Grok" in the context of Zeabur.
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.
Framework for automated search over task-specific model harnesses — the code around a fixed base model that decides what to store, retrieve, and show while the model works.
Maintain and author Editframe's skills-as-docs system. Covers file structure, frontmatter schemas, rendering conventions (html live demos, callouts, API metadata), the generation pipeline, and build/push workflow. Use when creating or editing skill files, reference documentation, frontmatter, html live blocks, API metadata, or working on the skills web renderer.
Expert guidance for fast fine-tuning with Unsloth - 2-5x faster training, 50-80% less memory, LoRA/QLoRA optimization
List Langfuse sessions. Use when checking user sessions, analyzing conversation flows, or monitoring session activity.
List all Langfuse prompts with their labels and versions. Use when checking available prompts, verifying label assignments, or getting an overview of prompt status.
This skill should be used when the user asks to "integrate DSPy with Haystack", "optimize Haystack prompts using DSPy", "use DSPy to improve Haystack pipeline", mentions "Haystack pipeline optimization", "combining DSPy and Haystack", "extract DSPy prompt for Haystack", or wants to use DSPy's optimization capabilities to automatically improve prompts in existing Haystack pipelines.