Total 50,473 skills, AI & Machine Learning has 8470 skills
Showing 12 of 8470 skills
Help users create high-quality skills by discovering and incorporating proven methodologies from domain experts. Use this skill BEFORE skill-creator when users want to create a new skill - it enhances skill-creator by first identifying expert frameworks and best practices to incorporate. Triggers on requests like "help me create a skill for X" or "I want to make a skill that does Y". This skill guides methodology selection, then hands off to skill-creator for the actual skill generation.
This skill should be used whenever users request personal assistance tasks such as schedule management, task tracking, reminder setting, habit monitoring, productivity advice, time management, or any query requiring personalized responses based on user preferences and context. On first use, collects comprehensive user information including schedule, working habits, preferences, goals, and routines. Maintains an intelligent database that automatically organizes and prioritizes information, keeping relevant data and discarding outdated context.
Design LLM applications using LangChain 1.x and LangGraph for agents, memory, and tool integration. Use when building LangChain applications, implementing AI agents, or creating complex LLM workflows.
Use when building ML pipelines, orchestrating training workflows, automating model lifecycle, implementing feature stores, or managing experiment tracking systems.
Build new agent skills. Use when creating diagnostic frameworks, CLI tools, or data-driven generators that follow the established skill patterns.
Build agents for legal document analysis, contract review, and compliance checking. Handles document parsing, risk identification, and legal research. Use when creating contract analysis tools, legal research assistants, compliance checkers, or document review systems.
Suggest relevant GitHub Copilot instruction files from the awesome-copilot repository based on current repository context and chat history, avoiding duplicates with existing instructions in this repository, and identifying outdated instructions that need updates.
Build an AI agent backend with persistent memory: one Rivet Actor per conversation, queued message handling, and streaming LLM responses as realtime events.
INVOKE THIS SKILL for LLM-as-judge evaluation workflows on Arize: creating/updating evaluators, running evaluations on spans or experiments, tasks, trigger-run, column mapping, and continuous monitoring. Use when the user says: create an evaluator, LLM judge, hallucination/faithfulness/correctness/relevance, run eval, score my spans or experiment, ax tasks, trigger-run, trigger eval, column mapping, continuous monitoring, query filter for evals, evaluator version, or improve an evaluator prompt.
Entrypoint for all Fusion skill lifecycle operations. USE FOR: finding, installing, updating, syncing, or greenkeeping skills; setting up skill automation; creating or authoring a new skill; reporting a bug with a skill. DO NOT USE FOR: resolving GitHub issues, reviewing PRs, planning task breakdowns, or authoring GitHub issues — those are handled by other Fusion skills.
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Targeted Chatroom: Recommend experts based on topics or accept user-specified experts to simulate multi-role conversations. Trigger methods: /dbs-chatroom, /targeted-chatroom, "Targeted Chatroom"