Total 50,615 skills, AI & Machine Learning has 8484 skills
Showing 12 of 8484 skills
use TensorArt/Tusi/吐司 to generate image or video for you
Полная русскоязычная справка по Ollama Web Search и Web Fetch API: поиск в интернете, получение контента страниц, Python/JS SDK, MCP-сервер, интеграция с OpenClaw. Используй этот скилл при любых вопросах об Ollama web search: как настроить API-ключ, выполнить поиск, получить содержимое страницы, подключить SDK, настроить MCP-сервер, интегрировать с агентами. Также используй при написании кода для Ollama Search: bash-скрипты, Python asyncio, JS/TS клиенты, tool-calling агенты, конфигурация OpenClaw. Триггерится на слова: ollama search, ollama web search, ollama_search, ollama fetch, web_search ollama, ollama api key, ollama MCP, поиск через ollama.
Analyzes current conversation context to recommend the best skills and subagents for the task at hand. Use proactively when unsure which tool, skill, or agent to use.
A hybrid pattern where the system pauses execution to request human approval, input, or disambiguation before proceeding with critical actions. Use when user asks to "add human approval", "require human review", "human-in-the-loop", or mentions approval workflows, human oversight, or escalation.
Plan and write strategic rebuttals after real paper reviews arrive. Use this skill whenever the user has OpenReview reviews, reviewer comments, scores, confidence ratings, meta-reviews, author response windows, or wants to decide which experiments to run, infer reviewer intent, draft point-by-point responses, prepare follow-up discussion replies, or improve wording after reviews for ML/AI venues such as NeurIPS, ICML, ICLR, CVPR, ACL, EMNLP, or similar conferences.
Initialize a full ML research project control root with independent paper, code, and optional slide repositories, shared project memory, root-level agent guidance, code-owned worktree policy, and component handoffs. Use when starting a new research project, setting up a project root for agents, connecting paper/code/slides repos, or replacing a simple paper+code workspace with a lifecycle-aware research project structure.
Enter explore mode - a thinking partner for exploring ideas, investigating problems, and clarifying requirements. Use when the user wants to think through something before or during a change.
AI project intelligence system. Manages .ai/ directory for rules, behaviours, sessions, incidents, memory, snapshots, and learning loops. Use when: starting a session, switching behaviour, logging an incident, saving feedback, reviewing past sessions, checking active hotfixes, managing snapshots, creating snippets/prompts. Proactively suggest when: user corrects AI behavior ("no", "don't", "wrong", "stop", "always", "never"), session ends, a mistake pattern repeats, starting work on unfamiliar code, user says "remember this" or "learn this".
[Hyper] Create and refactor AI-readable docs, instruction bases, runbooks, specs, and harness-ready rule packs for context, prompt, tool, eval, sourcing, safety, and validation workflows.
[Hyper] Optimize an existing Codex skill through baseline-first experiments, binary evals, optional guards, and one-mutation-at-a-time iteration. Use for skill autoresearch, measured trigger/workflow improvement, self-optimizing a skill, benchmarking skill changes, or resuming skill experiment artifacts.
[Hyper] Produce a multi-source, source-backed markdown research report for fact-finding, comparisons, market/trend analysis, or evidence-backed recommendations across live web, official docs, GitHub, and local repo sources. Use when synthesis and citations are needed, not for one-source lookups.
Execute Claude Code commands in the telegram_agent project directory. Use when the user wants to work on the telegram agent itself, fix bugs, add features, or modify the bot code. This is a COMMAND HANDLER, not a script executor.