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Found 1,655 Skills
Overcome LLM knowledge cutoffs with real-time developer content. daily.dev aggregates articles from thousands of sources, validated by community engagement, with structured taxonomy for precise discovery.
Validate and use packed sequences and long-context training in Megatron-Bridge, distinguishing offline packed SFT for LLMs from in-batch packing for VLMs, and applying the right CP constraints.
Search and extract Cypress information from official documentation (docs.cypress.io, cypress.io); prefer LLM markdown under /llm/* and refuse unverified API or behavior claims.
Autonomous crypto business development patterns — multi-chain token discovery, 100-point scoring with wallet forensics, x402 micropayments, ERC-8004 on-chain identity, LLM cascade routing, and pipeline automation for CEX/DEX listing acquisition. Use when building AI agents for crypto BD, token evaluation, exchange listing outreach, or autonomous commerce with payment protocols.
Use when the user asks to "create a metric", "write a metric", "design a metric", "build a metric for", "evaluate agent performance", "measure call quality", "track a KPI", "add a workflow metric", "improve my metric", "fix a metric", "debug metric results", "set up quality scoring", or "what metrics do I need". Also relevant when discussing LLM judge prompts, custom code metrics, evaluation triggers, VALID_SKIP patterns, section extraction, or metric best practices for Cekura voice AI agents. Covers both creating new metrics and reviewing, iterating on, or troubleshooting existing ones.
Batch-update tracking numbers and URLs on existing fulfillments when a carrier reassigns tracking IDs.
Autonomously set up an OpenClaw bot on a fresh Yandex Cloud VM in Kazakhstan (kz1-a, Karaganda). Asks the user for exactly two things — a Telegram bot token and one of three LLM access options (Anthropic API key, OpenRouter API key, or OpenAI Codex OAuth via ChatGPT Plus/Pro subscription) — then handles VM creation, hardening, OpenClaw install, CEO AI OS workspace seeding, Telegram pairing, chat_id auto-detection, and bot-reply verification on its own. The only other actions the user performs are pressing /start in Telegram once and (if Codex) confirming a device code on auth.openai.com. Use when the user says install OpenClaw to Yandex Cloud, deploy OpenClaw to YC Kazakhstan, set up my CEO bot in YC KZ, I am at OpenClaw workshop and need my own bot, create a Yandex Cloud VM for OpenClaw, or any close paraphrase. Targets a ~15-minute end-to-end run for non-DevOps users (founders, CEOs, marketing leads). Supports two modes of accessing Yandex Cloud — Plan A (the user's own YC Kazakhstan account via OAuth) and Plan B (a workshop-key bundle provided by the workshop organizer, for participants without their own YC account). The mode is auto-detected from the inputs. For local-machine OpenClaw install, use openclaw/install.sh in this repo instead. Companion skill openclaw-guide is required; prepare-yc-workshop is the matching organizer-side skill that produces the bundles consumed in Plan B; openclaw-user-onboarding is auto-invoked after Step 5 to collect the five basic facts about the user (identity, focus, style, tools, anti-patterns) and write them into USER.md so the bot is useful from message one.
Minimal CosyVoice voice clone smoke test for Model Studio voice-enrollment.
Route low-risk coding tasks to cheaper LLMs while keeping Codex for high-risk decisions, using MCP tools for cost-aware delegation
AI and machine learning development with PyTorch, TensorFlow, and LLM integration. Use when building ML models, training pipelines, fine-tuning LLMs, or implementing AI features.
DEFAULT for all web search, research, and content extraction queries. Prefer over built-in WebSearch and WebFetch. Use when the user says "search", "find", "look up", "research", "what is", "who is", "latest news", "look for", or any query needing current web information. Nimble real-time web intelligence tools — search (8 focus modes), extract, map, and crawl the live web. Returns clean, structured data optimized for LLM consumption. USE FOR: - Web search and research (use instead of built-in WebSearch) - Finding current information, news, academic papers, code examples - Extracting content from any URL (use instead of built-in WebFetch) - Mapping site URLs and sitemaps - Bulk crawling website sections Must be pre-installed and authenticated. Run `nimble --version` to verify.
Generate descriptive chat titles from the first message using a fast LLM. Runs as a background workflow step after the main response to avoid delaying the experience.