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Found 5,605 Skills
Agent skill that helps AI coding assistants write smarter, modern SwiftUI code with best practices for API usage, design, performance, and accessibility
Terminal-first Twitter/X CLI for reading feeds, bookmarks, search, and posting tweets without API keys
OpenClaw 中文官方技能库 — 翻译自 Clawdbot 官方技能，按场景分类整理，支持中文自然语言调用
Portable .agent/ folder with memory, skills, and protocols that works across Claude Code, Cursor, Windsurf, and other AI coding harnesses
Code review closeout for Claude Code, Codex, OpenCode, and DeepSeek TUI: local dirty changes, branch vs main, parallel tests.
Move testing activities earlier in the development lifecycle to catch defects when they're cheapest to fix. Use when implementing TDD, CI/CD, or early quality practices.
Use when retrieving the most relevant skills from a local or private skill library instead of relying on network-based skill discovery.
Extracts exact, behaviour-first specifications from an existing codebase. Defines domain concepts, use cases, and business rules with precision — zero implementation details. Use when reverse-engineering a legacy project into precise specs or preparing an AI-friendly spec set for a rewrite.
Interprets authoritative specs and helps design a new implementation collaboratively, preserving required business, API, and database contracts while exploring architecture, stack, and delivery options with the user. Use when the user wants to start a new project from frozen specs, discuss implementation approaches, or plan an incremental rebuild without depending on the legacy codebase.
Import datasets from HuggingFace and convert them to Coval test sets. Use when the user wants to create test cases from HuggingFace dataset or repository.
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.
After solving a non-trivial problem, detect generalizable learnings and propose skill updates so future interactions benefit automatically. Always active — applies to every interaction.