Loading...
Loading...
Found 2,506 Skills
Use when a manuscript is close to submission or resubmission and you need a preflight audit for claim support, figure-panel coverage, legend sync, methods references, terminology stability, and venue-facing risks.
ByteRover CLI (brv) - Persistent memory layer for AI coding agents with context trees, knowledge storage, and cloud sync
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.
Refresh golden values from a GitHub Actions workflow run (failing-only or all jobs), score the change with average normalized relative differences, and produce a PR-ready summary. Use when the user asks to update goldens for a CI run, refresh golden values from a workflow ID, or generate a golden-value diff summary for a PR description.
Guardian is an AI-powered penetration testing automation CLI that leverages multiple AI providers (OpenAI, Claude, Gemini) and 19+ security tools to orchestrate intelligent, step-by-step penetration testing workflows with comprehensive evidence capture.
Scan the portfolio for the highest-leverage AI opportunities and rank where to deploy operating-partner time. Ingests quarterly updates and financials across multiple portfolio companies, identifies quick wins at each, and stacks them into a single ranked action list. Use during quarterly portfolio reviews, annual planning, or when deciding which companies get AI investment first. Triggers on "AI readiness", "AI opportunity scan", "where should we deploy AI", "AI across the portfolio", "AI quick wins", or "which portcos are ready for AI".
Guardrails for adding unit tests in bklit-ui without over-testing. Use when the user mentions unit test, unit tests, tests, test coverage, add tests, write tests, vitest, jest, or asks whether something should be tested.
Automate the browser inside cmux. Use for cmux browser, browser surface, webview, current workspace browser, snapshot refs, DOM actions, waits, screenshots, cookies, storage, tabs, downloads, console, errors, and browser session state.
Complete React 19 fundamentals system. PROACTIVELY activate for: (1) React 19 new features and changes, (2) Server vs Client Components, (3) Server Actions setup, (4) use() hook usage, (5) JSX and component basics, (6) Props and state patterns, (7) Suspense and Error Boundaries, (8) Fragments and Portals. Provides: React 19 syntax, Server Component patterns, async data handling, component composition, best practices. Ensures modern React 19 patterns with proper server/client architecture.
Fetch raw OHLCV price data using the aipa CLI. Use this skill whenever the user asks for price data, candle data, OHLCV data, historical prices, stock quotes, crypto prices, moving averages, volume data, or any raw market data without AI analysis. Also use for: top performers, worst performers, best stocks, top gainers, biggest losers, market movers, ranking tickers by price change / volume / value / MA scores / money flow (`aipa performers`); volume profile, POC, point of control, value area, support/resistance by volume, volume-by-price histogram (`aipa volume-profile`). Also use for fundamental data: company info, financial ratios, PE, PB, ROE, NPL, CAR, fundamental ranking and screening (`aipa fundamentals info/ratios/rank/screen`). Also use when the user wants to inspect what data is available, build charts, perform their own calculations, or get numbers for a spreadsheet. Even if the user doesn't mention "aipa", trigger this skill for any raw financial data, fundamental data, or market ranking request.
Provides comprehensive code review covering 6 focused aspects - architecture & design, code quality, security & dependencies, performance & scalability, testing coverage, and documentation & API design. Use this skill for deep analysis with actionable feedback after significant code changes.
Router skill for LLMQuant crypto workflows. Use when the user needs crypto market regime analysis, token research, perpetual funding, basis, leverage, liquidity, or cross-asset crypto context.