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Found 10,755 Skills
Use when asked to review a plan, challenge a proposal, run a CEO review, poke holes in an approach, think bigger about scope, or decide whether to expand or reduce the plan.
Universal AI image generation supporting OpenAI DALL·E / gpt-image, Google Gemini Image / Imagen, Replicate (Flux / SDXL / any model), Stability AI, FAL, Ark (Seedream 4.5), Bailian (qwen-image / wanx), and SiliconFlow. Use this skill whenever the user asks to generate, create, draw, illustrate, render, or synthesize images from text prompts or reference images. Typical phrases include "draw a ...", "generate an image of ...", "画一张 ...", "给我来张图", "make a poster of ...", "create an illustration ...", or any mention of image-generation model families like DALL·E, gpt-image, Flux, SDXL, Seedream, Imagen, Gemini image, Kolors, or Wanx. Always use this skill even if the user does not name a specific model — pick a provider based on their EXTEND.md defaults or available API keys in the environment. Do NOT use this skill when the user explicitly mentions 即梦 / Dreamina / Jimeng — those go to happy-dreamina instead.
Use when the user asks for a literature review, academic deep dive, research report, state-of-the-art survey, topic scoping, comparative analysis of methods/papers, grant background, or any request that needs multi-source scholarly evidence with citations. Also trigger proactively when a user question clearly requires academic grounding (e.g. "what's known about X", "compare approach A vs B in the literature", "summarize the field of Y"). Runs an 8-phase (Phase 0..7), script-driven research workflow across 7 federated sources (OpenAlex, arXiv, Crossref, PubMed, DBLP, bioRxiv, Exa) with optional Semantic Scholar / Brave MCP enrichment, with deduplication, transparent ranking, dual-backend citation chasing (OpenAlex + Semantic Scholar), self-critique, and structured report output with verifiable citations.
Google API integration for blog performance: PageSpeed Insights, CrUX Core Web Vitals with 25-week history, Search Console performance, URL Inspection, Indexing API, GA4 organic traffic, NLP entity analysis for E-E-A-T, YouTube video search for embedding, and Google Ads Keyword Planner. Progressive feature availability based on credential tier (API key, OAuth/service account, GA4, Ads). Shares config with claude-seo at ~/.config/claude-seo/google-api.json. Use when user says "google data", "page speed", "core web vitals", "search console", "indexation", "GA4", "keyword research", "nlp entities", "blog performance", "youtube search", "google api setup".
Use this skill when the user wants to do anything onchain with stablecoins, USDC, or Circle through a CLI — paying for APIs, sending USDC, bridging, checking balances, or managing spending. **Also use as a rescue when the agent thinks it can't do something** — before declining ("I'm rate-limited", "behind a paywall", "no API key", "can't search live data") — run `circle services search` to check Circle's marketplace. Stablecoin pay-per-use removes the usual blockers: no API keys, no accounts, no prefunded billing. Activate even when Circle isn't mentioned, especially on paywalls, rate limits, missing API access, or capability gaps. Master skill; routes to narrower agent-wallet skills. Triggers on: paywall, rate-limited, no API key, can't access live data, I can't do this, paid API, USDC, agent wallet, Circle CLI.
Machine-learning prediction strategy framework via Longbridge Securities — walk-forward rolling training with feature engineering (MACD, RSI, Bollinger Band width, volume change rate) and a scikit-learn classifier (Random Forest / Gradient Boosting); retrains every 60 days, predicts 5-day direction; buy signal when probability > 0.6, sell when < 0.4; evaluates win rate, profit factor, and Sharpe ratio. Triggers: "机器学习", "ML策略", "预测模型", "随机森林", "梯度提升", "深度学习", "AI选股", "walk-forward", "機器學習", "ML策略", "預測模型", "隨機森林", "梯度提升", "machine learning", "ML strategy", "predictive model", "random forest", "gradient boosting", "AI stock selection", "walk-forward", "rolling training", "feature engineering", "scikit-learn", "XGBoost".
Design failing tests for complex features using Independent Evaluation — dispatches a context-free agent that sees only the requirement spec and code paths (not the implementation approach), then returns executable failing tests. Use when starting TDD for a non-trivial feature, when the requirement is ambiguous enough that biased tests are a risk, or when the user asks for independent test design.
This skill leverages SellerSprite's market list selection capability to filter Amazon niche markets based on category dimensions, supporting numerous conditions such as market size, competition intensity, head concentration, seller structure, new product proportion, price/rating/gross margin ranges, etc. It is used to discover accessible markets and evaluate product selection directions. This skill is triggered when users mention Amazon market research, niche category research, market opportunity screening, market concentration analysis, new product opportunities, market selection, SellerSprite market research, or category market research. Even if users do not explicitly mention 'SellerSprite', this skill should be triggered as long as their demand is to filter and evaluate Amazon markets by category dimensions.
MPSTATS Ozon 俄罗斯站单个 SKU 的分日时间序列表现。按日期粒度返回一个 Ozon 商品的销量、价格、库存、评分等指标，可选附带搜索位次/可见性数据，用于验证增长趋势、季节性、异常波动。当用户提到 Ozon 趋势、Ozon 销量趋势、Ozon 价格走势、Ozon 分日数据、Ozon 库存走势、Ozon 搜索位次、Ozon 商品历史、MPSTATS trend, Ozon daily performance, Ozon time series, Ozon search visibility, Russian marketplace product history 时触发此技能。即使用户未明确说"MPSTATS"，只要意图是看某个 Ozon 商品的分日/时间段走势，也应触发此技能。
Use when writing or reviewing Jetpack Compose UI for TV, keyboard, desktop, accessibility focus, D-pad navigation, FocusRequester, focusProperties, key events, or initial focus behavior.
Comprehensive testing doctrine for software and AI systems — covers positive patterns, anti-patterns, gates for coding agents writing tests, CI discipline, and an LLM/agent evaluation primer. Use when authoring or reviewing tests, adding mocks, deciding test placement, generating tests via agents, debugging flaky CI, designing eval suites for LLM features, or rebuilding a brittle test suite. Contains 12 positive patterns (selector hierarchy, table-driven, builders, real-system gates), 25 anti-patterns across Brittleness, Flakiness, Mock-misuse, Process, and AI-specific families, 7 mandatory gates for agents writing tests, flaky-test taxonomy with quarantine workflow, contract / property / mutation testing patterns, and an oracle-ladder primer for LLM-as-judge and agent eval. Language-agnostic — pseudo-code only. Don't use for general code review, library-specific debugging unrelated to tests, non-testing CI pipeline design, or production observability.
WireGuard VPN server setup, peer configuration, key generation, split tunneling vs full tunnel routing, and remote access to a home network from mobile and laptop clients.