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Found 412 Skills
SEC EDGAR filing analysis via Longbridge — 10-K annual report, 10-Q quarterly, 8-K material events, proxy statement, insider Form 4. Extracts risk factors, MD&A, non-recurring items, and investment signals. Triggers: "SEC文件", "SEC申报", "10-K", "10-Q", "8-K", "委托投票书", "Form 4", "MD&A", "风险因素", "内部人申报", "SEC文件", "SEC申報", "委託投票書", "風險因素", "內部人申報", "SEC filing", "10-K annual report", "10-Q quarterly", "8-K material event", "proxy statement", "Form 4 insider", "MD&A", "risk factors", "SEC EDGAR".
Angular 19 patterns: signals, standalone components, resource API, signal queries, dependency injection, and Aurora framework integration. Trigger: When implementing Angular components, directives, pipes, services, or using modern reactive patterns.
Write Rails code in 37signals/classic style: rich models, CRUD controllers, concerns, state-as-records, Minitest. Use when writing or modifying Ruby on Rails application code.
Analyst consensus snapshot for listed companies via Longbridge — current revenue / EPS / target-price consensus estimates and analyst rating distribution. For revision direction, beat/miss tracking, and PEAD signals use longbridge-earnings-revision. Triggers: "一致预期", "分析师预期", "EPS预测", "目标价", "分析师评级分布", "买入评级", "卖出评级", "一致預期", "分析師預期", "EPS預測", "目標價", "分析師評級分佈", "買入評級", "賣出評級", "analyst consensus", "EPS forecast", "target price", "analyst rating distribution", "buy sell hold", "price target consensus", "TSLA.US consensus", "700.HK analyst estimates".
Real-time crypto news aggregation with AI ratings and trading signals from 84+ sources across news, listings, on-chain, meme, market, and prediction engines
Angular core patterns: standalone components, signals, inject, control flow, zoneless. Trigger: When creating Angular components, using signals, or setting up zoneless.
Master modern Angular state management with Signals, NgRx, and RxJS. Use when setting up global state, managing component stores, choosing between state solutions, or migrating from legacy patterns.
CI-only self-improvement workflow using gh-aw (GitHub Agentic Workflows). Captures recurring failure patterns and quality signals from pull request checks, emits structured learning candidates, and proposes durable prevention rules without interactive prompts. Use when: you want automated learning capture in CI/headless pipelines.
Wyckoff Method Trading Skill. Analyze stock trends based on the Wyckoff Method, identify accumulation/distribution phases, and determine entry and exit points (signals like Spring, JAC, UT, etc.). This skill is triggered when users mention stock trading, Wyckoff, stock analysis, buy signals, sell signals, etc.
Use this skill when users want live on-chain market data: token prices, price charts (K-line, OHLC), trade history, swap activity. Also, it covers on-chain signals — smart money, whale, and KOL wallet activity, large trades, and signal-supported chains. For meme tokens: scanning new launches, checking dev wallets, developer reputation, rug pull detection, rug pull history, tokens by same creator, detecting bundles or snipers, bonding curves %, flagging suspicious launches, and meme token safety checks. For token search, market cap, liquidity, trending tokens, or holder distribution, use opentrade-token instead.
This skill should be used when writing Dioxus code, building Rust web/desktop/mobile apps with Dioxus, using RSX macro, signals, server functions, or any Dioxus features from 0.5+ (2024-2026).
Expert blueprint for signal-driven architecture using "Signal Up, Call Down" pattern for loose coupling. Covers typed signals, signal chains, one-shot connections, and AutoLoad event buses. Use when implementing event systems OR decoupling nodes. Keywords signal, emit, connect, CONNECT_ONE_SHOT, CONNECT_REFERENCE_COUNTED, event bus, AutoLoad, decoupling.