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Found 403 Skills
Smart Money analytics on OKX: leaderboard traders, position tracking, trade records, aggregated consensus signals, and signal history. Use this skill when the user asks about 聪明钱, smart money, 牛人榜, leaderboard, top traders, 带单员, lead traders, 交易员排行, trader ranking, trader positions, trader PnL, 交易员持仓, 交易员收益, smart money signal, 聪明钱信号, long/short ratio, 多空比, capital flow, 资金流向, position conviction, 仓位强度, entry price distribution, smart money overview, 聪明钱总览, signal history, 信号历史, trader search, 搜索交易员, who is trading BTC, 谁在交易BTC, recommend traders, 推荐交易员, best traders, top performers.
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".
US ETF capital-flow analysis via Longbridge Securities — tracks institutional money migration via ETF creation/redemption changes, sector breadth signals, and thematic momentum. Analyses major SPDR sector ETFs (XLK / XLF / XLE / XLV etc.) for net inflow / outflow to gauge industry rotation and risk-appetite shifts. Triggers: "ETF资金流", "ETF流向", "美国ETF", "板块ETF", "XLK", "XLF", "XLE", "机构资金迁移", "行业轮动信号", "ETF資金流", "ETF流向", "美國ETF", "板塊ETF", "機構資金遷移", "ETF flow", "US ETF flow", "sector ETF", "SPDR", "institutional flow", "sector rotation signal", "ETF inflow outflow", "fund flow".
Identify EMERGING trends by connecting dots across unrelated sources. Monitor niche communities, academic research, GitHub, patents, funding, regulatory changes. Predict what will trend in 3-6 months based on weak signals.
Technology-agnostic guidance for modular systems: bounded contexts, clear boundaries, composability, state isolation, explicit contracts, failure containment, scaffolding workflows, split/merge criteria, sub-units inside a context, and compliance review signals. Use when designing or reviewing module structure, service boundaries, package layout, cross-cutting dependencies, "how should we split this?", modularity assessments, coupling between domains, greenfield context design, or architecture discussions without assuming a specific framework, language, or repository layout. Do NOT use for executing the full Patterns 1–5 repo decomposition pipeline or per-pattern inventories (use modular-decomposition), phased extraction roadmaps as the main deliverable (use decomposition-planning-roadmap), or end-to-end legacy migration strategy (use legacy-migration-planner).
Vendor-neutral skill to score customer churn risk from account signals and produce prioritized retention actions.
Use Godot 4.x physics bodies and detection in 2D and 3D: RigidBody, StaticBody, Area, and CharacterBody; collision layers vs masks; contact/overlap signals; and raycasts (RayCast nodes and direct space-state queries). Use when configuring collision layers/masks, detecting overlaps with Area2D/Area3D, applying forces to a RigidBody, or casting rays in a Godot project (.tscn with physics bodies).
Build enriched prospect lists from ICP criteria - find targets, enrich contacts, score accounts, detect trigger signals
Input your best customers and find 100+ companies that match the profile. Uses firmographic data, tech stack, growth signals, and similarity scoring to identify ideal prospects. Use when building target account lists or expanding to new markets.
Identify upsell and cross-sell opportunities through usage patterns, growth signals, and account behavior analysis
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.