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Found 438 Skills
Analyzes content for E-E-A-T signals and suggests improvements to build authority and trust. Identifies missing credibility elements. Use PROACTIVELY for YMYL topics.
Use C#/.NET in Godot 4.x: partial classes extending nodes, the PascalCase lifecycle (_Ready/_Process/_PhysicsProcess), [Export] fields, [Signal] delegates as C# events, GetNode<T>, and calling between C# and GDScript. Use when writing Godot game code in C# (.cs files, .csproj), needing the Godot .NET build, converting GDScript patterns to C#, or wiring Godot signals as C# events.
Reference for X algorithm engagement types and signals. Use when analyzing engagement metrics, action predictions, or understanding what signals the algorithm tracks.
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.
Behavioral finance application framework — identify cognitive biases in markets (overreaction, underreaction, disposition effect, anchoring, herding), translate them into quantifiable trading signals (momentum / reversal), and assess whether current market sentiment shows systematic bias. Triggers: "行为金融", "认知偏差", "过度反应", "反应不足", "处置效应", "锚定效应", "羊群效应", "市场情绪偏差", "行為金融", "認知偏差", "過度反應", "反應不足", "處置效應", "錨定效應", "羊群效應", "behavioral finance", "cognitive bias", "overreaction", "underreaction", "disposition effect", "anchoring bias", "herding", "sentiment bias", "behavioral economics".
Quantitative signal scanning and position sizing tool based on the original Turtle Trading method. It retrieves market data for A-shares / Hong Kong stocks / US stocks / Singapore stocks via longbridge CLI, and automatically calculates ATR (N value), breakout signals (System 1 / System 2), stop-loss prices, add-on positions, and Unit position sizes. Trigger this tool when users mention 海龟, turtle, 海龟交易, 海龟信号, turtle signal, turtle trading, or ask about breakout signals, ATR, N value, Unit positions, stop-loss prices, add-on positions, S1/S2 signals, 20-day high/low, 55-day breakout, or request to scan watchlists/indexes for trading signals using the turtle system. It also triggers when users say "扫描突破信号", "帮我算Unit", "海龟止损", "海龟系统分析", or any combination of a stock name/code with "海龟". **Applicable scenarios:** - Scan for breakout signals (20-day/55-day high/low breakouts) after daily market close - Calculate ATR, stop-loss prices, and add-on positions for single stocks or batches of targets - Calculate reasonable Unit position sizes based on account net assets - Determine whether existing positions trigger exit or add-on conditions - Scan turtle signals for watchlist stocks / index components **Not applicable for:** - Fundamental analysis (Turtle system is purely technical) - Predicting price direction - Automatic order placement (only outputs signals; users operate on their own) - Short-selling opening operations for A-shares/Hong Kong stocks/Singapore stocks
Enterprise Angular development expert specializing in Angular 16+ features, Signals, Standalone Components, and RxJS/NgRx at scale.
Generate trading signals using npx neural-trader anomaly detection engine with Z-score scoring and neural prediction
When the user wants to improve their ability to recognize buying signals, ask for the sale, and confidently move deals to commitment. Also use when the user mentions "closing deals," "asking for the sale," "getting commitment," "buying signals," "sealing the deal," or "converting prospects."
Build and execute brand marketing strategy for B2B companies — thought leadership, ABM brand layer, trust signals, LinkedIn presence, long sales cycle brand touchpoints, and enterprise credibility. Use when the user says "B2B marketing", "B2B brand", "business to business marketing", "selling to companies", "enterprise marketing", "we sell to businesses", "B2B brand strategy", "thought leadership strategy", "B2B content marketing", "account-based marketing brand", "B2B positioning", "how do we build trust with buyers", or is marketing a product or service sold to other businesses rather than consumers.
Refactor Angular code to improve maintainability, readability, and adherence to best practices. Transforms large components, nested subscriptions, and outdated patterns into clean, modern Angular code. Applies signals, standalone components, OnPush change detection, proper RxJS patterns, and Angular Style Guide conventions. Identifies and fixes memory leaks, function calls in templates, fat components, and missing lazy loading.