Loading...
Loading...
Found 383 Skills
Router skill for LLMQuant market-intelligence workflows. Use when the user needs macro views, market sentiment dashboards, or event probability signals.
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."
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
Tagging schema for classifying community signals by persona, journey, and business impact.
Screen post-earnings gap-up stocks for PEAD (Post-Earnings Announcement Drift) patterns. Analyzes weekly candle formation to detect red candle pullbacks and breakout signals. Supports two input modes - FMP earnings calendar (Mode A) or earnings-trade-analyzer JSON output (Mode B). Use when user asks about PEAD screening, post-earnings drift, earnings gap follow-through, red candle breakout patterns, or weekly earnings momentum setups.
Crypto news search, AI ratings, trading signals, and real-time updates via the OpenNews 6551 API. Supports keyword search, coin filtering, source filtering, AI score ranking, and WebSocket live feeds.
Systematically discover and define your Ideal Customer Profile with firmographic criteria, buyer personas, scoring matrices, anti-ICP signals, and validation methodology.
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.
Aggregate and rank signals from multiple edge-finding skills (edge-candidate-agent, theme-detector, sector-analyst, institutional-flow-tracker) into a prioritized conviction dashboard with weighted scoring, deduplication, and contradiction detection.
Analyze articles for AI-generated content indicators and rewrite to pass WeChat's 3.27 non-human automated content creation detection. Checks for template phrases, transition word density, sentence uniformity, paragraph pattern repetition, and other signals that WeChat uses to flag AI content. Outputs a risk report and an optional humanized rewrite. Use when the user wants to check if an article looks AI-generated, make an article more human-like, bypass WeChat AI detection, or humanize AI-written content. Also trigger when the user mentions "去AI痕迹", "人性化润色", "微信AI检测", "anti-ai-check", "humanize article", "公众号发文检查".
Migrates Temporal, Inngest, Trigger.dev, and AWS Step Functions workflows to the Workflow SDK. Use when porting Activities, Workers, Signals, step.run(), step.waitForEvent(), Trigger.dev tasks / wait.forToken / triggerAndWait, ASL JSON state machines, Task/Choice/Wait/Parallel states, task tokens, or child workflows.
People.ai (now Backstory) platform help — automatic activity capture, deal intelligence, pipeline health, revenue forecasting, MCP integration, Salesforce/Dynamics/Oracle CRM sync. Use when reps aren't logging activities and CRM data is stale, deals are slipping without warning and you need early risk signals, forecast accuracy is poor because it's based on gut not data, evaluating People.ai vs Gong vs Clari vs Revenue.io for revenue intelligence, activity data isn't tying back to pipeline or revenue outcomes, or you want to connect People.ai to AI agents via MCP. Do NOT use for conversation intelligence with call recording and transcription (use /sales-gong or /sales-note-taker), building outbound sequences (use /sales-cadence), or general CRM data cleanup strategy (use /sales-data-hygiene).