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Found 312 Skills
Use to catalog churn/expansion plays tied to specific signals, cohorts, and owners.
Optimize content for AI Overviews (formerly SGE), ChatGPT web search, Perplexity, and other AI-powered search experiences. Generative Engine Optimization (GEO) analysis including brand mention signals, AI crawler accessibility, llms.txt compliance, passage-level citability scoring, and platform-specific optimization. Use when user says "AI Overviews", "SGE", "GEO", "AI search", "LLM optimization", "Perplexity", "AI citations", "ChatGPT search", or "AI visibility".
Detect and analyze adverse drug event signals using FDA FAERS data, drug labels, disproportionality analysis (PRR, ROR, IC), and biomedical evidence. Generates quantitative safety signal scores (0-100) with evidence grading. Use for post-market surveillance, pharmacovigilance, drug safety assessment, adverse event investigation, and regulatory decision support.
Discover genes associated with diseases and traits using GWAS data from the GWAS Catalog (500,000+ associations) and Open Targets Genetics (L2G predictions). Identifies genetic risk factors, prioritizes causal genes via locus-to-gene scoring, and assesses druggability. Use when asked to find genes associated with a disease or trait, discover genetic risk factors, translate GWAS signals to gene targets, or answer questions like "What genes are associated with type 2 diabetes?"
Identify and prioritize causal variants at GWAS loci using statistical fine-mapping and locus-to-gene predictions. Computes posterior probabilities for causal variants, links variants to genes via L2G predictions, annotates functional consequences, and suggests validation strategies. Use when asked to fine-map GWAS loci, prioritize causal variants, identify credible sets, or link GWAS signals to causal genes.
Transform GWAS signals into actionable drug targets and repurposing opportunities. Performs locus-to-gene mapping, target druggability assessment, existing drug identification, safety profile evaluation, and clinical trial matching. Use when discovering drug targets from GWAS data, finding drug repurposing opportunities from genetic associations, or translating GWAS findings into therapeutic leads.
Expert signal-based selling strategist for B2B outbound teams. Use when the user asks about buying signals, intent data, signal scoring, signal-based selling, website visitor tracking, job change signals, hiring signals, funding signals, competitor signals, tech stack changes, content engagement signals, multi-signal stacking, RB2B setup, Trigify setup, Common Room, Bombora, Koala, Warmly, 6sense, signal-to-action playbooks, or building signal-driven outbound campaigns. Also triggers on "buying signals", "intent data", "signal scoring", "signal-based", "website visitors", "job change", "hiring signal", "funding signal", "competitor signal", "tech change", "content engagement", "RB2B", "Trigify", "Common Room", "Bombora", "intent signals", "warm outbound", "signal stacking", "visitor tracking", "signal tools", "GTM plays". Do NOT use for general list building without signal context (use list-building skill) or email writing (use cold-email skill).
Expert GDScript best practices including static typing (var x: int, func returns void), signal architecture (signal up call down), unique node access (%NodeName, @onready), script structure (extends, class_name, signals, exports, methods), and performance patterns (dict.get with defaults, avoid get_node in loops). Use for code review, refactoring, or establishing project standards. Trigger keywords: static_typing, signal_architecture, unique_nodes, @onready, class_name, signal_up_call_down, gdscript_style_guide.
Perform technical analysis on stock K-line data, calculate indicators such as MA/MACD/RSI, and judge trends and trading signals. Trigger scenarios: (1) "Analyze the technical aspects of Moutai" (2) "Check if this stock is buyable" (3) "Technical analysis 600519" (4) Used when needing to judge stock trends and trading points. Need to use data-collect to obtain data first
Abstract detector tickets and hints into reusable edge concepts with thesis, invalidation signals, and strategy playbooks before strategy design/export.
Detects Follow-Through Day (FTD) signals for market bottom confirmation using William O'Neil's methodology. Dual-index tracking (S&P 500 + NASDAQ) with state machine for rally attempt, FTD qualification, and post-FTD health monitoring. Use when user asks about market bottom signals, follow-through days, rally attempts, re-entry timing after corrections, or whether it's safe to increase equity exposure. Complementary to market-top-detector (defensive) - this skill is offensive (bottom confirmation).
Detects market top probability using O'Neil Distribution Days, Minervini Leading Stock Deterioration, and Monty Defensive Sector Rotation. Generates a 0-100 composite score with risk zone classification. Use when user asks about market top risk, distribution days, defensive rotation, leadership breakdown, or whether to reduce equity exposure. Focuses on 2-8 week tactical timing signals for 10-20% corrections.