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Found 10 Skills
Detect buying signals from multiple sources, qualify leads, and generate outreach context
Build enriched prospect lists from ICP criteria - find targets, enrich contacts, score accounts, detect trigger signals
Identify non-obvious signals, hidden patterns, and clever correlations in datasets using investigative data analysis techniques. Use when analyzing social media exports, user data, behavioral datasets, or any structured data where deeper insights are desired. Pairs with personality-profiler for enhanced signal extraction. Triggers on requests like "what patterns do you see", "find hidden signals", "correlate these datasets", "what am I missing in this data", "analyze across datasets", "find non-obvious insights", or when users want to go beyond surface-level analysis. Also use proactively when you notice interesting anomalies or correlations during any data analysis task.
Detect buying signals across TAM companies and watchlist personas. Three-phase architecture: (1) free diff-based signals from existing data (headcount growth, tech stack changes, funding rounds), (2) Apify-powered signals (job postings, LinkedIn content analysis, profile changes), and (3) post-processing with dedup, scoring, and lead status updates. Writes signals to Supabase signals table for downstream activation.
Identifies, monitors, and analyzes industry trends including technology adoption, market shifts, regulatory changes, and emerging patterns using weak signal detection and trend forecasting. Use when the user requests trend analysis, industry forecasting, emerging technology tracking, or wants to identify market opportunities and threats.
Lightweight scanner tracking Smart Money market concentration across all Hyperliquid assets. Flags assets accelerating up the ranks before they become crowded top-3 plays. IMMEDIATE_MOVER signal fires on 10+ rank jumps with quality filters (erratic history, velocity gate, trader count floor, max leverage check). One API call per scan, runs every 60 seconds. Use when detecting SM rotations, finding emerging opportunities early, or monitoring rank acceleration patterns.
End-to-end outbound prospecting: detect intent signals, research companies, find decision-maker contacts, personalize messaging, launch campaign.
Trend intelligence and cultural signal detection for emerging news and behaviors. USE WHEN: Researching latest news (48h), identifying cultural/tech/consumer shifts before mainstream adoption, analyzing emerging trends with advanced elicitation. PRIMARY TRIGGERS: "coolhunt [topic]" = Full research workflow (5 steps) "trend analysis" = Deep analysis with elicitation methods "news scan [topic]" = Quick news gathering WORKFLOW: Request → Web Research → Elicitation Selection → Analysis → Report OUTPUT: Markdown report with headline, summary, fact-check, and behavioral analysis saved to coolhunter-output/report-{datetime}/{title}.md
Assess chemical and drug toxicity via adverse outcome pathways, real-world adverse event signals, and toxicogenomic evidence. Integrates AOPWiki (AOPWiki_list_aops, AOPWiki_get_aop) for mechanism- level pathway tracing, FAERS for post-market adverse event quantification, OpenFDA for label mining, and CTD for chemical-gene-disease evidence. Produces structured toxicity reports with evidence grading (T1-T4). Use when asked about toxicity mechanisms, adverse outcome pathways, AOP mapping, FAERS signal detection, or chemical-disease relationships for drugs or environmental chemicals.
Comprehensive drug safety review integrating FDA labels, FAERS adverse event reports, disproportionality analysis, pharmacogenomics, clinical trials, and literature. Use for regulatory assessments, post-market surveillance, drug safety reviews, adverse event investigation, and pharmacovigilance.