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Found 412 Skills
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.
Macro liquidity monitoring and risk early-warning system. By tracking 4 core indicators (Fed Net Liquidity, SOFR Overnight Financing Rate, MOVE Treasury Volatility Index, Yen Carry Trade Signals), it provides real-time assessment of liquidity conditions in the global financial system, outputting liquidity ratings and risk response recommendations. When users mention topics such as liquidity, Fed balance sheet reduction (QT), TGA account, reverse repo ON RRP, SOFR rate, MOVE index, Treasury volatility, yen carry trade, USDJPY and interest rate differentials, impact of QT on markets, whether money is tight, liquidity inflection points, tightening financial conditions, etc., this skill should be used. Even if users ask broadly "how is liquidity right now" or "is the Fed draining or injecting liquidity," this skill should be triggered to provide a structured analytical framework.
Use for decision-grade Abel causal reads: explain what is driving a market or company node, how two nodes connect, what changes under intervention, or how a real-world choice looks when routed through Abel proxy signals. Use when user says "Abel" or "causal" or "causality" or "drivers" or "what if" in the context of market, business, crypto, or proxy-routed questions.
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.
Full-story verification — infers what the user is building, then verifies the complete flow end-to-end: browser → API → data → response. Triggers on dev server start and 'why isn't this working' signals.
Detecting whether agent iterations are converging toward a stable solution or hitting a ceiling. Covers convergence signals, ceiling detection, non-convergence diagnosis, test pass rate as a convergence metric, and forward progress tracking for large projects. Trigger phrases: "convergence", "is the agent converging", "ceiling detection", "when to stop iterating", "diminishing returns"
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).
Produces a private strategic preparation document for the user before a meeting that matters. Captures stakes, stakeholder positions and reads, ranked desired outcomes, key messages, anticipated questions with prepared responses, risks and tensions, specific asks, and success signals. Distinct from meeting-agenda because this artifact is not shared with attendees; it is the user's personal tactical prep for meetings where positioning matters.
Adapts experiences across cultures and languages — not just translation, but cultural reconception. Part of the Intent design strategy system. When a product enters a new market, everything is in play: information density, navigation patterns, color meaning, icon comprehension, date formats, trust signals, payment flows, and the fundamental assumptions about how people make decisions. Trigger when: planning international expansion, auditing i18n readiness, adapting designs for RTL languages, reviewing cultural assumptions in a design, preparing localization test plans, or when someone says "we need to launch in [country]" and the plan is "just translate it." Also trigger for compliance reviews across markets (GDPR, PIPL, accessibility laws).
Ichimoku Cloud (一目均衡表) five-line system signal engine for stocks listed in HK / US / A-share / Singapore via Longbridge Securities. Computes Tenkan-sen, Kijun-sen, Senkou Span A/B, and Chikou Span from OHLCV data; generates price-vs-cloud position, line-cross signals, and full trend-confirmation scores. Triggers: "一目均衡表", "一目云", "云图", "转折线", "基准线", "先行带", "迟行线", "云上", "云下", "一目均衡表", "一目雲", "雲圖", "轉折線", "基準線", "先行帶", "遲行線", "ichimoku", "ichimoku cloud", "tenkan sen", "kijun sen", "senkou span", "chikou span", "cloud breakout".
Diagnose why a SigNoz alert fired by correlating the alert's own signal with neighbor signals (error rate, latency, throughput, CPU/memory), traces, and logs around the fire window — and rank likely causes. Make sure to use this skill whenever the user asks "why did this alert fire", "what caused alert X", "investigate this alert", "RCA for the alert that paged me", "what's wrong with [service]" in the context of a recent fire, or otherwise asks for a root-cause analysis of a firing or recently-fired alert. Read-only — does not modify any alert or notification.
Build Temporal workflow applications in Go. Use when creating or modifying Temporal workflows, activities, workers, clients, signals, queries, updates, retry policies, saga patterns, or writing Temporal tests.