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Found 426 Skills
Interpret GA4 and GSC data with benchmarks, status indicators, and actionable insights
Use this agent when you need to understand the historical context and evolution of code changes, trace the origins of specific code patterns, identify key contributors and their expertise areas, or analyze patterns in commit history. This agent excels at archaeological analysis of git repositories to provide insights about code evolution and development patterns. <example>Context: The user wants to understand the history and evolution of recently modified files.\nuser: "I've just refactored the authentication module. Can you analyze the historical context?"\nassistant: "I'll use the git-history-analyzer agent to examine the evolution of the authentication module files."\n<commentary>Since the user wants historical context about code changes, use the git-history-analyzer agent to trace file evolution, identify contributors, and extract patterns from the git history.</commentary></example> <example>Context: The user needs to understand why certain code patterns exist.\nuser: "Why does this payment processing...
Create powerful pitch closings with market insights, proprietary advantages, founder mission, and subtle FOMO triggers in under 45 seconds.
Help users run effective customer discovery conversations and extract actionable insights. Use when someone is preparing for user research, planning discovery interviews, writing interview questions, analyzing findings, validating problems, understanding customer behavior, or trying to learn what customers actually want. Triggers include mentions of "customer interviews", "user research", "discovery calls", "talking to customers", "validating ideas", "customer conversations", "problem validation", or questions about what to ask customers.
Conduct deep research on any topic — get comprehensive reports with citations, key findings, and actionable insights in minutes. Use when user wants to "deep research", "research this", "investigate", "analysis report", "深度研究", "调研", "リサーチ", "심층 연구".
Use when new insights change the scope, acceptance criteria, domain language, or technical constraints of an existing Epic, Feature, or Task — for example "refine epic
Enthu.AI platform help — contact center conversation intelligence with auto QA scorecards, agent coaching, compliance monitoring, and speech analytics. Use when setting up Enthu.AI QA scorecards for call center agents, calls not being scored or transcribed correctly, agents not seeing coaching insights from their calls, Enthu.AI integration with Aircall or RingCentral not syncing, comparing Enthu.AI vs Gong or CallMiner for contact center QA, or configuring sentiment analysis and keyword tracking. Do NOT use for building a general coaching program (use /sales-coaching) or reviewing a specific call transcript (use /sales-call-review).
Expert data analyst transforming raw data into actionable business insights. Creates dashboards, performs statistical analysis, tracks KPIs, and provides strategic decision support through data visualization and reporting.
SQL for data analysis with exploratory analysis, advanced aggregations, statistical functions, outlier detection, and business insights. 50+ real-world analytics queries.
Use when planning and synthesizing product/user research as a method-and-repository discipline — selecting the right method for the goal (generative interviews vs usability test vs concept test vs validation), computing method-based saturation/sample size with an explicit confidence level, or synthesizing coded observations into insights while flagging single-source anecdotes. Never fabricates user insight; an insight requires recurrence across independent participants. Distinct from product-team/ux-researcher-designer (persona/journey artifacts), product-discovery (discovery-sprint planning), and experiment-designer (live A/B) — this is the research-ops method + insight-repository layer.
AI-powered stock and crypto analysis using the aipa CLI. Use this skill whenever the user asks to analyze a ticker, compare stocks, get technical analysis, or answer any financial market question about Vietnamese stocks (VIC, VCB, FPT...), cryptocurrencies (BTC, ETH...), or global assets. Also use for price action analysis, moving average analysis, support/resistance questions, sector comparison, Wyckoff analysis, or trading insights. Also handles fundamental analysis when the user explicitly asks for fundamentals, PE, ROE, NPL, CAR, valuation, or "phân tích cơ bản" — use `aipa fundamentals` commands to enrich technical analysis with financial ratios, company info, and fundamental screening/ranking. For raw price data without AI, use the aipa-data skill instead.
Salesforce Data Cloud Segment phase. Use this skill when the user creates or publishes segments, manages calculated insights, or troubleshoots audience SQL in Data Cloud. TRIGGER when: user creates or publishes segments, manages calculated insights, inspects segment counts or membership, or troubleshoots audience SQL in Data Cloud. DO NOT TRIGGER when: the task is DMO/mapping/identity-resolution work (use data360-harmonize), activation work (use data360-activate), query/search-index work (use data360-query), or Standard Data Model (STDM)/session tracing (use agentforce-observe).