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Found 638 Skills
Normalize messy creator campaign metrics from multiple sources into a single clean table with standardized field names ready to merge into your master tracker. This skill should be used when cleaning up influencer metrics, standardizing campaign data from multiple platforms, normalizing creator performance numbers, merging metrics from Instagram and TikTok and YouTube into one sheet, formatting messy analytics exports, preparing campaign data for a master spreadsheet, converting raw platform stats into a consistent format, combining metrics from different reporting tools, deduplicating creator data from multiple sources, fixing inconsistent column names across exports, or cleaning up a metrics dump before reporting. For calculating engagement rates, see engagement-rate-calculator-benchmarker. For full campaign reports, see campaign-roi-calculator. For parsing a single Story screenshot, see story-metrics-screenshot-parser.
Stream call audio in real-time, fork media to external destinations, and transcribe speech live. Use for real-time analytics and AI integrations. This skill provides Python SDK examples.
Forecast Generator - Auto-activating skill for Data Analytics. Triggers on: forecast generator, forecast generator Part of the Data Analytics skill category.
Query Web3 blockchain data from Moralis API. Use when user asks about wallet data (balances, tokens, NFTs, transaction history, profitability, net worth), token data (prices, metadata, DEX pairs, analytics, security scores), NFT data (metadata, transfers, traits, rarity, floor prices), DeFi positions, entity/label data for exchanges and funds, or block and transaction data. Supports EVM chains (Ethereum, Polygon, BSC, Arbitrum, Base, Optimism, Avalanche, etc.) and Solana. NOT for real-time streaming - use moralis-streams-api instead.
Use when the user asks about RevenueCat data, analytics, charts, KPIs
End-to-end data engineering pipeline for Harvard Art Museums API with ETL, SQL analytics, and Streamlit visualization
Generate and retrieve usage reports for billing, analytics, and reconciliation. This skill provides REST API (curl) examples.
Use ProviderObserver to log or debug Riverpod provider lifecycle; didUpdateProvider, ProviderScope observers, naming providers. Use when adding logging, analytics, or debugging for provider state changes. Use this skill when the user asks about ProviderObserver, logging Riverpod, or debugging provider updates.
World-class data science skill for statistical modeling, experimentation, causal inference, and advanced analytics. Expertise in Python (NumPy, Pandas, Scikit-learn), R, SQL, statistical methods, A/B testing, time series, and business intelligence. Includes experiment design, feature engineering, model evaluation, and stakeholder communication. Use when designing experiments, building predictive models, performing causal analysis, or driving data-driven decisions.
Search and analyze Tencent Cloud CLS (Cloud Log Service) logs. Use whenever the user asks to: search logs, debug API errors, trace requests by trace ID, find 5xx errors, run CQL/SQL analytics over log topics, extract structured fields. Backed by the official tencentcloud-sdk-python CLS client.
RevenueCat CLI tool for subscription analytics, MRR tracking, customer management, and offering configuration. Use when analyzing app revenue, checking subscriber status, managing offerings/packages/entitlements, querying chart data, setting up webhooks, or any RevenueCat API interaction via CLI. Triggers on "revcat", "RevenueCat", "MRR", "subscription analytics", "revenue metrics", "offerings", "entitlements", "paywalls", or when the user wants to interact with RevenueCat data.
Build end-to-end ETL pipelines and analytics dashboards using Harvard Art Museums API data with Python, SQL, and Streamlit