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Found 62 Skills
Comprehensive guide for interacting with the hydric Liquidity Pools Indexer (Envio/HyperIndex). Use this skill when you need to (1) Query real-time Liquidity Pool data like TVL, Volume, Fees, or Yields/APY, (2) Fetch cross-chain token metadata and prices, (3) Aggregate protocol data (Uniswap, etc.), (4) Retrieve historical time-series data for generic analytics
Detect abnormal access patterns in AWS S3, GCS, and Azure Blob Storage by analyzing CloudTrail Data Events, GCS audit logs, and Azure Storage Analytics. Identifies after-hours bulk downloads, access from new IP addresses, unusual API calls (GetObject spikes), and potential data exfiltration using statistical baselines and time-series anomaly detection.
Fee velocity and volume momentum tracker for Bitflow HODLMM pools — detects entry windows by comparing today's fee capture against the 7-day baseline, building a local time-series to surface trend direction (accelerating, stable, cooling).
Workload-aware architecture design for Apache Doris. MUST USE when designing data architectures, choosing between data models, planning ingestion strategies, sizing clusters, or translating business requirements into Apache Doris system designs. Complements doris-best-practices with decision frameworks and sizing-first workflow. Use when user describes a workload involving: IoT, sensor data, telemetry, real-time analytics, dashboard, log analysis, log search, CDC sync, time-series, device monitoring, point query service, ad-hoc analytics, lakehouse federation, ETL/ELT pipeline, report analytics, clickstream, user behavior, observability, metrics, fleet tracking, or any OLAP workload requiring table design from scratch. Also triggers on prompts like: "design a table for...", "how should I store...", "build an architecture for...", "we have X devices sending data every Y seconds", "recommend a cluster size for...", "what data model should I use for...", "we need to ingest X GB/day", "migrate from MySQL/PostgreSQL to Apache Doris". Also use for legacy analytics/search/serving stack consolidation prompts even when Apache Doris is not named explicitly, including replacing or migrating from Impala, Kudu, Elasticsearch/ES, Greenplum, Presto, HBase, Hive, Hadoop, Redis, or Lambda-style multi-engine data platforms.
Quantitative statistics framework for time-series analysis using Longbridge price data — ADF unit root test (stationarity), cointegration (Engle-Granger / Johansen), GARCH volatility modelling (conditional heteroskedasticity), regression diagnostics (Durbin-Watson / Breusch-Pagan), bootstrap confidence intervals, hypothesis tests (t-test / F-test). Requires statsmodels and scipy. Triggers: "量化统计", "ADF检验", "单位根", "协整检验", "GARCH", "自相关", "异方差", "Bootstrap", "假设检验", "量化統計", "ADF檢驗", "單位根", "協整檢驗", "異方差", "假設檢驗", "quantitative statistics", "ADF test", "unit root", "cointegration", "GARCH", "autocorrelation", "heteroskedasticity", "bootstrap", "hypothesis test", "statsmodels".
Implements Syncfusion ASP.NET Core Chart (SfChart) for data visualization. Use this when building charts, visualizing time-series or categorical data, or creating dashboards. Covers series configuration (line, bar, pie), axes, tooltips, legends, and customization for ASP.NET Core applications.
A high-level interactive graphing library for Python. Ideal for web-based visualizations, 3D plots, and complex interactive dashboards. Built on plotly.js, it allows users to zoom, pan, and hover over data points in a browser-based environment. Use for interactive charts, web applications, Jupyter notebooks, 3D data visualization, geographic maps, financial charts, animations, time-series analysis, and building production-ready dashboards with Dash.
Daily compression of time-series data with merge logic for multiple pipeline runs, structured aggregation for dashboards, and storage estimation for capacity planning.
Financial Data Analysis Skill (based on `bl mcp` + Alibaba Cloud Bailian MCP Market `market-cmapi00073529`), covering financial instruments such as China A-shares, funds, and bonds. It supports stock screening, fund screening, fund manager screening, financial data query (net profit / revenue / ROE, etc.), macro and industry time-series data (GDP / CPI / production-sales-price), brokerage research report retrieval, and A-share listed company announcement retrieval. Be sure to activate when users ask about the following keywords: stock selection / stock screening, fund screening, fund manager screening, financial data / net profit / revenue / valuation, macroeconomy / GDP / CPI, industry production-sales-price, brokerage research report / industry research report, listed company announcement. Not applicable to: general programming issues, non-financial data, non-Chinese market instruments.
Implement Syncfusion Angular Stock Chart component for displaying financial data and OHLC charts. Use this skill whenever users need to create stock charts, display candlestick or OHLC data, add technical indicators, implement date range selection, or work with time-series financial visualization. Includes series types, axis customization, interactive features, and export capabilities.
Implement Syncfusion Blazor Stock Chart (SfStockChart) for financial data visualization. Use this when working with stock charts, candlestick displays, OHLC data, or technical indicators like SMA, EMA, MACD, and Bollinger Bands. This skill covers period selectors, range navigation, and financial time-series data visualization in Blazor applications.
Query and analyze data in Azure Data Explorer (Kusto/ADX) using KQL for log analytics, telemetry, and time series analysis. USE FOR: KQL queries, Kusto database queries, Azure Data Explorer, ADX clusters, log analytics, time series data, IoT telemetry, anomaly detection DO NOT USE FOR: SQL databases (use azure-postgres), NoSQL queries (use azure-storage), Elasticsearch, AWS analytics tools