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Found 149 Skills
Enrich contact and company data using x402-protected APIs. Superior to generic web search for structured business data. USE FOR: - Enriching person profiles by email, LinkedIn URL, or name - Enriching companies by domain - Finding contact details (email, phone) with confidence scores - Scraping full LinkedIn profiles (experience, education, skills) - Searching for people or companies by criteria - Bulk enrichment operations (up to 10 at a time) TRIGGERS: - "enrich", "lookup", "find info about", "research" - "who is [person]", "company profile for", "tell me about" - "find contact for", "get LinkedIn for", "get email for" - "employee at", "works at", "company details" ALWAYS use x402.fetch for enrichx402.com endpoints - never curl or WebFetch. Returns structured JSON data, not web page HTML. IMPORTANT: Never guess endpoint paths. All paths follow the pattern https://enrichx402.com/api/{provider}/{action}. Use exact URLs from the Quick Reference table below or call x402.discover_api_endpoints first.
Pyspark Transformer - Auto-activating skill for Data Pipelines. Triggers on: pyspark transformer, pyspark transformer Part of the Data Pipelines skill category.
Creates custom Docker-based State Transition Functions (STFs) for D6E platform workflows. Use when building containerized business logic for D6E, implementing data processing steps, or creating workflow functions that need database access. Handles JSON input/output, SQL API integration, and multi-language implementations (Python, Node.js, Go).
A fast, extensible progress bar for Python and CLI. Instantly makes your loops show a smart progress meter with ETA, iterations per second, and customizable statistics. Minimal overhead. Use for monitoring long-running loops, simulations, data processing, ML training, file downloads, I/O operations, command-line tools, pandas operations, parallel tasks, and nested progress bars.
Identify key themes and concerns raised by analysts during earnings calls, including specific analyst attribution and topic categorization.
Under the assumption that the US dollar or a certain currency loses its reserve status and gold becomes the only anchor, deduce the 'implied gold price that the balance sheet can withstand' by dividing central bank monetary liabilities by gold reserves, and output the leverage level, gap and ranking of each country or currency.
Create and execute temporary scripts (Python, Node.js, shell) during workflow execution for API integrations, data processing, and custom tools. Use when user needs to interact with external APIs, process data with specific libraries, or create temporary executable code.
Build event streaming and real-time data pipelines with Kafka, Pulsar, Redpanda, Flink, and Spark. Covers producer/consumer patterns, stream processing, event sourcing, and CDC across TypeScript, Python, Go, and Java. When building real-time systems, microservices communication, or data integration pipelines.
Analyze datasets to discover patterns, anomalies, and relationships. Use when exploring data files, generating statistical summaries, checking data quality, or creating visualizations. Supports CSV, Excel, JSON, Parquet, and more.
Databricks development guidance including Python SDK, Databricks Connect, CLI, and REST API. Use when working with databricks-sdk, databricks-connect, or Databricks APIs.
Sync retirement account data from Vanguard and Fidelity CSV exports to Google Sheets DataHub. Handles multiple accounts, aggregates holdings by ticker, and updates quantities in retirement section (rows 46-62). Triggers on sync retirement, update retirement, vanguard sync, 401k update, IRA sync, or working with notebooks/retirement-accounts/ files.
Sync dividend data from Fidelity CSV to Dividends sheet. Reads dividend.csv from notebooks/updates/, calculates actual dividends received (shares × amount per share), writes to input area (rows 2-46), then clicks Add Dividend button to process. Triggers on sync dividends, update dividends, dividend tracker, layer 2 income, or monthly dividend analysis.