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Found 841 Skills
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.
This skill should be used when the user asks to "connect to Trading 212", "authenticate Trading 212 API", "place a trade", "buy stock", "sell shares", "place market order",, "place pending order", "place limit order", "cancel order", "check my balance", "view account summary", "get positions", "view portfolio", "check P&L", "find ticker symbol", "search instruments", "check trading hours", "view dividends", "get order history", "export transactions", "generate CSV report", or needs guidance on Trading 212 API authentication, order placement, position monitoring, account information, instrument lookup, or historical data retrieval.
Generate analytics reports from Olakai data using CLI commands. AUTO-INVOKE when user wants: usage summaries, KPI trends, risk analysis, ROI reports, efficiency metrics, agent comparisons, token usage reports, cost analysis, compliance reports, or any analytics without using the web dashboard. TRIGGER KEYWORDS: olakai, analytics, reports, usage summary, KPI trends, risk analysis, ROI, efficiency, agent comparison, token usage, cost analysis, metrics report, dashboard data, CLI analytics, terminal report, compliance, usage report, event summary, performance metrics, AI usage stats. DO NOT load for: setting up monitoring (use olakai-add-monitoring), troubleshooting (use olakai-troubleshoot), or creating new agents (use olakai-create-agent).
Comprehensive data validation using Pydantic v2 with data quality monitoring and schema alignment for PlanetScale PostgreSQL. Use when implementing API validation, database schema alignment, or data quality assurance. Triggers: 'validation', 'Pydantic', 'schema', 'data quality'.
Use when creating Makefiles for process lifecycle management with PID tracking, logging, and status monitoring. Triggers on: 'use makefile mode', 'makefile', 'create makefile', 'process management', 'background jobs', 'start/stop services'. Full access mode - can create/modify Makefiles.
Use this skill when deploying ML models to production, setting up model monitoring, implementing A/B testing for models, or managing feature stores. Triggers on model deployment, model serving, ML pipelines, feature engineering, model versioning, data drift detection, model registry, experiment tracking, and any task requiring machine learning operations infrastructure.
Fetches web pages and converts them to clean markdown using a robust 3-tier chain (Firecrawl → Jina Reader → Scrapling stealth browser). Use this skill instead of WebFetch whenever the user provides a URL and needs the page's text content — especially for sites that block direct access: medium.com articles (paywalled/metered), WeChat public accounts (mp.weixin.qq.com, geo-restricted), documentation sites with bot protection, or any page where simple HTTP fetching might return a CAPTCHA or empty page. Triggers for: "read this URL", "summarize this article/page", "grab the content from", "extract text from", "what does this page say", "fetch this link", or any request to access and process a specific web page. Do NOT trigger for: building scrapers, checking HTTP status codes, parsing already-downloaded HTML files, answering conceptual questions about scraping tools, or monitoring page changes.
Set up and run ongoing competitive intelligence monitoring for a client. Tracks competitor content, ads, reviews, social, and product moves.
Use when the user needs CI/CD pipelines, Docker configuration, Kubernetes deployment, infrastructure-as-code, monitoring, or zero-downtime deployment strategies. Triggers: user says "devops", "docker", "kubernetes", "CI/CD", "infrastructure", "monitoring", "deploy to production", "container", "terraform", "observability".
Data validation using Great Expectations. Expectation suites, checkpoints, and data docs for pipeline monitoring.
Convert websites into LLM-ready data with Firecrawl API. Features: scrape, crawl, map, search, extract, agent (autonomous), batch operations, and change tracking. Handles JavaScript, anti-bot bypass, PDF/DOCX parsing, and branding extraction. Prevents 10 documented errors. Use when: scraping websites, crawling sites, web search + scrape, autonomous data gathering, monitoring content changes, extracting brand/design systems, or troubleshooting content not loading, JavaScript rendering, bot detection, v2 migration, job status errors, DNS resolution, or stealth mode pricing.
Track real-time cryptocurrency prices across exchanges with historical data and alerts. Provides price data infrastructure for dependent skills (portfolio, tax, DeFi, arbitrage). Use when checking crypto prices, monitoring markets, or fetching historical price data. Trigger with phrases like "check price", "BTC price", "crypto prices", "price history", "get quote for", "what's ETH trading at", "show me top coins", or "track my watchlist".