productivity▌

Expert guidance on PostgreSQL-specific features, optimization patterns, and advanced data type capabilities. \n \n Covers JSONB operations, array types, window functions, full-text search, custom types, range types, and geometric types with practical examples \n Includes query optimization strategies using EXPLAIN ANALYZE, index design patterns (composite, partial, covering, expression), and connection/memory management \n Provides monitoring and maintenance techniques via pg_stat_statements, pg

Interactive workflow to refine task prompts through structured questioning and clipboard delivery. \n \n Guides users through systematic prompt refinement by interrogating scope, deliverables, constraints, and technical requirements \n Produces polished markdown prompts and automatically copies them to the system clipboard via the Joyride extension \n Focuses exclusively on prompt engineering; does not generate code or implementation details \n Requires the Joyride extension for VSCode clipboard

Credit risk data cleaning and variable screening pipeline for pre-loan modeling. \n \n Executes 11 independent steps covering data loading, abnormal period filtering, missing rate analysis, low-IV and high-PSI variable removal, null importance denoising, and correlation-based feature elimination \n Supports organization-level analysis with separate modeling and out-of-sample (OOS) sample handling, plus multi-process acceleration for IV and PSI calculations \n Generates comprehensive Excel report

Comprehensive token security analyzer checking ERC20/ERC721 conformity, 24+ weird token patterns, and integration safety. \n \n Analyzes both token implementations and protocol integrations across 10 assessment categories, including contract composition, owner privileges, and on-chain scarcity \n Detects 24+ known weird token patterns (fee-on-transfer, missing return values, reentrant hooks, pausable tokens, blocklists, and more) with specific code evidence \n Integrates Slither analysis for ERC

Vision-driven browser automation from screenshots, no DOM access required. \n \n Operates in a headless Puppeteer browser that persists across CLI calls, allowing sequential commands without session loss \n Interacts with all visible page elements using natural language prompts; no CSS selectors or accessibility labels needed \n Requires configuration of a vision-capable model (Gemini, Qwen, Doubao, or similar) via environment variables for visual grounding \n Supports connect, take_screenshot,

Turn a user request into a single, actionable plan with atomic steps.

Agents on Eve Horizon have no built-in "memory" primitive, but the platform provides storage systems at every timescale. This skill teaches how to compose them into coherent memory for agents that learn, remember, and share.

Alva is an agentic finance platform. It provides unified access to 250+ financial data sources spanning crypto, equities, ETFs, macroeconomic indicators, on-chain analytics, and social sentiment -- including spot and futures OHLCV, funding rates, company fundamentals, price targets, insider and senator trades, earnings estimates, CPI, GDP, Treasury rates, exchange flows, DeFi metrics, news feeds, social media and more!

Automate Google Classroom course creation and student enrollment workflows. \n \n Creates courses with customizable name, section, room, and owner details via the gws-classroom skill \n Invites students by email with role assignment (e.g., STUDENT) and lists enrolled participants \n Requires the gws-classroom skill as a prerequisite dependency \n

READMEs answer questions your audience will have. Different audiences need different information - a contributor to an OSS project needs different context than future-you opening a config folder.