productivity▌

Complete company and person research powered by web search, enriched with verified contact data and CRM history when available. \n \n Researches companies and individuals via web search alone, extracting business overview, recent news, hiring signals, leadership team, and product details \n Supercharged by optional enrichment connectors that add verified emails, phone numbers, tech stack, org charts, and funding details \n Integrates with CRM to surface prior relationship history, past opportuni

Generates a fully configured Spring Boot project from scratch using the Spring Initializr API. The skill walks the user through selecting project parameters, choosing an architecture style (DDD or Layered), configuring data stores, and setting up Docker Compose for local development. The result is a build-ready project with standardized structure, dependency management, and configuration.

Visual comparison of web pages or elements across two URLs or images. \n \n Captures screenshots at desktop, mobile (375x812), or tablet (768x1024) viewports, with optional full-page scrolling \n Supports CSS selectors to isolate specific elements, and accepts file://, http://, https:// URLs or local image paths \n Generates markdown-formatted output with automatic image upload to 0x0.st (or GitHub Gist) for easy PR integration \n Includes Vercel deployment protection detection and GitHub CLI in

Search the web for one or more queries in parallel via the Serper API.

通过 Bitable API 操作数据、字段、视图和权限。

Use this skill to keep App Store Connect (ASC) and RevenueCat aligned, including creating missing ASC items and mapping them to RevenueCat resources.

Build a production-ready, AI-powered data collection agent for any public data source. Runs on a schedule, enriches results with a free LLM, stores to a database, and improves over time.

Comprehensive security guidance for Laravel applications to protect against common vulnerabilities.

If you see unfamiliar placeholders or need to check which tools are connected, see CONNECTORS.md.

Expert guide for optimizing LLM prompts through patterns, testing, and systematic refinement. \n \n Covers five core techniques: few-shot learning, chain-of-thought reasoning, prompt optimization, template systems, and system prompt design \n Includes progressive disclosure patterns that scale complexity from simple instructions to multi-example reasoning traces \n Provides practical examples for each pattern, from code review templates to bug analysis workflows \n Emphasizes testing and iterati