Skill UI

A comprehensive skill for managing the entire lifecycle of Volcano Jobs within the KubeSphere environment. It supports the scheduling and execution of complex batch workloads, including deep learning tasks using PyTorch and TensorFlow, MPI, and general resource-intensive jobs. Provides detailed API usage and troubleshooting guidance for job scheduling and resource conflicts.

A powerful, kubectl/docker-style CLI tool designed to manage and submit distributed computing jobs on the Qizhi (启智) platform. Use it for tasks like logging in, checking resource availability, discovering workspaces, and submitting complex GPU, CPU, or batch jobs efficiently.

This workflow guides users through the complete lifecycle of customizing large language models (LLMs). It covers uploading training data, initiating fine-tuning jobs, monitoring training progress, managing model versions, and finally deploying the optimized model to a dedicated, autoscaling inference endpoint using the Together AI API. Ideal for production-level customization.

This skill provides an expert framework for applying psychological principles and mental models to marketing strategy. It helps users understand deep consumer behavior, solve complex decision-making problems, and ethically influence purchasing decisions. Use it when addressing cognitive biases, persuasion techniques, or needing foundational frameworks like First Principles and Jobs to Be Done for strategic optimization.

This skill provides a rigorous, data-driven framework to interrogate product roadmaps and feature commitments using six critical questions. It forces teams to think beyond mere features, focusing on Jobs To Be Done (JTBD), North Star Metrics, Product-Market Fit (PMF) signals, RICE scoring, opportunity cost, and defining clear kill criteria. It is ideal for quarterly planning, major feature launches, and assessing product pivots to ensure strategic alignment.

A powerful solution for handling background jobs and asynchronous tasks within Django applications using Celery. It facilitates task queuing, reliable worker management, scheduled execution (cron jobs), and robust error handling. Ideal for sending emails, processing heavy data loads, or managing complex, multi-step workflows without blocking the main thread.

A powerful Node CLI tool for sending both SMS and iMessage directly from a shell environment, script, or automation hook. It simplifies outbound communication by handling account setup and message sending without requiring a dedicated API client or webhook server. Ideal for cron jobs, CI/CD pipelines, and agent turn notifications.

HasData is a comprehensive cloud platform designed for extracting structured public web data. It supports three core execution modes: Web Scraping API for arbitrary URLs (including JS rendering), pre-parsed Scraper APIs for known platforms (like Google or Amazon), and asynchronous Scraper Jobs for bulk or recursive crawling. Ideal for market research, e-commerce intelligence, job data collection, and local business lead generation.

The RunAPI CLI serves as the dedicated execution layer for interacting with RunAPI's suite of advanced AI models. It allows developers to programmatically generate multimodal content, including images, videos, and music/audio, directly from the terminal or CI/CD pipeline. Users can submit one-off jobs, manage asynchronous tasks, and pass complex JSON request bodies to various services like Suno, Claude, and Gemini, making it essential for robust AI automation workflows.

This advanced skill provides highly structured and actionable feedback on any digital or physical design. It applies professional UX frameworks, including Nielsen's Heuristics, Gestalt principles, and Jobs-to-be-Done (JTBD), to evaluate usability, identify critical issues, and provide prioritized, specific recommendations. Ideal for reviewing wireframes, UI screens, user flows, and assessing product completeness.

A comprehensive framework for structuring user interviews, customer discovery, or Jobs-to-be-Done (JTBD) research. This guide provides structured steps for screener creation, deep behavioral exploration (focusing on past actions, not future predictions), and systematic synthesis/pattern detection, ensuring the gathering of genuine, actionable insights.

This skill guides product teams beyond listing features by applying the Jobs-to-be-Done (JTBD) framework. It maps customer needs across functional, emotional, and social dimensions, allowing teams to write precise job stories. Use this to conduct deep user research, identify core pain points, and define product opportunities based on user outcomes rather than mere outputs.