Skill UI

A comprehensive skill for generating production-grade, robust automation scripts and end-to-end tests using Selenium WebDriver. Supports multiple languages (Java, Python, JS, C#, etc.) and execution environments, including local machines and TestMu AI cloud for cross-browser compatibility. It guides users on best practices like explicit waits, Page Object Model (POM), and stable locator strategies, acting as a senior QA automation architect.

This extension tracks how often your brand is cited or mentioned across leading Large Language Models (LLMs) like ChatGPT and Perplexity. It provides detailed time-series data, including citation rates and trend deltas (week-over-week, month-over-month). It is essential for SEO professionals to monitor brand authority and visibility within the rapidly evolving landscape of generative AI search results.

A comprehensive guide for training or fine-tuning advanced sentence-transformer models. This skill assists in selecting the correct architecture—including Bi-encoders (SentenceTransformer), CrossEncoders (for reranking), and SparseEncoders—for various Natural Language Processing (NLP) tasks. Use cases include semantic retrieval, similarity matching, document clustering, and pair-wise classification.

This skill provides expert capabilities for training and fine-tuning transformer language models using the TRL (Transformers Reinforcement Learning) library. It supports state-of-the-art post-training methods, including Supervised Fine-Tuning (SFT), Direct Preference Optimization (DPO), Group Relative Policy Optimization (GRPO), and Reward Model training. Use this skill to align and customize foundation models for advanced tasks via CLI commands.

A comprehensive guide to designing transparent, predictable, and developer-friendly usage-based pricing models. Learn which metrics (API calls, compute time, storage) developers accept, how to structure clear pricing pages, and how to avoid confusing or punitive billing practices to maximize adoption and revenue.

This skill generates comprehensive end-to-end (E2E) automation tests using WebdriverIO (WDIO) in JavaScript or TypeScript. It supports various frameworks (Mocha, Jasmine, Cucumber) and includes advanced patterns like the Page Object Model (POM) and robust selector strategies. Users can configure tests for local execution or integrate with cloud services like LambdaTest, making it ideal for simulating complex user interactions and ensuring application quality across multiple browsers and environments.

A powerful plugin enabling Claude Code to delegate complex tasks to external AI CLIs (such as OpenAI Codex or Google Antigravity/Gemini) without exiting the conversation. It supports multi-model workflows, allowing users to seek a second opinion, cross-check deep analysis, or delegate side tasks (like research or code review). The core value is that Claude synthesizes the raw outputs, providing a critical review and reconciliation of findings across all consulted models.

A comprehensive 10-page pitch deck template designed for fundraising and presenting to venture capitalists (VCs). It covers all essential sections, including problem identification, solution overview, market size (TAM/SAM/SOM), traction data visualization, business model, go-to-market strategy, and the funding ask. Ideal for startups seeking seed or Series A funding.

This guide provides a comprehensive reference on Agent Skills, a standardized and powerful method for providing structured context, workflows, and tools to Large Language Models (LLMs). It details the anatomy of the SKILL.md file, the three-stage progressive disclosure loading process, and best practices for creating both capability (tool-based) and process (workflow-based) primitives. Use this resource when designing, reviewing, or debugging agent-driven applications to ensure reliable and context-efficient performance.

This guide explains how to register custom model slugs (variants) within the Pi Agent's configuration files. It is essential for ensuring that specialized OpenRouter variants or brand-new provider models, which are not part of the static bundled registry, resolve correctly and are available for accurate agent model invocation.

This skill executes the DeepSWE benchmark, a comprehensive coding-agent evaluation suite. It uses OpenRouter and mini-swe-agent to score various Large Language Models (LLMs) on 113 tasks, providing reproducible results for model comparison, development assessment, and research benchmarking. Use this when a standardized, deep evaluation of LLM coding capabilities is required.

This tool manages the formal documentation of significant architectural decisions (ADRs). It automatically assigns sequential numbering, generates structured Markdown files (ADR-NNN), and registers the decision in the AgentDB graph. Use it when documenting technology choices, API designs, or data model changes to maintain a clear, traceable, and centralized history of system evolution.