Skill UI

This skill guides the creation of high-converting, honest comparison and alternative pages for developer tools. It teaches how to structure content that ranks for competitive SEO terms (e.g., "[Competitor] alternatives," "[Product] vs [Competitor]"), capturing high-intent traffic by addressing user pain points and providing clear technical differentiation.

A comprehensive guide to designing effective free tiers, freemium models, and free trials for developer tools. It teaches how to create usage limits and feature gates that encourage natural conversion to paid plans without causing developer resentment or hindering initial adoption.

This guide details best practices for implementing robust, type-safe GraphQL queries and mutations. It covers using separate .gql files, running code generation tools, and implementing mandatory error handling (onError) and loading states. Use this when building complex, reliable data fetching layers with Apollo Client.

This skill provides comprehensive access to the Hugging Face Hub ecosystem via MCP server tools. Users can search for state-of-the-art models, datasets, and research papers, retrieve detailed repository information, fetch documentation, run compute jobs on GPU/CPU, and interact with Gradio Spaces as fully functional AI tools. Ideal for ML development, research, and application prototyping.

This skill guides users through the complete lifecycle of data quality incident management using Monte Carlo MCP tools. It performs detailed investigation, including root cause analysis and blast radius assessment. It then coordinates various external tools (APIs, CLI) to propose and execute appropriate remediation actions, ensuring all data incidents are resolved with full context.

This skill enhances SEO visibility specifically for non-Google engines like Bing, Yandex, Seznam, and Naver. It utilizes Bing Webmaster Tools and the IndexNow protocol to ensure fresh content and links are indexed quickly. It is crucial for maximizing citation eligibility in Microsoft Copilot and gaining access to unique link data beyond Google's reach.

Rewrites overly formal or vague code review comments generated by AI or corporate tools. It cuts out filler phrases like "I noticed..." or "It might be worth considering...", transforming them into direct, actionable feedback. The output uses a clear format (Location: Severity: Observation. Fix.) that sounds like it came from a helpful, experienced teammate, significantly improving the quality and reception of PR feedback.

Utilizes Expo DOM components to render web code verbatim inside a webview on native platforms, while maintaining native rendering on the web. This enables developers to integrate web-only libraries (such as charting tools, syntax highlighters, or complex CSS layouts) and incrementally migrate existing web components into a React Native application without substantial rewriting.

This skill provides the central management layer for defining an AI agent's capabilities. It uses the `capabilities.yaml` file as the single source of truth to configure everything from integrated skills, tools, hooks, and sub-agents. Use this when running any `capa` command (install, clean, add, etc.), integrating a new service, or troubleshooting the project's entire operational environment.

The Agent Harness provides a robust, verifiable loop structure for driving complex goals across specialized domains. It converts a high-level objective into a verifiable task plan, executes tasks sequentially using domain-specific tools, and rigorously verifies every step with machine-run checks. The system includes mechanisms for retries, budget management, and mandatory human escalation, ensuring no goal is closed until all progress is verifiably complete or explicitly waived.

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.

A comprehensive suite designed for AI agents to perform safe, deep, and multi-format web searches. It allows agents to retrieve current web information, analyze PDFs, extract YouTube transcripts, and access GitHub code files. Instructions include guidelines for varying search depths and using specialized tools for code context retrieval.