Skill UI

This skill is intended to analyze and improve the quality of codebases, ensuring adherence to best practices and coding standards. Note: This specific file is a translation placeholder, and the core functionality description should refer to the original skill file for details.

Use this command to set up a structured multi-agent collaboration environment within AgentHub. It allows you to define the core task, specify the required number of agents, and configure detailed evaluation criteria (metrics, directions, and commands) for both quantitative benchmarking and qualitative LLM judging. This is the starting point for any agent competition or complex AI workflow.

This skill is intended for managing the Japanese translation and localization of the core nanoclaw-repl module. The current content serves as a placeholder, indicating that the Japanese translation is actively under development. Users are advised to refer to the original English source file for the full and functional version of the skill.

This skill is intended for Perl testing functionalities. Currently, the Japanese translation and content are under development, serving as a placeholder. Users should refer to the original English skill file for the core functionality and detailed implementation.

A comprehensive guide to integrating privacy protections into software architecture from the ground up. This skill ensures compliance with major global regulations like GDPR, CCPA, and LGPD by implementing core principles such as data minimization, purpose limitation, and default privacy settings. Essential for developers building any application that handles personal user data.

This skill transforms a refined research proposal or method idea into a detailed, structured, and claim-driven experiment roadmap. It helps users determine exactly which experiments to run, in what order, and what evidence is needed to support the core claims of a research paper, ensuring focus on novelty, simplicity, and genuine contribution.

This skill automates the process of vulnerability prioritization by querying the FIRST Exploit Prediction Scoring System (EPSS) API. It calculates the real-world probability of a CVE being exploited within 30 days, providing a crucial risk metric that surpasses traditional CVSS severity scoring. Use it for risk-based vulnerability management, allowing security teams to efficiently triage and remediate the most actively threatened vulnerabilities first.

This file serves as the dedicated translation resource for the MCP Server Patterns library. It is used to localize key strings and texts to ensure accurate user experience across different languages. Developers should refer to the original skill file for the core English content.

This skill transforms vague or fuzzy research directions into highly concrete, elegant, and academically rigorous proposals. It operates through multi-phase, iterative refinement, anchoring the process to the core problem while ensuring the proposed method is minimal, cutting-edge, and ready for publication or implementation.

This comprehensive pipeline guides users from a vague research concept to a fully structured, testable academic proposal. It first refines the core methodology (research-refine) to establish a stable thesis, and then generates a detailed, claim-driven experiment roadmap (experiment-plan). This end-to-end workflow ensures that the final academic output is both elegant and empirically validated.

Astro is a modern web framework designed specifically for building high-performance, content-heavy websites like blogs, documentation sites, and portfolios. Its core innovation is the Islands Architecture, which ships zero JavaScript by default, drastically improving performance and Core Web Vitals. It supports multi-framework components (React, Vue, Svelte) in a single project, making it ideal for content developers prioritizing speed and flexibility.

A comprehensive tool for establishing performance baselines across multiple dimensions. It measures Core Web Vitals (LCP, CLS, INP), API latency (p50, p95, p99), and development build efficiency. Essential for detecting performance regressions before merging code, ensuring stability in CI/CD pipelines, and comparing alternative stack implementations.