Skill UI

This skill executes a comprehensive, three-stage verification pipeline to rigorously evaluate any given code artifact or execution session. The process starts with mechanical checks (linting, building, unit testing), progresses to semantic evaluation (checking against acceptance criteria and goal alignment), and optionally concludes with a Multi-Model Consensus vote for maximum reliability. Ideal for CI/CD pipelines and critical code reviews.

An expert assistant dedicated to ensuring compliance with GDPR and global data protection regulations. This skill covers auditing code and systems for violations, drafting compliant legal documents (like privacy policies and DPAs), answering complex compliance questions with authoritative GDPR article citations, and reviewing data flows for PII handling practices. It addresses both EU and UK GDPR requirements.

Hivemind is an advanced orchestration layer designed to manage complex tasks using a parallel swarm of external, low-cost workers. It simulates a structured team workflow (scout, coder, tester) to decompose large problems, execute subtasks in isolated worktrees, synthesize aggregated results, and perform consensus reviews. This dramatically reduces token costs and enhances reliability for large-scale coding, research, and testing tasks.

A guided tool to manage and progress through a structured, multi-module technical learning curriculum. It tracks prerequisites, requires recording concrete evidence artifacts for completion, and implements spaced repetition reviews to ensure long-term knowledge retention in coding practices.

This skill systematically audits Playwright End-to-End (E2E) test files. It checks for common anti-patterns, adherence to best practices, and identifies coverage gaps across the entire test suite. It provides a detailed score (1-10) and generates actionable reports, including suggested code fixes, significantly improving test reliability and maintainability.

This skill analyzes code for language and framework-specific security best practices. It is designed to help users write secure-by-default code, passively detect major vulnerabilities, or generate comprehensive, prioritized vulnerability reports. Supports languages including Python, JavaScript/TypeScript, and Go, ensuring robust security standards throughout the development lifecycle.

Tinte is an agent-native infrastructure designed for generating, compiling, and managing consistent design systems from a single source of truth. It maintains a graph of 13 semantic OKLCH color tokens, compiling them into multiple formats including shadcn/ui presets, VS Code themes, and terminal configurations. Use it to ensure brand consistency, extract themes from images (via AI), and generate code previews with professional styling.

This skill provides a comprehensive workflow for creating professional and standardized pull requests (PRs). It enforces critical rules, including mandatory issue linkage to approved items, strict branch naming conventions (e.g., feat/description), adherence to Conventional Commits, and the completion of detailed PR body templates. Use this guide when submitting any code changes to ensure high quality, traceability, and seamless code review.

This skill automatically analyzes overly large Pull Requests (over 400 lines) and intelligently splits them into a series of smaller, manageable, and logically chained PRs (Stacked or Feature Branch Chain). It ensures that each review slice remains focused, actionable, and can be reviewed within a reasonable time frame (≤60 minutes), significantly improving code review efficiency and maintainability.

A comprehensive guide and set of rules for writing effective, warm, and actionable comments across various development platforms. It helps users structure feedback for GitHub PRs, issue trackers, or Slack messages, ensuring the tone is consistently thoughtful, direct, and focused on clear next steps, rather than simply listing observations.

This skill analyzes excessively large Pull Requests (PRs) that exceed established line budgets (e.g., 400 lines). It automatically splits these massive changes into smaller, focused, and sequential PRs using advanced chaining or stacking strategies. This process is crucial for protecting reviewer focus, ensuring reviews can be completed within a manageable time budget (e.g., ≤ 60 minutes), and maintaining high code quality during complex feature integration.

A rigorous, standalone tool designed for explicit, blind, and adversarial code review. It executes the code target through two parallel, independent judges (Judge A and Judge B) with strict rules and limited fix rounds. This process ensures maximum scrutiny, providing a definitive, highly corroborated verdict (APPROVED or ESCALATED) that replaces standard review methods.