Skill UI

This deterministic sanitizer prepares LaTeX manuscripts for publication gates. It performs three key repairs: normalizing complex punctuation to ASCII safe equivalents, replacing unconfirmed forecast magnitudes with 'TBD' placeholders, and removing redundant figure/table placeholder commands. It ensures the manuscript is structurally sound and ready for final quality review.

This internal, deterministic gate enforces academic rigor before manuscript compilation. It audits the input, rejecting unsupported empirical claims, missing citation verdicts, or concrete outcome numbers that lack user evidence. It ensures that generated scientific papers only present validated results, blocking unsupported quantitative or qualitative assertions.

A comprehensive toolkit designed for reading, reviewing, and programmatically creating high-fidelity PDF documents. It supports content extraction from existing PDFs, generating professionally formatted reports, and validating visual quality through rendering to PNG images. Ideal for tasks requiring precise typography, layout integrity, and polished final deliverables.

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 generates high-quality, styled code screenshots by calling the ray.tinte.dev API. It allows users to convert raw code snippets into professional PNG images, supporting multiple programming languages (e.g., Python, JavaScript, TypeScript), customizable themes, and various styling parameters like font size and padding. Use this when the user explicitly requests code images, code snippets as pictures, or mentions 'ray' to visualize code.

This advanced skill provides systematic, adversarial verification for AI-generated legal documents. It rigorously checks factual accuracy, legal citations, numerical data, and source authenticity against authoritative databases. Use this when you need to perform red-teaming, fact-check, or quality-control complex legal analyses, compliance reports, or regulatory summaries before any external distribution.

This internal deterministic quality gate is used before meta-short-drama final publication. It rigorously verifies the media content's integrity by checking real-provider image/video receipts, confirming paid submission dispositions, and utilizing ffprobe to validate decodability and expected final durations. The tool is designed to sanitize all sensitive data, ensuring only bounded, auditable information is passed to the next stage.

skill-doctor grades the performance and quality of an AI agent setup using real, local conversation history (e.g., Claude Code/Codex sessions). It scores skills against defined rubrics for efficiency and code quality, drafts evidence-backed suggestions for improvement, and generates a comprehensive, shareable local report. All processing is strictly local and private.

This tool guides the analysis of work sessions by detecting user feedback (corrections, successes, edge cases). It evaluates these signals against quality criteria (Complete, Precise, Atomic, Stable) to propose structured improvements, update skill documentation (SKILL.md), and maintain a changelog.

Automates the conversion of visual designs from Stitch into high-quality, modular React and Vite components. This skill ensures strict adherence to modern architectural standards, including logic isolation via custom hooks, data decoupling, and robust type safety using TypeScript. It manages complex workflows like network fetching, style guide synchronization, and multi-phase validation to generate production-ready frontend code.

A comprehensive playbook for building visual novels, covering core components like branching scripts, character presentation, backgrounds, and choice mechanics. It details necessary quality-of-life features such as save-anywhere, backlog, and auto-advance, ensuring a rich, engaging, and readable story experience.

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.