Skill UI

This skill transforms generated wiki Markdown files into a polished, professional VitePress static documentation site. It automatically integrates a dark theme, enhances interactivity, and supports complex Mermaid diagrams with careful CSS and JavaScript fixes. Use this when the goal is to build a fully browsable, deployed documentation website from raw wiki content.

Automates detection and deep exploratory analysis across 200+ scientific data formats, assessing quality, extracting metadata, and recommending visualizations while generating markdown reports that guide downstream workflows and highlight structure and distributions.

Conduct rigorous, multi-database literature reviews with systematic workflows, verified citations in styles like APA or Nature, and AI-enhanced schematics for publication-ready markdown and PDF outputs in biomedical and technical domains.

Defines a Markdown/Mermaid-first documentation skill for scientific and technical writing, providing diagram standards, 24 reference types, and templates so every report, README, or analysis stays text-first, versionable, and visualization-ready.

MarkItDown converts PDFs, DOCX, PPTX, XLSX, HTML, JSON, XML, archives, YouTube links, images via OCR, and audio via transcription into clean Markdown, providing token-efficient text ready for LLMs and documentation workflows.

A comprehensive security scanner designed to audit AI agent skills before deployment. It analyzes source code (Python, Bash, JS), detects critical vulnerabilities like command injection, network exfiltration, and unsafe deserialization. Furthermore, it scans markdown files for prompt injection attacks, and assesses dependency supply chain risks, providing a clear PASS/WARN/FAIL verdict and remediation guidance.

A rigorous, security-focused code review process designed for Pull Requests (PRs), commits, and diffs. It moves beyond general reviews by focusing intensely on high-risk areas such as authentication, cryptography, external calls, and value transfer. The methodology is evidence-based, requiring detailed attack scenario modeling and generating comprehensive, auditable markdown reports to identify overlooked vulnerabilities and regressions.

This skill provides comprehensive tools for AI engineers and researchers to publish, manage, and link research papers directly on the Hugging Face Hub. It supports creating dedicated paper pages, linking papers to corresponding models and datasets, claiming authorship, and generating professional, markdown-based research articles with LaTeX support. Use it to streamline the entire academic publishing workflow from initial draft to final publication.

Automatically gather Playwright test outcomes, highlight failures/flakies, and deliver summaries (Markdown, Slack, TestRail, HTML) aligned with existing workflows for quick triage.

This module provides a centralized interface for the AgentHub message board. It allows multiple AI agents and the coordinator to communicate, track tasks, and log results through structured markdown posts across dedicated channels (Dispatch, Progress, Results). It is essential for monitoring complex multi-agent workflows and ensuring transparent collaboration and auditing.

Auto-generate professional GEO service proposals from audit data, translating findings into business risks, tiered recommendations, pricing, timeline, and PDF-ready documentation for prospect follow-up.

Implements Manus-style file-based planning to organize complex tasks, enforcing persistent markdown plan/findings/progress files, enforcing read-before-decide and write-after-action rules, and enabling session recovery after /clear.