Skill UI

Utilize Velociraptor, an advanced open-source platform, to collect, query, and monitor forensic artifacts across diverse endpoints (Windows, Linux, macOS). This skill enables incident response teams to perform large-scale, rapid digital forensic investigations by collecting critical data such as event logs, registry entries, prefetch files, and network metadata using VQL queries.

Zeek is a powerful, open-source network analysis framework that functions as a passive security monitor. It generates highly detailed, structured logs (e.g., HTTP, DNS, TLS) from raw network traffic, allowing for deep metadata extraction. This skill guides users through deploying Zeek, writing custom detection scripts, and integrating the resulting rich security logs with SIEM platforms for advanced threat detection and forensic investigations.

This skill provides comprehensive analysis and structured data extraction for academic research papers hosted on Hugging Face and arXiv. It can read paper content in markdown format, retrieve key metadata (authors, abstracts, GitHub repos), and identify linked assets such as associated models, datasets, and Spaces. Use this when the user provides a Hugging Face or arXiv URL, or explicitly requests a summary or explanation of an AI research topic.

A specialized tool for finding peer-reviewed academic papers from major venues like IEEE, ACM, and Springer. Unlike preprint services (e.g., arXiv), this skill provides published literature with citation counts, detailed venue metadata, and a TLDR summary, ensuring access to verified research findings.

This skill analyzes accumulated usage logs from a complex research harness (ARIS) to propose structural optimizations. It identifies areas for improvement in SKILL scripts, default parameters, workflow ordering, and reviewer prompts. It is designed to automate the meta-level engineering process, ensuring that system efficiency is continuously improved based on real-world usage data.

This skill generates multiple optimized variants for title tags, meta descriptions, and social media sharing tags (OG/Twitter). It provides three distinct styles (Benefit Lead, Question Hook, Social Proof) for each type, allowing users to A/B test copy to maximize click-through rate (CTR). Ideal for refining landing pages, blog posts, or any content requiring robust search engine optimization (SEO) and social media presence.

This entry highlights a skill definition that lacks required metadata such as name and description, making it unusable until the missing information is provided.

A placeholder skill entry that explains the lack of a YAML frontmatter, useful for tracking or validation workflows that detect missing metadata.

Detects when a skill's frontmatter block lacks its closing delimiter so editors can fix the metadata formatting before parsing fails.

Provides a well-structured skill template with metadata for `lark-cli`, helping developers verify formatting and readiness before deployment.

Complex Skill CLI wraps multi-line metadata and coordinates lark-cli plus Node.js binaries to expose a predictable helper for complex automation or deployment tasks within CLI-driven workflows.

Use the gws-forms skill to list available Google Forms, fetch their metadata, and retrieve response data from the CLI for quick review and follow-up.