Skill UI

A professional and versatile card template optimized for sharing quotes, insights, or data points on social media like Twitter/X. Designed with a 16:9 aspect ratio, it features a central hero quote, author details, and subtle background textures (grid/noise). It ensures high visual impact and professional presentation, helping your content stand out in a crowded feed.

A sophisticated deck template mimicking the look of printed ink on e-paper. Designed for deep narrative storytelling, academic sharing, or personal essays, this template rejects modern digital aesthetics. It features 10 versatile, magazine-style layouts and 5 curated, monochromatic color palettes (e.g., Kraft Paper, Indigo Porcelain), ensuring a timeless, print-like feel for professional presentations.

A specialized presentation deck template designed for internal engineering talks, technical conferences, and deep-dive knowledge sharing. It features a professional GitHub-dark theme, JetBrains Mono coding font, and a structured layout including Cover, Agenda, main content slides (with code blocks), demo slides (terminal screenshots), and Q&A sections.

This aesthetic deck is perfect for personal narratives, journaling, or lifestyle sharing. It features a soft pastel macaron color scheme, creamy backgrounds, and gentle light blobs, making it ideal for presenting emotional stories, personal growth tracks, or slow-life concepts in a visually dreamy way.

This tool generates hyper-realistic X (Twitter) post cards, accurately simulating the platform's UI, including user profiles, content, and dynamic interaction metrics (likes, reposts, views). It is ideal for content creators and marketers needing high-fidelity social media assets for video overlays, knowledge card sharing, or professional promotional materials.

This skill automates the commit and push process for local skill changes. It should be used after a skill has been fully validated and updated, ensuring the canonical copy of the skill is published to the configured remote GitHub repository. This is essential for sharing or finalizing skill updates.

This tool enables the creation and management of Dynamic Agentic Architecture (DAA) agents. Unlike static agents, DAA agents possess the ability to learn, adapt their internal behavior based on real-time performance metrics, and continuously evolve through interactions. It facilitates knowledge sharing among multiple agents, ensuring systemic, continuous improvement in complex AI systems. Ideal for scenarios requiring high adaptability and evolving intelligence.

This skill generates an enterprise-grade threat model report using the `harness threat-model` command. It categorizes threats across the MCP surface, providing a detailed report including the overall worst severity (clean, low, medium, high) and specific findings. Ideal for pre-launch security reviews and periodic audits when sharing findings with an InfoSec team.

This skill facilitates the crucial process of sharing learned intelligent patterns across isolated projects or machines using the InterPlanetary File System (IPFS). It allows users to publish a project's accumulated knowledge base to a decentralized network and later fetch, apply, and merge these patterns into new or existing projects. This is invaluable for bootstrapping new applications with prior knowledge or consolidating learnings across a large monorepo.

This tool suite provides functionality to interact with a community gallery for WebAssembly (WASM) agents. Users can browse available agents, search for specific functionalities, install pre-built agents, publish their own creations, and export agents for packaging. It streamlines the process of sharing and utilizing modular WASM components.

The Unified Memory system provides a durable, inspectable context layer for sharing state and handoffs between multiple autonomous agents (harnesses) like Claude, Codex, and Hermes. It allows agents to save work state, transfer context, resume tasks, and search shared project knowledge across different scopes (project, team, user).

A comprehensive guide for authors submitting to the American Journal of Sociology (AJS). It outlines best practices for data documentation, ensuring research provenance, and ethically sharing findings in both quantitative and ethnographic contexts. It emphasizes creating a thorough, checkable evidentiary trail appropriate to the claim, while clarifying AJS's non-mandatory policy on replication deposits and adherence to confidentiality standards.