Agent Skills Hub

massgen-config-creator

Guide for creating properly structured YAML configuration files for MassGen. Use this when creating new configs for examples, case studies, testing, or feature demonstrations.

data-viz-plots

Create publication-quality plots and visualizations using matplotlib and seaborn. Works locally with any LLM.

enterprise-agent-builder

Architects enterprise AI agents from structured specs, generating production-ready code, data flow diagrams, and platform-specific logic for ServiceNow, Salesforce, and Snowflake.

mod-actions

A comprehensive moderation toolkit for Civitai, providing automated user management, strike systems, image review, content regulation, and CSAM reporting via tRPC API.

openai-agents-sdk

Build AI agents with the OpenAI Agents SDK for Python. Supports multi-agent handoffs, function tools, stateful sessions, streaming, and Azure OpenAI integration via LiteLLM.

template-generator

Generate structured configuration files and formatted output by injecting user data into pre-defined project templates.

holistic-testing-pact

Apply Holistic Testing with PACT (Proactive, Autonomous, Collaborative, Targeted) principles to build quality into team culture and test strategies for modern software systems.

webf-quickstart

Get started with WebF development: setup WebF Go, initialize Vite-based web projects (React/Vue/Svelte), and preview apps in a W3C-compliant native runtime.

Extract structured data from unstructured files (PDF, PPTX, DOCX...)

Implement LlamaExtract for robust structured data extraction from PDF, DOCX, and PPTX files using Pydantic schemas.

agentdb-state-manager

Persistent state management and workflow analytics using DuckDB for task dependency tracking, historical metrics, and context checkpointing.

skill-architect

Expert consultant for designing and building high-quality, consistent AI agent skills. Guides you through discovery, architecture, and creation phases to ensure reliable, composable, and efficient skill delivery.

hive-mind-advanced

Queen-led multi-agent orchestration for Claude Code, featuring Byzantine consensus, persistent collective memory, and adaptive task distribution for complex software projects.