Agent Skills Hub

vvm

VVM (Vibe Virtual Machine) is a language for agentic programs where the LLM acts as the runtime. Orchestrate multi-agent workflows, manage state, and build resilient AI pipelines.

debug-firewall

Debug the AWF (Agentic Workflow Firewall) by inspecting containers, analyzing Squid logs, checking iptables, and troubleshooting network or domain access issues in isolated sandboxes.

mcp-gateway-patterns

MCP Gateway design patterns for managing Agent Gateway, Subprocess, and Daemon isolation strategies to optimize context token usage and system performance.

project-migrate

Intelligently migrate existing brownfield projects to the AgenticDev structure using AI-powered analysis to reorganize documentation, generate rich frontmatter, and preserve git history.

librarian

Fetch, index, and search developer documentation from GitHub and websites to provide AI agents with accurate, grounded, and version-specific code context.

openai-agent-sdk-skill

Build AI agents, multi-agent systems, and workflows using the OpenAI Agents SDK for TypeScript/JavaScript. Supports tools, handoffs, guardrails, MCP, and realtime voice.

land

Automated PR lifecycle management: monitors conflicts, resolves CI failures, handles review feedback, and executes squash-merges for safe code integration.

moai-foundation-core

Foundational architectural principles for MoAI-ADK, featuring TRUST 5, SPEC-First TDD, delegation patterns, and token-efficient agent orchestration workflows.

langgraph-workflows

Master multi-agent orchestration with LangGraph. Build stateful, fault-tolerant AI workflows using supervisor-worker patterns, conditional routing, and advanced state management.

libragent-quality

Comprehensive code quality validation for LibrAgent, covering TypeScript frontend and Rust/Tauri backend via automated linting, formatting, type checking, and build verification.

pentest-osint-recon

Automated OSINT reconnaissance agent for mapping external attack surfaces, identifying assets, and uncovering security vulnerabilities.

markdown-token-optimizer

Analyzes markdown files to identify token-wasting patterns, providing actionable suggestions to optimize documentation for LLM consumption and token efficiency.