Skill UI

Performs a GEO-focused technical SEO audit covering crawlability, indexability, security, performance, SSR, and AI crawler access to keep both search engines and AI agents from losing visibility.

LEX is a structured truth engine designed to eliminate legal hallucinations by grounding AI agents in verified government references and legislation across 29+ jurisdictions (including US, EU, and CA). It provides deterministic context for comparing legal requirements, drafting compliant business, and employment documents, ensuring high jurisdictional accuracy.

Validates SKILL.md files against the agentskills specification and Anthropic best practices, catching structure, semantic, naming, and quality issues in a single read-only pass before publishing or debugging skills.

Manages and coordinates complex workflows involving multiple AI agents and tasks. It efficiently distributes work across multiple workers, handles runtime errors, and intelligently merges disparate results into a unified output, making it ideal for large-scale, distributed AI computations.

Helps founders, RevOps, and GTM engineers turn manual revenue processes into reliable, observable automation by mapping tech stacks, designing workflow architectures, and orchestrating AI agents across platforms like n8n, Make, and Zapier.

Runs AgentHub's init→baseline→spawn→eval→merge workflow in one command, letting teams define tasks, agents, metrics, and templates to automate evaluation and merging the winning agent.

RecallMax dramatically enhances AI agent memory capabilities by cleanly injecting massive external contexts (500K-1M tokens) without hallucination drift. It automatically summarizes lengthy conversations, preserving tone, intent, and key facts. Furthermore, it compresses multi-turn interaction histories into high-density token sequences, ensuring agents maintain perfect recall across complex and long-running sessions.

An advanced reliability wrapper for AI agents that monitors, manages, and recovers from tool call failures. It automatically handles common issues such as truncated JSON responses, API timeouts, rate limits, and mid-chain process breakdowns. By implementing sophisticated failure classification, checkpointing, and learning mechanisms, Guardian ensures complex, multi-step agent workflows remain stable and resilient.

A comprehensive design specification detailing 98 rules for building Command Line Interface (CLI) tools that are safe, reliable, and easily consumable by AI agents. It covers structured JSON output formats, standardized error handling (to stderr), robust input contracts, safety guardrails (e.g., preventing path traversal), and tiered compliance levels (Agent-Friendly, Agent-Ready, Agent-Native) for seamless integration into AI workflows.

Provides step-by-step guidance for installing, configuring, and operating the Havoc post-exploitation C2 framework with teamserver, HTTPS listeners, redirectors, and Demon agents suited for authorized red team engagements.

A robust framework for orchestrating complex, multi-step coding tasks using multiple AI agents. It functions by first planning the entire project into a mission dependency graph (DAG), then dispatching specialized agents to isolated Git worktrees for parallel development. The system automatically monitors progress, handles merges, and generates structured, comprehensive reports detailing changes, completed tasks, and next steps.

Step-by-step guidance for deploying Palo Alto Networks Prisma Access to deliver SASE zero trust access via GlobalProtect agents, ZTNA Connectors, granular security policies, and Strata Cloud Manager orchestration for remote and branch users.