Skill UI

A robust, production-tested pattern for coordinating multiple specialized AI agents. The orchestrator decomposes complex tasks, routes them to the most suitable specialist, prevents redundant or conflicting work (anti-duplication), and enforces mandatory quality gates (e.g., running tests, checking file diffs) to verify results before marking a task as complete. It also includes heartbeat monitoring for task progress.

Design secure multi-tenant LLM hosting platforms on shared GPU inference infrastructure, covering tenant isolation, per-tenant quotas and rate limits, billing attribution, noisy-neighbor protection, and per-tenant policy controls for vLLM on Kubernetes.

This skill enables AI-powered PowerPoint generation by analyzing documents and incorporating styled images. It is designed for users needing automated presentation creation with visual enhancements based on source material. Suitable for quick prototyping and content summarization into slides efficiently.

Unified LLM inference layer built into Neon branches: one credential and one OpenAI-compatible API for frontier and open-source models from seven providers. Switch models without rewiring, wire it into OpenAI/Anthropic SDKs, and keep AI requests branch-scoped.

Nika is an open-source Rust engine that captures repeatable AI tasks as checkable YAML workflow files. It audits workflows before token spending, enforces strict cost budgets, and executes against local or cloud providers. Ideal for daily digests, ETL, and multi-step pipelines requiring audit trails and deterministic execution without autonomous coding capabilities.

A remote MCP server designed for AI agents to dynamically discover, inspect, and verify external tools, APIs, and services. It allows agents to search a curated index of AI-ready websites, check for machine-readable endpoints (like OpenAPI or MCP), and confirm if an endpoint responds correctly to JSON-RPC, enabling robust, dynamic agent workflow building.

Plans first, then orchestrates dynamic multi-agent workflows with adversarial verification via a local odw daemon or native fallback. Supports 16-100 parallel agents, sandboxed scripts, SQLite checkpoints, and crash-resume for tasks spanning many files or items.

Orchestrate bounded coding tasks by delegating them to the Oh My Pi (omp) CLI implementer, then review the diff and land the changes yourself. Covers brief writing, model selection, dispatch, and polling.

Open Dynamic Workflows (ODW) is an advanced, open-source engine designed to manage complex coding tasks using multiple AI agents. It operates in three stages: planning the task into parallel subtasks, orchestrating various coding agents (like Codex or Antigravity) to work concurrently, and finally, performing an adversarial verification pass to challenge and validate the combined output before merging. It supports multiple model providers and is ideal for structured, high-reliability software development.

Find, use, create, install, share, update, and migrate agent skills stored in OpenViking, including from Git or local folders, so they work across harnesses and machines.

Coordinate focused subagents on substantial work while maintaining non-overlapping ownership and integrating verified results. Ideal for large-scope tasks where parallel processing reduces elapsed time. Decompose tasks into distinct assignments, run scouts in parallel, assign distinct ownership, and synthesize outputs. Keep trivial work with the coordinator to avoid overhead.

Pilot Protocol provides AI agents with permanent network addresses, encrypted P2P messaging, and NAT traversal capabilities. It includes an installable app store for agent-native services. Use it for direct agent communication, stable addressing across clouds, and installing local capabilities without REST plumbing.