By mrgoonie
Invoke OpenRouter models via battle-tested CLI for chat completions, embeddings, reranking, video generation, API key setup, model browsing, and credits checks from shell scripts and agents, delivering stable JSON/NDJSON output, cascading configs, and reliable exit codes for production workflows.
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Platform integration skills for Shopify, Bunny.net (CDN, Storage, Stream, DNS, Edge Scripting, Shield, Containers), payment providers (SePay, Polar, Stripe, Paddle, Creem), and MCP server management
Generate images and videos with Leonardo.Ai through the leonardo CLI. Includes guides for all model families and recipe references.
npx claudepluginhub mrgoonie/openrouter-cli --plugin openrouterOpenRouter SDK plugin - unified interface for 500+ LLM models with intelligent routing, cost optimization, and framework integrations (Vercel AI SDK, LangChain, OpenAI SDK, PydanticAI)
Flagship+ skill pack for OpenRouter - 30 skills for multi-model routing, fallbacks, and LLM gateway mastery
Run any model with an Anthropic- or OpenAI-compatible API (e.g. DeepSeek, GLM, Kimi, Qwen, MiniMax) — even your Codex subscription — as real Claude Code workflows, agent-team teammates, or one-shot subagents, driven exactly like native ones. Your main session's own auth is untouched (OAuth subscription or API key, either works); API-key providers bill the provider key via apiKeyHelper, while a Codex subscription bills through a local OAuth daemon — each worker receives its credential on demand, never through its env or argv. Requires the `cc-fleet` binary on PATH, installed separately.
Smart LLM routing with Claude subscription monitoring, complexity-first model selection, and 20+ AI providers
Teach Claude to detect, wire, and troubleshoot FreeRide — a local OpenAI-compatible gateway routing across free-tier providers (OpenRouter, Groq, NVIDIA NIM, Cloudflare Workers AI, HuggingFace).
When calling LLM APIs from Python code. When connecting to llamafile or local LLM servers. When switching between OpenAI/Anthropic/local providers. When implementing retry/fallback logic for LLM calls. When code imports litellm or uses completion() patterns.