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Found 102 Skills
Configure LM Studio as embedding provider for GrepAI. Use this skill for local embeddings with a GUI interface.
NEAR AI agent development and integration. Use when building AI agents on NEAR, integrating AI models, creating agent workflows, or implementing AI-powered dApps on NEAR Protocol.
Add, update, or remove text/image/video models. Handles any provider.
Ollama API Documentation
Query OpenRouter for available AI models, pricing, capabilities, throughput, and provider performance. Use when the user asks about available OpenRouter models, model pricing, model context lengths, model capabilities, provider latency or uptime, throughput limits, supported parameters, wants to search/filter/compare models, or find the fastest provider for a model.
Google Gemini API with @google/genai SDK. Use for multimodal AI, thinking mode, function calling, or encountering SDK deprecation warnings, context errors, multimodal format errors.
Uses a local model to describe something about an image
AI model safety scanner built on NVIDIA garak for testing LLMs against 179 security probes across 35 vulnerability families
Google Gemini integration. Manage Users, Conversations. Use when the user wants to interact with Google Gemini data.
Find AI models on Replicate using search and curated collections.
Cross-model benchmark for gstack skills. Runs the same prompt through Claude, GPT (via Codex CLI), and Gemini side-by-side — compares latency, tokens, cost, and optionally quality via LLM judge. Answers "which model is actually best for this skill?" with data instead of vibes. Separate from /benchmark, which measures web page performance. Use when: "benchmark models", "compare models", "which model is best for X", "cross-model comparison", "model shootout". (gstack) Voice triggers (speech-to-text aliases): "compare models", "model shootout", "which model is best".
Train custom AI models (LoRA) on fal.ai for personalized image generation tailored to a brand, character, or style.