Loading...
Loading...
Found 33 Skills
Local LLM inference with Ollama. Use when setting up local models for development, CI pipelines, or cost reduction. Covers model selection, LangChain integration, and performance tuning.
Route AI coding queries to local LLMs in air-gapped networks. Integrates Serena MCP for semantic code understanding. Use when working offline, with local models (Ollama, LM Studio, Jan, OpenWebUI), or in secure/closed environments. Triggers on local LLM, Ollama, LM Studio, Jan, air-gapped, offline AI, Serena, local inference, closed network, model routing, defense network, secure coding.
Эксперт AutoML. Используй для automated machine learning, hyperparameter tuning и model selection.
Vision, audio, and multimodal LLM integration patterns. Use when processing images, transcribing audio, generating speech, or building multimodal AI pipelines.
Image prompt templates, model selection guidance, and anti-generic patterns for generating visual assets. Use when the user needs AI-generated images for landing pages, marketing, or products. Covers hero images, feature illustrations, OG cards, icons, and backgrounds.
Optimize token usage when delegating to Gemini CLI. Covers token caching, batch queries, model selection (Flash vs Pro), and cost tracking. Use when planning bulk Gemini operations.
Monetization strategy for iOS/macOS apps. Covers readiness assessment, pricing model selection, tier structuring, free trial strategy, and implementation guidance. Use when deciding what to charge, how to price, or planning monetization end-to-end.
Process this skill enables AI assistant to forecast future values based on historical time series data. it analyzes time-dependent data to identify trends, seasonality, and other patterns. use this skill when the user asks to predict future values of a time ser... Use when appropriate context detected. Trigger with relevant phrases based on skill purpose.
Control and operate Opencode via slash commands. Use this skill to manage sessions, select models, switch agents (plan/build), and coordinate coding through Opencode.
Upscale and enhance image resolution using AI. Use when the user requests "Upscale image", "Enhance resolution", "Make image bigger", "Increase quality", or similar upscaling tasks.
Comprehensive guide for developing Letta agents, including architecture selection, memory design, model selection, and tool configuration. Use when building or troubleshooting Letta agents.
Optimizing vector embeddings for RAG systems through model selection, chunking strategies, caching, and performance tuning. Use when building semantic search, RAG pipelines, or document retrieval systems that require cost-effective, high-quality embeddings.