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Found 98 Skills
SerpApi search engine results API via curl. Use this skill to scrape Google, Bing, YouTube, and other search engines.
Local text-to-speech via sherpa-onnx (offline, no cloud)
Sell your home quickly with Offerpad's iBuyer service.
SmarterPay integration. Manage data, records, and automate workflows. Use when the user wants to interact with SmarterPay data.
Find certified shops and get fair price estimates for car repairs.
Agente que simula Andrej Karpathy — ex-Director of AI da Tesla, co-fundador da OpenAI, fundador da Eureka Labs, e o maior educador de deep learning do mundo.
Scaffolds a personal LLM Wiki from scratch — the Karpathy pattern of incrementally building a persistent, interlinked markdown knowledge base maintained by LLMs. Generates directory structure, schema file, index, log, and workflow conventions. Use when user says "create wiki", "new wiki", "bootstrap wiki", "llm wiki", "knowledge base", "start a wiki", "build a wiki", or wants to set up a structured markdown knowledge base for any domain.
Hyperparameter Tuner - Auto-activating skill for ML Training. Triggers on: hyperparameter tuner, hyperparameter tuner Part of the ML Training skill category.
Fetches Andrej Karpathy's curated RSS feed, reads ALL original articles, and generates a themed daily briefing document with citation links. This skill should be used when the user asks to generate a Karpathy RSS daily report, fetch Karpathy's curated RSS updates, or create an AI/tech daily briefing based on Karpathy's sources. Trigger phrases include "Karpathy Daily Report", "Karpathy RSS", "Generate Daily Report", "RSS Briefing", "Karpathy Daily".
Optimize machine learning model hyperparameters using grid search, random search, or Bayesian optimization. Finds best parameter configurations to maximize performance. Use when asked to "tune hyperparameters" or "optimize model". Trigger with relevant phrases based on skill purpose.
Run and interact with KarpathyTalk, an open markdown-based developer social network with GitHub auth, SQLite, and an LLM-friendly JSON/markdown API.
Behavioral guidelines to reduce common LLM coding mistakes. Use when writing, reviewing, or refactoring code to avoid overcomplication, make surgical changes, surface assumptions, and define verifiable success criteria.