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Found 1,282 Skills
INVOKE THIS SKILL when adding Arize AX tracing to an application. Follow the Agent-Assisted Tracing two-phase flow: analyze the codebase (read-only), then implement instrumentation after user confirmation. When the app uses LLM tool/function calling, add manual CHAIN + TOOL spans so traces show each tool's input and output. Leverages https://arize.com/docs/ax/alyx/tracing-assistant and https://arize.com/docs/PROMPT.md.
Use this skill when optimizing for AI-powered search engines and generative search results - Google AI Overviews, ChatGPT Search (SearchGPT), Perplexity, Microsoft Copilot Search, and other LLM-powered answer engines. Covers Generative Engine Optimization (GEO), citation signals for AI search, entity authority, LLMs.txt specification, and LLM-friendliness patterns based on Princeton GEO research. Triggers on visibility in AI search, getting cited by LLMs, or adapting SEO for the AI search era.
Behavioral compliance testing for any CLAUDE.md or agent definition file. Auto-generates test scenarios from your rules, runs them via LLM-as-judge scoring, and reports compliance. Optionally improves failing rules via automated mutation loop.
Build generative UI apps with OpenUI and OpenUI Lang — the token-efficient open standard for LLM-generated interfaces. Use when mentioning OpenUI, @openuidev, generative UI, streaming UI from LLMs, component libraries for AI, or replacing json-render/A2UI. Covers scaffolding, defineComponent, system prompts, the Renderer, and debugging OpenUI Lang output.
CrewAI agent design and configuration. Use when creating, configuring, or debugging crewAI agents — choosing role/goal/backstory, selecting LLMs, assigning tools, tuning max_iter/max_rpm/max_execution_time, enabling planning/code execution/delegation, setting up knowledge sources, using guardrails, or configuring agents in YAML vs code.
One-click model liberation toolkit for removing refusal behaviors from LLMs via surgical abliteration techniques
Convert files, URLs, and media to markdown using the markit-ai CLI and SDK with pluggable converters and LLM support.
MacOS voice input tool with local/cloud ASR engines, LLM text optimization, and fully local storage built in Swift
PyTorch implementation of TurboQuant for LLM KV cache compression using two-stage vector quantization (random rotation + Lloyd-Max + QJL residual correction).
Fetch and compile arXiv papers on LLMs, autonomous agents, and AI infrastructure into scored, grouped research digests. Stores digests at ~/.aibtc/arxiv-research/digests/. No API key required.
Fine-tune LLMs using the Tinker API. Covers supervised fine-tuning, reinforcement learning, LoRA training, vision-language models, and both high-level Cookbook patterns and low-level API usage.
LLM-assisted human-in-the-loop review. Make sense of a change, focus attention where it matters, test. Use when the user says "checkpoint", "human review", or "walk me through this change".