Agent skills for Codex CLI

Build voice AI agents with LiveKit Agents SDK.

Inspect LiveView socket assigns for memory bloat — missing temporary_assigns, unused assigns, unbounded lists needing streams, memory…

Build LiveView: async data (assign_async), PubSub (check connected?), phx-change events, form components/modals/uploads, streams for…

Use for Livewire security work. Covers what a public property publishes, snapshot serialization, #[Locked], the persistent middleware gap…

Maintains an implementation-agnostic, behavior-first functional blueprint to guide AI-driven refactoring and long-term project evolution.

Use when targeting Living Reviews in Relativity (LRR) or deciding whether an invited, continuously updated authoritative review in…

Entry point for deploying and managing apps on Lizard via the `lizard` CLI (npm `@lizard-build/cli`).

Analyzes articles to extract deep structural insights and cognitive collisions using an X-ray scanning methodology.

Transforms text and web content into high-quality visual PNGs using specialized design templates and artistic styles.

Simplifies complex academic papers into jargon-free, actionable insights using the Feynman technique and conversational analysis.

Synchronizes local Claude skills to GitHub with automatic Org-mode to Markdown conversion and documentation validation.

Deep-dive English word mastery tool. Deconstructs a single English word into core semantics and epiphany. Use when user asks to…

Expert guidance for fine-tuning LLMs with LLaMA-Factory - WebUI no-code, 100+ models, 2/3/4/5/6/8-bit QLoRA, multimodal support

Data framework for building LLM applications with RAG.

Complete LLDB command reference — variable inspection, breakpoints, threads, expression evaluation, process control, memory commands, and…

Use for authorized security assessment of LLM applications and AI agents, including prompt injection, tool abuse, RAG exposure, memory…

Configure RuVLLM local inference with model selection, MicroLoRA fine-tuning, and SONA adaptation

Poison the data an LLM application trusts — its RAG knowledge base, fine-tuning corpus, or ingestion pipeline — so that later answers…

Abuse an over-privileged LLM agent — excessive tools, permissions, or autonomy — to make it perform actions beyond its intended scope…

LLM integration patterns including API usage, streaming, function calling, RAG pipelines, and cost optimization

Harden an LLM application against sensitive-data leakage by filtering and redacting model output and constraining what reaches the context.