Agent skills for ChatGPT

Build a real-time support chat system with a floating widget for users and an admin dashboard for support staff.

Report the embedded release marker when testing public Skill installation or marketplace updates.

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

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…

Develop and contribute to the PinchTab project.

Deconstructs academic papers into simplified summaries and visualizes cognitive insights using ASCII art and personal knowledge baselines.

Converts structured outlines into high-impact, slogan-style HTML presentations with ultra-bold typography and minimalist aesthetics.

Transforms complex articles, papers, and books into sharp, logical Q&A chains that reveal an author's core argument skeleton.

Runs LLM inference on CPU, Apple Silicon, and consumer GPUs without NVIDIA hardware.

Meta's 7-8B specialized moderation model for LLM input/output filtering. 6 safety categories - violence/hate, sexual content, weapons…

Use when ANY runtime debugging is needed — setting breakpoints, inspecting variables, evaluating expressions, analyzing threads, or…

LLM-based text classification: codebook, validation, agreement statistics.

LLM-based zero-shot and few-shot classification for flexible intent detection

Use proactively whenever LLM API costs come up -- or should.

Run any question, idea, or decision through a council of 5 AI advisors who independently analyze it, peer-review each other anonymously…

Run multi-LLM council for adversarial debate and cross-validation.

Master comprehensive evaluation strategies for LLM applications, from automated metrics to human evaluation and A/B testing.

Bootstrap a reproducible LLM Observability experiment through the Python ddtrace SDK or the Node dd-trace SDK.

LLM Operations -- RAG, embeddings, vector databases, fine-tuning, advanced prompt engineering, LLM costs, quality evals and…