AI Skills for OpenAI API

Enables display of HTML content on OpenClaw-connected nodes, perfect for interactive demos and visualizations.

Creates unique lobster personas for OpenClaw AI Agents, generating character traits, rules, and visual prompts based on user preferences.

Enables high-throughput LLM serving with OpenAI API compatibility, optimizing inference latency and GPU memory usage.

Enables delegation of coding tasks to OpenAI Codex CLI for efficient feature development, refactoring, and PR reviews.

DSPy enables declarative programming for language models, optimizing prompts and building modular AI systems efficiently.

Facilitates remote AI agent pairing with browsers, enabling scoped access and seamless collaboration through HTTP requests.

Provides repo-specific guidance for managing cross-platform coding tasks and maintaining synchronization across multiple AI coding platforms.

Automates GitHub repository management with a structured 7-stage workflow for auditing, cleanup, and competitor analysis.

Enables the creation of type-safe AI agents in Python, ensuring structured outputs and seamless integration with various LLMs.

Extracts structured data from LLM responses using schema-constrained decoding for reliable JSON and typed objects.

This skill audits third-party AI agent skills for security risks, ensuring safe installations by detecting malicious patterns.

Builds a low-latency voice assistant inspired by Iron Man using Pipecat, Google Gemini, and OpenAI technologies.

MolyKit provides tools for building cross-platform AI chat interfaces, integrating OpenAI APIs, and managing async operations.

Facilitates structured evaluation management for Hugging Face model cards, enabling efficient data extraction and custom evaluations.

Provides a comprehensive reference for building real-time voice and multimodal AI applications using Daily, enabling seamless integration of AI services.

Generates artistic and photorealistic images using Stability AI's API, offering various modes for image creation and editing.

Designs advanced LLM applications using LangChain and LangGraph for AI agents, memory management, and tool integration.

Guides users in selecting and optimizing embedding models for semantic search and RAG applications, enhancing model performance and quality.

Provides authoritative documentation for working with the OpenAI API, ensuring accurate and up-to-date information for developers.

Expertly builds stateful, multi-actor AI applications using LangGraph, focusing on graph construction and state management.