Agent Skills Hub

data_processor

A multi-paradigm ETL pipeline agent supporting batch and streaming data processing, schema inference, and configurable DAG-based transformations for heterogeneous data sources.

ring:writing-skills

A framework for applying Test-Driven Development to process documentation, ensuring agent reliability by using pressure scenarios to identify and patch rationalization loopholes.

task-breakdown

Break down complex development requests into sequenced, actionable tasks for multi-agent delegation in Claude Code environments.

Observability

Real-time observability dashboard for PAI multi-agent activity, featuring live WebSocket streaming, session tracing, and agent workflow debugging.

qras

A local RAG semantic memory system using Qdrant and Ollama. Ideal for recalling workspace files, notes, project decisions, and user preferences with high-relevance vector search.

hf-mcp

Connect your AI agent to the Hugging Face Hub via MCP. Search models, datasets, and papers, manage repos, run cloud compute jobs, and invoke Gradio Spaces as functional AI tools.

openai-agents-sdk

Build AI agents with the OpenAI Agents SDK for Python. Supports multi-agent handoffs, function tools, stateful sessions, streaming, and Azure OpenAI integration via LiteLLM.

test-driven-development

Enforces disciplined Test-Driven Development (TDD) by requiring a failing test before implementation, ensuring code reliability and preventing premature over-engineering.

cn-daily-tools

An all-in-one Chinese daily utility toolkit: weather, currency exchange, news, and package tracking. Zero configuration, no API keys required.

aarnphm.github.io

A highly customized personal garden based on Quartz v4, featuring enhanced Markdown parsing, telescopic text, TikZ/pseudocode rendering, and Obsidian integration.

marketing-fundamentals

Master core marketing concepts, psychology, and frameworks. Includes funnel mapping, positioning, value propositions, and customer journey analysis for effective strategy.

prompt-improver

Enriches vague prompts by performing codebase research and asking targeted questions to clarify user intent before execution.