Agent Skills Hub

airflow

Query, manage, and troubleshoot Apache Airflow workflows using the af CLI. Features include DAG inspection, task log retrieval, run triggering, error diagnosis, and system health monitoring.

ai-writing-guide

Automate multi-stakeholder marketing asset approvals with tiered routing, real-time status tracking, and automated escalations.

ai-pattern-detection

Detects AI-generated patterns in writing and suggests authentic, human-like alternatives to improve content quality and natural voice.

ai-llm-engineering

Operational hub for LLM system lifecycle, architecture, and deployment. Features include PEFT/LoRA fine-tuning, RAG pipelines, vLLM throughput optimization, automated drift detection, and CI/CD-integrated evaluation frameworks.

ai-integration

Patterns and reference implementation for integrating the Claude API into applications, including chat, streaming, tool use, and structured JSON output.

agently-playbook

The primary entry point for orchestrating Agently projects, managing model-powered tools, defining workflows, and structuring application architectures from initial business requirements.

agentic-quality-engineering

Orchestrate advanced Quality Engineering workflows using a fleet of 19+ AI agents, PACT principles, and automated test-to-deployment quality gates.

agentic-jujutsu

Quantum-resistant, self-learning version control and multi-agent coordination for AI developers and engineering teams.

agentic-development

Build autonomous, multi-step AI agents using Pydantic AI (Python) and Claude Agent SDK (Node.js/TypeScript).

AgentDB Vector Search

High-performance vector search engine for AI agents featuring sub-millisecond retrieval, HNSW indexing, and quantization for efficient RAG, similarity matching, and knowledge base management.

AgentDB Performance Optimization

Optimize AgentDB performance using quantization, HNSW indexing, caching, and batch operations to improve speed, memory, and scalability.

AgentDB Memory Patterns

Implement high-performance persistent memory and self-learning patterns for AI agents using AgentDB. Features session memory, long-term vector storage, and hierarchical context management for stateful agent workflows.