Agent Skills Hub

swarm-advanced

Orchestrate complex multi-agent swarms with topologies like mesh, hierarchical, and star for research, development, and testing workflows.

infographic-template-updater

Automates the synchronization of new infographic templates by updating project documentation, gallery mappings, and AI playground prompts.

mcp-guide

Decision framework for choosing between MCP tools and direct API skills to optimize agent performance, cost, and efficiency.

lading-optimize-submit

Automates the submission workflow for lading performance optimizations, including branch management, git commits, and PR creation.

project-development

A framework for managing the end-to-end LLM project lifecycle, from evaluating task-model fit and pipeline architecture design to implementing structured output parsing and agent-assisted development.

vm-dev

Virtual machine development expert focusing on bytecode design, stack-based/register-based VM implementation, memory management, and garbage collection.

microsim-screen-capture

Automate high-quality screenshot generation for MicroSim visualizations using Chrome headless mode. Ideal for documentation, social media previews, and quality assessment.

datarobot-model-deployment

Tools for deploying, managing, and monitoring DataRobot models, including prediction environment configuration, champion/challenger workflows, and deployment operations.

token-surgeon

Audit and optimize your AI prompts with Token Surgeon. Detect 10 common waste patterns, calculate efficiency, and reduce token usage for better prompt performance.

deep-research

A systematic, multi-angle web research agent. Use for deep investigation, complex queries, and as a mandatory pre-research step before content generation to ensure evidence-backed, high-quality results.

tool-design

Expert framework for designing agent-facing tools, optimizing tool descriptions, enforcing contract-based APIs, and implementing architectural reduction for reliable AI agent tool selection.

skill-engineer

Orchestrates multi-agent iterative refinement for high-quality OpenClaw skill development, ensuring rigorous testing and lifecycle management.