Agent Skills Hub

sql

Executes SQL queries against the WordPress development database for inspection, troubleshooting, and audit log analysis.

unity

Control the Unity Editor via Claude Code to run tests, compile scripts, manage play mode, and retrieve console logs using a file-based bridge.

chrome-devtools-mcp-manager

Manage OpenClaw's built-in Chrome browser and chrome-devtools-mcp integration for robust browser automation using the Model Context Protocol.

youtube_moderation_prototype

A prototype skill for automating YouTube live chat moderation using pattern-based detection for spam, toxic content, and rate limiting, optimized for testing agent reliability before deployment.

iterate

Autonomous improvement loop for codebase optimization. Automatically modifies, measures, and iterates on code based on a specific goal and mechanical metric.

native-app-performance

Native macOS/iOS app performance profiling via xctrace and CLI-based hotspot analysis without opening the Instruments UI.

database-patterns

Expert database design and access patterns: schema architecture, indexing strategies, query optimization, repository patterns, and transaction management for SQL and NoSQL databases.

code-search-selector

Intelligent tool selector for code search. Routes queries between semantic (claudemem) and native tools (Grep/Glob) to optimize efficiency, token usage, and search accuracy.

code-review

Perform comprehensive code reviews with a focus on security vulnerabilities, performance optimization, maintainability, and code correctness.

pytorch-lightning

PyTorch Lightning skill for scalable deep learning: automates model training, multi-GPU orchestration, data pipelines, and distributed training strategies like DDP, FSDP, and DeepSpeed.

dinero-best-practices

Enforce best practices for Dinero.js. Use when handling monetary values, performing arithmetic, or refactoring code to ensure safe, type-safe, and accurate currency calculations in JS/TS applications.

context-optimization

Optimize agent context windows through KV-caching, observation masking, summarization-based compaction, and context partitioning to reduce costs and latency.