Agent Skills Hub

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.

code-review-facilitator

Automated static code review for Arduino, ESP32, and RP2040 projects. Identifies memory safety issues, structure improvements, and best practices to enhance firmware quality and reliability.

workflows-plan

Transforms feature requests, bug reports, and improvement ideas into structured, actionable markdown project plans using repository research and industry best practices.

structured-outputs-advisor

Expert advisor for implementing Anthropic's structured outputs. Choose between JSON mode and strict tool use for guaranteed schema compliance and validated agentic workflows.

structured-code-review

Performs a structured five-stage code review covering requirements, correctness, code quality, testing, and security. Provides actionable, categorized feedback (Blocker/Major/Minor/Nit) to improve PR quality.

risk-based-testing

Focus testing effort on highest-risk areas using risk assessment and prioritization. Use when planning test strategy, allocating resources, or making coverage decisions.

vercel-react-native-skills

React Native and Expo best practices for performant mobile apps. Covers list virtualization, animations with Reanimated, UI patterns, and native platform API optimizations.

inno-prepare-resources

Automates research resource preparation by loading instances, searching GitHub for codebases, building dataset descriptions, and downloading arXiv papers.

vitest

Vitest testing patterns for reliable unit and integration tests. Focuses on critical business logic, edge cases, and mocking strategies for high-impact functions.

omc-plan

Intelligent strategic planning and requirements gathering with multi-perspective consensus loops and structured deliberation.

implementation-planner

Create structured, high-quality technical implementation plans via an agent-driven, iterative process. Ideal for complex refactoring, new features, and technical design.

markdown-token-optimizer

Analyzes markdown files to identify token-wasting patterns, providing actionable suggestions to optimize documentation for LLM consumption and token efficiency.