Skill UI

RouterBase acts as a unified, OpenAI-compatible API gateway, allowing applications to route requests across diverse large language models (LLMs) like GPT, Claude, and Gemini. It helps developers migrate existing OpenAI SDK calls, implement sophisticated primary/fallback model selection based on cost, latency, and quality, and manage multimodal payloads (image, audio, video) from a single, standardized endpoint.

This utility diagnoses and automatically repairs common issues within the Ruflo installation environment. It performs comprehensive health checks on core dependencies like Node.js, npm, and git, while also validating configurations, daemon status, memory databases, and API keys. It provides targeted commands to resolve issues related to memory initialization, daemon startup, and configuration resets, ensuring a stable operational environment.

The Santa Method is a multi-agent adversarial verification framework designed to improve output quality by requiring two independent reviewers (Agent B and Agent C) to pass the content before publication. It eliminates single-agent bias and systematically improves outputs through iterative refinement loops until convergence or manual escalation.

This tool assesses whether coding agents adhere to defined skills, rules, or agent definitions. It automatically generates scenarios with varying prompt strictness, executes the agent, and generates a comprehensive report detailing the compliance rate of tool calls against predefined workflow specifications using advanced LLM classification.

Skill Scout is a crucial pre-creation workflow designed to prevent the duplication of effort. Before building a new skill, it systematically searches local, marketplace, GitHub, and web sources. It not only finds potential matches but also rigorously vets them for security, maintenance status, and relevance, providing the user with clear options: Use Existing, Fork/Extend, or Create New.

An advanced tool for network intelligence that calculates weighted graph scores to map the optimal path to a target. It identifies potential introducers, measures 'bridge value' across connections, and helps determine whether a connection requires a warm introduction or direct outreach on platforms like X and LinkedIn. Ideal for users needing the raw ranking methodology.

This skill guides users through Phases 2 (Pseudocode Design) and 3 (Architecture Design) of the SPARC methodology. It translates high-level specifications into detailed technical blueprints, covering algorithm pseudocode, module boundaries, API contracts (using DDD patterns), and infrastructure planning, ensuring a robust plan before writing production code.

This skill executes the final two phases of the SPARC methodology: Refinement and Completion. It systematically reviews the implemented feature through rigorous code reviews, expands test coverage (unit, integration, edge cases), validates performance, generates a traceability matrix, creates comprehensive documentation, and confirms deployment readiness. It ensures the feature is robust, tested, and production-ready.

This tool executes the foundational SPARC Specification Phase (Phase 1) for new features or projects. It guides the user through systematically gathering comprehensive requirements, including functional/non-functional needs, defining concrete acceptance criteria (Given/When/Then), identifying technical constraints, and mapping edge cases. It creates a robust, formalized specification document that serves as the blueprint for all subsequent design and development phases.

A comprehensive guide to architectural patterns for building scalable, production-ready backend services using Java and Spring Boot. Covers essential topics including RESTful API design, layered architecture (Controller, Service, Repository), data persistence (JPA), caching, asynchronous processing, robust error handling, and middleware filtering.

This skill acts as an expert guide for creating comprehensive, implementation-ready design system documentation. It structures guidelines by defining foundational tokens (color, typography, spacing), detailing component anatomy, interaction states, and adhering to strict accessibility standards (WCAG 2.2 AA). Use it to ensure your design standards are consistent, technically sound, and actionable for engineering and design teams.

Suggests when to manually run /compact at logical workflow boundaries instead of relying on automatic compaction, helping preserve context after research, milestones, or task shifts.