Skill UI

This skill covers production patterns for Linkerd, a lightweight security-first service mesh for Kubernetes. It includes setup instructions, namespace injection, service profiles for retries/timeouts, traffic splits for canary deployments, server authorization policies, and multi-cluster configurations. Ideal for DevOps engineers managing microservices security and traffic management.

A systematic, multi-phase workflow designed for diagnosing and resolving complex Linux system issues. It guides users through initial assessment, resource analysis (CPU, memory, disk), process investigation, log analysis, network diagnostics, and service failure resolution. Ideal for system administrators and DevOps engineers handling production incidents.

Design and implement production-ready ML pipelines using multi-agent MLOps orchestration, covering data engineering, feature engineering, model training, experiment tracking, deployment, and serving.

This skill simulates a highly advanced 'Board of Experts,' consulting multiple specialized personas (e.g., Musk, Buffett, Jobs) simultaneously. It gathers distinct, multi-perspective analyses on any complex topic—from engineering feasibility to market strategy—and synthesizes them into a single, comprehensive, and actionable decision. Ideal for complex strategic planning, product development, and high-stakes investment decisions.

Aggregates AI and tech news from multiple RSS feeds, deduplicates overlapping coverage, ranks stories by industry impact, and outputs structured briefing cards with sentiment, tags, impact scores, and commentary.

Nika is an open-source Rust engine that captures repeatable AI tasks as checkable YAML workflow files. It audits workflows before token spending, enforces strict cost budgets, and executes against local or cloud providers. Ideal for daily digests, ETL, and multi-step pipelines requiring audit trails and deterministic execution without autonomous coding capabilities.

Open Dynamic Workflows (ODW) is an advanced, open-source engine designed to manage complex coding tasks using multiple AI agents. It operates in three stages: planning the task into parallel subtasks, orchestrating various coding agents (like Codex or Antigravity) to work concurrently, and finally, performing an adversarial verification pass to challenge and validate the combined output before merging. It supports multiple model providers and is ideal for structured, high-reliability software development.

This skill scaffolds the necessary configurations for advanced engineering workflows. It guides the user through setting up the issue tracking system (GitHub, GitLab, or local markdown), defining the canonical triage label vocabulary, and establishing the domain documentation context (single or multi-context). It must be run once to initialize the repository for subsequent agent-driven development skills.

Build real-time conversational AI voice engines using async worker pipelines, streaming transcription, LLM agents, and TTS synthesis with interrupt handling and multi-provider support. Ideal for creating voice assistants, customer service agents, and voice-enabled applications that process streaming audio and integrate multiple AI providers effectively.

This tool identifies duplicate content across multiple texts or web pages. It compares input to find exact matches and substantive overlaps, aiding in SEO optimization and content quality assurance. Users can paste content or provide URLs for analysis to ensure originality and compliance with search engine guidelines.

This skill acts as an interactive brainstorming engine for the Elephant & Goldfish Model (EGM). It transforms raw concepts into structured hypotheses through clarifying questions and automated multi-lens reviews. The process iteratively refines ideas into RFC summaries ready for human review or detailed design. It emphasizes stress-testing, avoiding bias, and delivering artifacts first to ensure robust product development.