Skill UI

A comprehensive guide covering patterns and architectures for automating code execution using LLMs. It spans simple sequential pipelines (e.g., daily dev scripts) to advanced, RFC-driven multi-agent Directed Acyclic Graph (DAG) orchestration. Ideal for building CI/CD style continuous development pipelines, managing complex state, and automating quality gates without human intervention.

A comprehensive operational guide for support teams to manage complex customer billing workflows. It assists operators in diagnosing billing anomalies, processing refunds, triaging charges, and recovering customer portals. Use this when investigating billing discrepancies, assessing churn risk, or ensuring accurate subscription state and revenue management.

This skill manages the end-to-end operational workflow for corporate email communication. It is focused on the mechanics of the mailbox itself, allowing users to triage inboxes, draft replies, send messages, and verify successful delivery. It ensures that all actions are context-aware, adhering to brand voice, and providing verifiable proof of the message's final status (e.g., Sent or Drafted).

This skill provides comprehensive operational controls for long-lived, cloud-hosted agent workloads. It manages the entire lifecycle—from deployment and scaling to observability and security. Features include detailed monitoring (logs, metrics, traces), safety controls (kill switches, least privilege), and robust change management processes (rollout, rollback, auditing). Ideal for mission-critical microservices and background agents.

Used to verify the actual billing reality, revenue, and pricing mechanics—such as team billing, quotas, and refunds—based on underlying product code, rather than sales documents or simple customer fixes. This skill separates billing facts, customer impact, and the true product implementation logic.

A comprehensive guide detailing modern architectural patterns for building high-performance user interfaces with React and Next.js. Covers advanced techniques including Compound Components, Render Props, custom state hooks (like useQuery and useDebounce), advanced state management (Context + Reducer), and performance optimization strategies like memoization and code splitting.

Manage GitHub repositories effectively through issue triaging, PR reviews, and CI/CD workflow debugging. Automate release management and security monitoring using the GitHub CLI. Ideal for maintaining open-source project health and developer experience.

This skill guides the operation, consolidation, and maintenance of complex working systems within Google Workspace (Docs, Sheets, Slides). It emphasizes treating files as integrated systems—such as trackers or planning hubs—requiring careful inspection, precise edits, and structural cleanup rather than simple content rewriting. Use it for consolidating scattered data, cleaning shared spreadsheets, or ensuring the correct canonical version of a document is utilized.

A powerful tool designed to scaffold sophisticated, custom AI agent harnesses using the metaharness CLI. It supports various templates (e.g., coding, devops, marketing) and AI hosts (e.g., Claude, Codex). Crucially, it operates with maximum safety, defaulting to a dry-run mode and refusing to write to the calling repository root, ensuring controlled and predictable development workflows.

This framework manages the ingestion, organization, synchronization, and search of knowledge across multiple storage layers, including local files, persistent memory, vector stores, and Git repositories. It provides a structured approach for ensuring knowledge durability, deduplication, and maintaining a 'single source of truth' across complex development and operational contexts.

Provides comprehensive configuration management for local LLM inference using RuVLLM. Users can select models, perform task-specific fine-tuning with MicroLoRA adapters, or implement continuous, real-time adaptation using SONA. This tool guides the entire advanced LLM workflow, covering status checks, configuration generation, and advanced adaptation loops.

Design and review goal-oriented agent loops to prevent failure modes like spinning or Goodhart-gaming. Covers defining machine-decidable goals, selecting loop types (servo/regulator), and implementing plan/build/judge skeletons. Essential for building stable autonomous agents.