Skill UI

torchforge is Meta's advanced PyTorch-native library designed for agentic Reinforcement Learning (RL). It fundamentally separates core RL algorithms from complex distributed infrastructure concerns. This allows researchers to rapidly prototype and experiment with novel RL methods (like GRPO) using clean, PyTorch-native abstractions, while automatically handling large-scale tasks like distributed training across thousands of GPUs using Monarch and TorchTitan.

Tracks CPU, memory, disk/network I/O, DB connections, and threads via the resource-usage-tracker plugin to reveal performance bottlenecks, recommend right-sizing, and guide cost-saving actions.

Guide for orchestrating Triggercmd actions through Rube MCP and Composio, covering prerequisites, discovery steps, connection checks, execution calls, and best practices for schema compliance when automating flows.

This skill guides users through transcribing live meetings (Zoom, Meet, Teams) or voice memos using advanced AI. It provides full transcriptions with timestamps, and advanced AI processing to automatically generate structured meeting summaries, prioritized action items with assignees, and key discussion points. It is essential for meeting accountability, knowledge capture, and project follow-up.

A comprehensive utility suite for handling external API rate limits, specifically designed for services like TwinMind. It implements advanced patterns including exponential backoff with jitter and request queue management. Use this to ensure resilient, high-throughput, and stable interactions with resource-constrained AI APIs, minimizing 429 errors.

Automates Twitter/X workflows via Rube MCP’s Composio toolkit, handling posts, searches, user lookups, bookmarks, lists, and interactions after establishing the managed connection.

Guides using the GitHub CLI to inspect repositories, manage PRs/issues/actions, and fetch API data instead of curl/WebFetch, with tips for cloning, viewing, and automating GitHub workflows.

This guide details how to integrate Vast.ai's GPU provisioning capabilities into automated CI/CD pipelines, such as GitHub Actions. It enables developers to run GPU-accelerated tests, model benchmarks, and validations automatically. Key features include robust instance lifecycle management (provisioning, running, and cleanup) and advanced cost-control mechanisms (e.g., setting budget limits) to ensure reliable and efficient testing in a cloud environment.

Automate Venly operations via the Composio Rube MCP stack by discovering current tool schemas, validating connections, and executing schema-compliant actions for NFT and wallet workflows.

Configures robust CI/CD pipelines for Vercel projects using GitHub Actions. This guide automates the full deployment lifecycle, including generating preview environments on every pull request, performing reliable production builds upon merging to main, and implementing test gating to ensure code quality before release. Ideal for professional web development workflows.

A comprehensive guide for implementing secure and reliable webhook endpoints to handle Vercel deployment lifecycle events. This skill covers signature verification (HMAC) to ensure security, processing key events (e.g., deployment.ready, deployment.error), and implementing idempotency to prevent duplicate actions. Ideal for building automated CI/CD integrations, status notifications, or custom project hooks that react to deployment changes in real-time.

Master advanced testing strategies for smart contracts using industry-leading frameworks like Hardhat and Foundry. This skill covers unit testing, integration testing, gas optimization analysis, fuzzing for edge cases, and simulating real-world mainnet interactions via forking. Ideal for ensuring the security and reliability of decentralized applications (DApps).