Skill UI

Guides connecting to Composio's Rube MCP to discover templated toolkit actions, ensuring searches for up-to-date schemas before running workflows, managing connections, and executing tools via multi-step MCP calls.

Automates Composio Textit workflows through Rube MCP APIs, guiding you to search tool schemas, manage Textit connections, and execute operations while reusing sessions, filling memory placeholders, and respecting pagination tokens.

Automates Textrazor tasks through Composio’s Rube MCP pipeline, using RUBE_SEARCH_TOOLS, RUBE_MANAGE_CONNECTIONS, and RUBE_MULTI_EXECUTE_TOOL so each workflow picks up the current schema and active toolkit connection.

Automates Thanks IO operations through Composio’s Rube MCP toolkit by guiding workflows to search current tool schemas, verify connections, and execute schema-compliant calls with session-aware memory handling.

Automates Timelinesai tasks by driving Composio’s toolkit through the Rube MCP interface, ensuring connection management, schema discovery, and lifecycle steps (search, connect, execute) are enforced before workflow execution.

Guides using Composio’s Rube MCP to automate Timelink tasks: search the current tool schemas before every workflow, confirm Timelink connections, execute via RUBE_MULTI_EXECUTE_TOOL with compliant arguments, handle pagination, and reuse sessions safely.

Automate Timely workflows through Composio’s toolkit using Rube MCP, always calling RUBE_SEARCH_TOOLS to fetch the latest schemas before executing managed tools.

Automate Token Metrics operations through Composio’s toolkit by orchestrating Rube MCP searches, connection checks, and schema-compliant executions so every `RUBE_MULTI_EXECUTE_TOOL` call runs with up-to-date tooling details and pagination awareness.

Uses Rube MCP and Composio's Tomtom toolkit to automate Tomtom workflows, from fetching live tool schemas with `RUBE_SEARCH_TOOLS` to validating `RUBE_MANAGE_CONNECTIONS` status and executing `RUBE_MULTI_EXECUTE_TOOL` calls with schema-compliant arguments.

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.

TransformerLens is the standard library for performing mechanistic interpretability research on large language models. It provides clean interfaces to inspect and manipulate transformer internals—such as attention patterns, residual streams, and MLP outputs—via activation caching and HookPoints. This tool is essential for reverse-engineering model algorithms, performing causal tracing, and studying the internal circuits responsible for model behavior.

Automates Trello boards, cards, lists, assignments, searches, comments, and attachments through Composio’s Rube MCP, so teams can script workflows like card creation, movement, member assignment, and data retrieval without manual clicks.