Skill UI

Automates Addresszen tasks by orchestrating Composio’s Addresszen toolkit through the Rube MCP workflow, ensuring schema-aware tool discovery, session-aware execution, and connection checks before running any operations.

Provides steps to automate Adobe tasks via Composio's Adobe toolkit using Rube MCP, emphasizing discovery of current tool schemas, connection verification, and compliant execution flows for reliable workflows.

Guides connecting Rube MCP to Composio’s Adyntel toolkit, searching for live tool schemas, validating connections, and executing multi-tool workflows while handling session reuse, memory, and pagination requirements.

Automate Composio’s Aero Workflow toolkit through the Rube MCP bridge, discovering current tool schemas with `RUBE_SEARCH_TOOLS`, validating connections, and dispatching schema-compliant calls to `RUBE_MULTI_EXECUTE_TOOL` for safe workflow operations.

Automate Aeroleads operations via Composio’s toolkit using Rube MCP: search for current tool schemas, confirm active connections, and invoke multi-tool executions with schema-compliant arguments and session handling.

Guides automating Affinda tasks through Composio's Rube MCP client, detailing connection setup, tool discovery, multi-tool execution, and reminders about schema searches, sessions, and pagination safety.

Automates Affinity tasks through Composio’s toolkit by using the Rube MCP commands to search for current tool schemas, validate the affinity connection, and execute schema-compliant workflows across RUBE_SEARCH_TOOLS, RUBE_MANAGE_CONNECTIONS, and RUBE_MULTI_EXECUTE_TOOL.

AFL++ is an advanced fork of AFL that runs multi-core campaigns, supports diverse mutations, and targets large C/C++ codebases with stable tooling via Docker or host builds.

Streamlines Agencyzoom operations through Composio’s toolkit by driving Rube MCP searches, connection checks, and multi-execute calls before any action, making it ideal for automation engineers embedding CRM tasks into composable workflows.

Automatically detects and loads specialized agent instructions from the `AGENTS.md` file in the current working directory. This skill seamlessly integrates project-specific rules and behavioral guidelines into the AI's session context, ensuring the AI operates according to project standards without manual intervention. It is crucial for maintaining specialized agent behaviors across different development tasks and directory changes.

A comprehensive tool for designing, generating schemas, and evaluating complex multi-agent systems. It guides users through defining system requirements, selecting optimal orchestration patterns (Supervisor, Swarm, Pipeline), generating provider-ready tool schemas (Anthropic/OpenAI), and analyzing execution logs for performance bottlenecks, cost, and latency. This ensures robust, production-grade autonomous workflows.

Utilizes the Azure AI Projects SDK's ImageBasedHostedAgentDefinition to build robust, container-based AI agents deployed in Azure AI Foundry. This workflow is essential for creating production-grade agents that require custom logic, precise resource allocation (CPU/Memory), and integration of advanced tools like code interpreters.