Skill UI

Automates HubSpot CRM workflows through Rube MCP and Composio, orchestrating contact, company, deal, ticket, and custom property tasks while enforcing batch limits and schema-aware validation.

Automates daily planning by integrating with your calendar (e.g., Outlook via WorkIQ). It pulls your schedule, cross-references open tasks, analyzes workspace context, and classifies every meeting (Customer, Deep Work, Learning, etc.). The tool detects scheduling conflicts, identifies time zone issues, and generates a structured HTML prep file with proactive recommendations to maximize focus and productivity for the next day.

Automates Linear issues, projects, cycles, labels, comments, and GraphQL workflows through Rube MCP’s Composio toolkit so teams can manage states, tasks, and custom queries without juggling direct APIs.

Generates concise meeting minutes for internal syncs up to 60 minutes, capturing metadata, attendees, agenda, decisions, action items with owners/due dates, and follow-up steps for easy task creation.

Reads `.agent.md` or `.prompt.md` files, assesses task complexity, tooling, and requirements, then recommends the most cost-efficient GitHub Copilot model(s) (e.g., GPT-5, Claude Sonnet) with rationale for users across different subscription tiers and priorities.

Guides how to write JavaScript inside n8n Code nodes, choose execution modes, access data with $input/$node, handle Webhook payloads, and return the required [{json:…}] structure for automation tasks.

This guide provides proven architectural patterns for building complex, reliable, and scalable workflows using n8n. It covers core patterns like Webhook processing, HTTP API integration, database synchronization, AI agent design, and scheduled tasks. Learn how to select the right pattern and utilize advanced components for robust automation.

Use Composio's Rube MCP suite to orchestrate Pipedrive CRM workflow tasks—deals, contacts, activities, notes, and pipelines—by first calling RUBE_SEARCH_TOOLS for schemas and keeping the connection active before executing each workflow.

This skill implements a persistent, file-based planning system (Manus Pattern) for managing complex tasks and projects. It mandates the use of dedicated Markdown files—task_plan.md, findings.md, and progress.md—to act as a reliable "disk working memory." It guides users through structured planning, detailed progress logging, discovery documentation, and rigorous error tracking, ensuring that context and findings are always preserved and traceable, regardless of session interruptions or complex workflow steps.

This system manages complex, multi-stage tasks by leveraging the file system as persistent memory. It automatically creates and updates structured Markdown files (task_plan.md, findings.md, progress.md) to track project phases, record research findings, and log errors. It is essential for long-running research, large-scale development projects, or any workflow that exceeds the limitations of the session context window.

This tool acts as an expert prompt engineer, guiding users through a systematic discovery process to create highly structured, production-ready prompts for AI assistants like GitHub Copilot. It covers defining persona, specifying complex tasks, managing context variables, integrating tools, and enforcing strict output standards, ensuring the resulting prompt is comprehensive and actionable for advanced AI agents.

A comprehensive template for planning large-scale, multi-file refactoring tasks. It enforces a systematic approach by requiring developers to map out the current state, target state, affected files, and execution phases (Types, Implementation, Tests). Crucially, it mandates detailed verification and a robust rollback plan to ensure code stability during major changes.