Skill UI

Orchestrate Wolfram Alpha API workflows through Composio’s toolkit using Rube MCP, ensuring each run first fetches current tool schemas, verifies active API connections, and executes schema-compliant steps via multi-tool calls.

Create a disciplined, developer-ready implementation plan whenever a multi-step spec arises; document every file, command, and bite-sized action with precise steps, tests, and commit guidance so any engineer can execute confidently with DRY/YAGNI/TDD practices.

This guide provides essential patterns and best practices for building robust automated workflows using no-code platforms like Zapier and Make. Learn the difference between simple triggers and complex multi-step processes, including conditional branching and data transformation. Understand when to use each platform's strengths to ensure reliable business process automation.

Automates Zoho Inventory workflows by orchestrating Composio toolkit calls through the Rube MCP interface, guiding you to first search tools, verify connections, and execute multi-step operations with schema compliance and session reuse.

PufferLib is a high-performance library designed for advanced reinforcement learning simulations and training. It excels in parallel environment simulation, offering optimized vectorization and native support for multi-agent systems. Utilizing algorithms like PuffeRL (optimized PPO+LSTM), it achieves millions of steps per second, significantly accelerating research and deployment across single-agent and multi-agent environments.

A powerful tool for architecting production-grade multi-agent workflows. It allows users to define complex, multi-step AI pipelines using structured patterns (sequential, parallel, hierarchical). Key features include defining explicit handoff contracts, implementing robust failure handling, and managing context/cost discipline across long-running processes, ensuring reliable and scalable AI system deployment.

Creates detailed implementation plans for multi-step tasks by outlining file responsibilities, concrete coding/testing steps, and commit guidance so developers can execute with no prior context.

This command guides the entire lifecycle of major feature development, providing a structured, multi-phase workflow. It helps users move a feature from initial concept (research) through planning, implementation, and progress tracking. Use it when you need to coordinate status, next steps, and phased delivery for complex features.

This guide outlines a systematic process for transforming any recurring technical pattern, complex debugging solution, or workflow into a standalone, portable skill. It details the multi-step extraction workflow, including pattern identification, structured documentation generation (SKILL.md), and quality control checks to ensure the skill can be reused across different projects.

Build, run, and visualize multi-step AI generation workflows via muapi.ai. Translate natural language intents into runnable node graphs, discover or edit existing pipelines, and execute them interactively or through the CLI with automated monitoring.

Guides Odoo users through configuring FIFO/AVCO valuation, reordering rules, putaway strategies, warehouse routes and multi-step flows to ensure accurate stock levels and traceable receipts/shipments.

A comprehensive, canonical workflow for defining, writing, and improving complex AI skills. It guides users through a structured, multi-step process, including resolving targets, synthesizing information, enforcing depth gates, authoring artifacts, optimizing descriptions, and conducting thorough evaluation and validation.