cconami

Generate ralph.yml and PROMPT.md configuration files for Ralph Orchestrator workflows from plans, tickets, or ideas. Use when setting up Ralph Orchestrator, creating hat-based workflows, or adapting Linear/Jira/markdown plans into ralph.yml + PROMPT.md files.

Build production-ready Claude Code skills through a structured Research-Draft-Refine process. Use when creating new skills, converting slash commands to skills, or generating AgentSkills.io-compatible skills from specifications.

Analyzes and visualizes dependencies across work items, identifying blockers, critical paths, and circular dependencies. Use when planning sprints, debugging blocked items, or understanding work item relationships before execution.

Facilitates interactive design brainstorming sessions for UI/UX concepts. Use when exploring visual designs, user flows, component architecture, or creative solutions before implementation.

Breaks down epics into features and tasks optimized for AI agent execution. Includes structure preparation, parallel codebase analysis, feature sizing, task generation, and dependency mapping. Use when an epic is ready for sprint planning or when a large work item needs decomposition into actionable pieces.

Systematically creates production-ready Claude Code subagents with research, drafting, and refinement phases. Use when you need a new specialized agent for a specific domain or task pattern.

Executes specific work items ad-hoc using AI agents with intelligent dependency analysis and parallelization. Use when you need to implement one or more specific items outside of a formal sprint, or when testing implementation of individual features.

Manages sprint lifecycle including planning, execution, monitoring, and review. Use for creating sprints from epics (/managing-sprints plan), executing sprints with parallel AI agents (/managing-sprints execute), checking progress (/managing-sprints status), or reviewing completed work (/managing-sprints review). Optimizes for maximum parallelization while avoiding file conflicts.

Provides project management tool abstraction layer. Auto-loads when working with work items, epics, features, tasks, sprints, or backlogs. Detects PM tool (Linear, Jira, GitHub Projects, markdown) from project configuration and loads appropriate adapter for seamless operations across different PM systems.

Refines work items (epics, features, tasks, bugs) into AI-ready specifications. Use when converting rough ideas into structured items, preparing epics for breakdown, enhancing existing items with acceptance criteria, or creating new items from scratch. Supports --type (epic|epic-lite|feature|task|bug), --analyze-codebase for technical context, and --interactive for guided refinement.

Scrapes documentation websites and converts content to organized markdown files for local reference. Use when you need offline documentation, want to add library docs to ai_docs/knowledge/, or need to create local reference materials.

Reorganizes work items when priorities change - move items between sprints or projects, rebalance workload, and update dependencies. Use when sprint scope changes, priorities shift, or work needs redistribution.

Facilitates interactive PRD (Product Requirements Document) workshops with multi-phase workflow. Use when defining new features, products, or initiatives that need structured requirements gathering and documentation.