Skill UI

Provides comprehensive guidance on scheduling AI agent runs, covering external systems like cron and systemd, and built-in schedulers (e.g., Hermes). It details best practices for setting up recurring jobs, implementing heartbeat patterns, and avoiding common pitfalls like tight timers or state loss, ensuring reliable, scheduled automation.

A comprehensive guide covering patterns and architectures for automating code execution using LLMs. It spans simple sequential pipelines (e.g., daily dev scripts) to advanced, RFC-driven multi-agent Directed Acyclic Graph (DAG) orchestration. Ideal for building CI/CD style continuous development pipelines, managing complex state, and automating quality gates without human intervention.

A robust framework for orchestrating complex, multi-step coding tasks using multiple AI agents. It functions by first planning the entire project into a mission dependency graph (DAG), then dispatching specialized agents to isolated Git worktrees for parallel development. The system automatically monitors progress, handles merges, and generates structured, comprehensive reports detailing changes, completed tasks, and next steps.

This advanced orchestration tool streamlines the process of building a Minimum Viable Product (MVP). By ingesting high-level design documents (SDD/PRD), it automatically plans thin, end-to-end vertical slices. The system then scaffolds, executes TDD implementation, and manages gated commits, transforming theoretical specifications into a functional, reviewable starting point, dramatically accelerating initial development cycles.

This engine serves as a shared, comprehensive orchestration layer for the entire development lifecycle (orch-* skills). It defines a rigorous, gated pipeline—including Research, Plan, TDD Implementation, Review, and Commit—ensuring consistency regardless of the specific operation (e.g., feature addition, defect fixing). It also includes a size classifier to accurately scope the required effort and gates for mandatory human review.

This skill provides a structured framework for managing complex, multi-agent development tasks. It treats agents as a collaborative team, utilizing structured work items, defined ownership, Agent Kanban boards, and explicit merge gates. This ensures that large-scale, multi-tool, or cross-branch development efforts are predictable, highly visible, and result in reliably mergeable, production-ready artifacts.

This skill acts as an advanced orchestration protocol for reviewing GitHub pull requests. It is stack-agnostic, meaning it does not enforce its own rules. Instead, it dynamically discovers the project's existing standards—such as the test runner, architectural conventions, and requirement specifications—before running six specialized subagents in parallel. It provides a comprehensive, context-aware review and summary directly on GitHub.