trycycle

Orchestrate multi-agent planning, execution, and review loops with artifact tracking.

3|Updated Jan 14, 2014

Search Tags:#automation #workflow #planning #ai #agents #orchestration #execution

Ready to run

npx skills add https://github.com/prateek/dotfiles --skill trycycle-prateek

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: trycycle
Source: https://github.com/prateek/dotfiles/tree/main/.agents/skills/trycycle
Command: npx skills add https://github.com/prateek/dotfiles --skill trycycle-prateek

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Trycycle provides a disciplined workflow orchestrator for AI coding agents, enabling users to chain planning, execution, and review loops with deterministic gating and artifact management.

Core Features & Use Cases

Orchestrates multi-agent planning, execution, and post-implementation review loops
Ensures consistent workflow state via worktrees/workspace hygiene and artifact tracking
Supports both local and host backends across Codex, Claude, Kimi, and OpenCode
Use cases: coordinating agent-driven coding tasks, code review automation, and autonomous AI pilots

Quick Start

Tell your preferred AI agent to invoke Trycycle by name to start an autonomous workflow coordination.

Frequently Asked Questions about trycycle

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

What is multi-agent workflow orchestration for AI coding tasks?▼

Multi-agent workflow orchestration coordinates planning, execution, and post-implementation review phases for AI agents. Trycycle enables this by creating an auditable automation loop, ensuring agents operate cohesively with deterministic gating and artifact tracking throughout the entire process.

Does AI agent orchestration work with Claude and Codex backends?▼

Yes, AI agent orchestration supports both local and host backends across Codex, Claude, Kimi, and OpenCode. Trycycle coordinates these environments by managing workflow state via worktrees and workspace hygiene to maintain consistent execution across different platforms.

How do I automate code review with a multi-agent workflow?▼

Automate code review by chaining execution and post-implementation review loops within an orchestrated workflow. Tell your preferred AI agent to invoke Trycycle by name to start the autonomous coordination, which manages artifact tracking and gating between the execution and review phases.

Can I chain planning and execution loops for autonomous AI pilots?▼

Yes, you can chain planning and execution loops for autonomous AI pilots. Trycycle orchestrates these end-to-end workflows with deterministic gating, ensuring consistent state transitions and artifact management so agents can operate autonomously as a cohesive, auditable automation loop.

What is the best way to maintain workflow state across multiple AI agents?▼

The best way to maintain workflow state is through workspace hygiene and artifact tracking. Trycycle enforces consistent workflow state by managing worktrees and tracking artifacts, ensuring deterministic gating between the planning, execution, and review phases of your multi-agent automation.