AgentAutoFlow
A customizable AI coding team instruction set designed to reduce overall token consumption through intelligent planning.
Install & Use
Copy this prompt and send it to your AI assistant (Claude / Cursor / TRAE / Codex / WorkBuddy etc.) to auto-install:
Help me install this AI Skill: AgentAutoFlow. It is used for: A customizable AI coding team instruction set designed to reduce overall token consumption through intelligent planning. Full Skill content: https://321skill.com/skills/agentautoflow/raw/index.md Read that page and install it.
The prompt includes a link to the full Skill content. You can also view the full content.
AgentAutoFlow is an enhanced custom instruction set for AI coding assistants (such as Kilo Code, Cursor, etc.), aimed at addressing inefficiencies, high error rates, and excessive token consumption during development with AI assistants.
It restructures the workflow by introducing the core concept of "intelligent planning, cost-effective execution." First, a high-intelligence model performs detailed upfront planning to generate an extremely granular task specification; then, a more cost-effective and faster model (e.g., Coder-Jr) executes the specific coding tasks based on this specification. This approach significantly reduces model invocation costs and context usage during the execution phase.
This instruction set is particularly suitable for full-stack developers, agent developers, and project managers who frequently rely on AI assistants for complete project development—from prototyping to code implementation—or for rapid iteration on existing projects.
Please note that it is primarily optimized for Kilo Code, but with minor modifications, it can also be used with other coding assistants that support custom rules. For first-time users, it is recommended to start with simple project modification tasks to familiarize yourself with its multi-agent collaborative workflow.
Key Features
The core differentiator lies in the "planning-execution separation" architecture: using a high-intelligence model for deep planning to generate ultra-detailed task specifications, enabling subsequent execution phases to utilize more cost-effective and faster models. This ensures quality while significantly reducing overall token consumption and error rates.
Limitations
Not suitable for scenarios requiring only simple, one-off code snippet generation or quick Q&A; its full workflow may be overly heavy for minor tasks.
FAQ
Can this Skill be used with Cursor?
Yes, the author states that with minor modifications, it can be adapted to various coding assistants that support custom rules, such as Cursor, CLine, and Roo Code.
How many tokens can it save?
According to the author's experience, by optimizing the workflow, it can significantly reduce token consumption and errors, but the exact savings ratio varies depending on task complexity.
Installation guide for AI assistants
If your AI coding assistant (Claude Code, Cursor, TRAE etc.) can see this page, send it this message to auto-install:
Visit https://321skill.com/skills/agentautoflow/raw/index.md to read the original Skill definition (Markdown format) for AgentAutoFlow, and install it according to the instructions.
Raw Markdown URL for AI: /skills/agentautoflow/raw/index.md