What is the primary purpose of the pl4n skill?

The pl4n skill orchestrates multiple AI agents to collaboratively create, review, and refine highly detailed implementation plans for software projects.

What AI models does the pl4n ensemble use?

Pl4n typically orchestrates an ensemble involving Claude (via Claude Code) and OpenAI models to provide diverse perspectives and peer-review capabilities.

How do I start a new planning session in Claude Code?

You can start a session by using the `/pl4n:plan` slash command or by running `pl4n init "your task description"` directly in the terminal.

Can I provide feedback to the agents during the planning process?

Yes, the workflow is designed for iterative human review. You can edit the generated turn files in the .pl4n/sessions directory and then use the 'continue' command to let the agents process your feedback.

How does pl4n handle plan finalization?

Once you are satisfied with the synthesized plan, the 'approve' command locks the session and creates a PLAN.md symlink in your project root for easy reference.

Pl4n Multi-Agent Planner

Name: Pl4n Multi-Agent Planner
Author: gbasin

bygbasin

Productividad y Flujo de Trabajo

Orchestrates multi-agent AI ensembles to generate, refine, and finalize comprehensive implementation plans for complex software tasks.

Acerca de

Pl4n is a specialized planning orchestration tool that leverages an ensemble of AI agents, including Claude and OpenAI models, to build rigorous technical roadmaps. It replaces manual task listing with an iterative, turn-based workflow where agents draft, peer-review, and synthesize implementation strategies. This skill allows developers to manage the entire planning lifecycle directly within Claude Code—from initial task discovery and risk assessment to the generation of a finalized PLAN.md—ensuring complex features are thoroughly vetted before implementation begins.

Características Principales

Multi-agent ensemble planning using Claude and OpenAI models
Iterative human-in-the-loop refinement with turn-based session management
Automated risk assessment and technical dependency mapping
Session state tracking with diffing capabilities between planning turns
Standardized PLAN.md generation with symlinked session history
0 GitHub stars

Casos de Uso

Decomposing large feature requests into actionable, ordered task lists
Conducting multi-agent peer reviews on proposed architectural changes
Generating standardized technical specifications for team-wide implementation

Acerca de

Características Principales

Multi-agent ensemble planning using Claude and OpenAI models
Iterative human-in-the-loop refinement with turn-based session management
Automated risk assessment and technical dependency mapping
Session state tracking with diffing capabilities between planning turns
Standardized PLAN.md generation with symlinked session history
0 GitHub stars

Casos de Uso

Decomposing large feature requests into actionable, ordered task lists
Conducting multi-agent peer reviews on proposed architectural changes
Generating standardized technical specifications for team-wide implementation