SeemSeam

SeemSeam / plan-tree

Public

Codex skill for maintaining structured planning document trees

28
4
85% credibility
Found May 26, 2026 at 28 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
AI Summary

Plan Tree is a planning skill designed for AI-assisted projects. It provides a structured way to maintain project plans that survive multiple sessions and work across different AI assistants. Instead of letting important decisions, open questions, and project direction get lost between conversations, plan-tree creates a durable 'control plane' where your AI assistant records goals, progress, decisions, and remaining questions. The methodology emphasizes that with AI handling implementation quickly, thoughtful planning becomes the most important part of any project. Users add a simple instruction rule to their AI assistant, which then automatically maintains an organized planning tree with sections for roadmaps, implementation status, decisions, topics, and history.

How It Works

1
💡 You notice something shifts with AI

When AI handles implementation fast, planning becomes the real key to success instead of just writing code

2
🌳 You discover plan-tree

A thoughtful way to keep your project plans alive, organized, and lasting across all your AI sessions

3
📝 You teach your AI assistant the skill

You add a simple memory rule that helps your AI understand how to maintain your project plans properly

4
🗺️ Your AI builds a living plan structure

It creates an organized space with your goals, decisions, open questions, and progress all in one place

5
🔄 Plans stay fresh automatically

Every time you chat with your AI, it updates the plan with new decisions, completed work, and any new questions

🎯 Your project stays on track and clear

No more lost context or forgotten decisions—everything lives in one organized, shared place between you and your AI

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Star Growth

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AI-Generated Review

What is plan-tree?

plan-tree is a portable AI planning skill that transforms temporary, session-local task plans into durable, structured Markdown planning trees. It solves the problem where AI-assisted development compresses implementation time so much that traditional "small planning, small execution" workflows break down. The skill maintains entry points, roadmaps, decisions, open questions, and implementation status across sessions and multiple agents. It's designed to be added to AI agent memory files and works with providers that support skill loading through YAML configuration.

Why is it gaining traction?

The project addresses a real pain point: as AI coding assistants make implementation faster, the bottleneck shifts to planning and coordination. plan-tree provides a semantic framework for capturing not just what to do next, but why decisions were made, what was rejected, and what remains unresolved. The hook is its focus on preserving project context and intent across sessions, preventing the "invisible drift" where code evolves but planning documentation doesn't keep pace. It also bridges existing planning documentation through registration and migration support.

Who should use this?

- Teams using AI coding assistants on complex, multi-session projects - Developers working on projects with frequent handoffs between team members or agents - Technical leads who need to maintain project context and decisions over time - Anyone frustrated with losing planning context between AI sessions

Verdict

With 28 stars and a credibility score of 0.8500000238418579%, plan-tree is a young but well-conceptualized tool. The documentation is solid and the use case is genuine, but the community is still small. Worth trying if you need structured planning for AI-assisted workflows, though treat it as an emerging solution rather than a mature one.

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