smart-tree

🥈Silver

Smart Tree: not just a tree, a philosophy. A context-aware, AI-crafted replacement for 20+ tools with MEM8 quantum compression, semantic search, AST-smart editing, and partnership memory. Crafted with care by human + AI. accept no knock-offs.

230210Updated 5d ago

Intermediate30min to implementautomation

Saves ~300 min per use

Quick InstallView Source

git clone https://github.com/8b-is/smart-tree.git

Works with:

Claude

Overview

About This Skill

How to Use

[{"step":"Define the task and context. Replace [TASK], [PROJECT/TEAM], and [DOCUMENTS/FILES] in the prompt template with specific details. For example: 'Automate the refactor of the user authentication module for the 'SecureLogin' project.'","tip":"Be as specific as possible about the scope. Include file paths, repositories, or documentation links to narrow the semantic search."},{"step":"Run the Smart Tree system. Paste the customized prompt into your AI tool (e.g., Claude, ChatGPT) or execute it in your development environment if the Smart Tree is integrated as a CLI tool.","tip":"If using an AI tool, ensure it has access to your project files (e.g., via VS Code extension or file upload). For CLI tools, use flags like `--context-dir` to specify the search scope."},{"step":"Review the output. The AI will provide a summary of changes, modified files, and a pull request draft. Check for accuracy and alignment with your goals.","tip":"Use the MEM8-compressed summary to quickly verify the changes. If something is off, ask the AI to 're-run with stricter semantic constraints' or 'focus on [SPECIFIC_FILE].'"},{"step":"Integrate the changes. Apply the AST-smart edits to your codebase and merge the pull request. Use the partnership memory to ensure consistency with prior work.","tip":"If the Smart Tree is part of a CI/CD pipeline, the changes can be automatically applied and tested. Otherwise, manually review the diff before merging."},{"step":"Store the output for future reference. The MEM8 compression and partnership memory will automatically update, making future tasks faster and more consistent.","tip":"Encourage your team to use the same Smart Tree system for all similar tasks to build a robust partnership memory."}]

Setup & Installation

Quick Install

No install command available. Check the GitHub repository for manual installation instructions.

Alternative Install (Git Clone)

git clone https://github.com/8b-is/smart-tree

Requirements

Claude Code or compatible AI agent
Works with: Claude

Quick Start Guide

Install the Skill

Copy the install command above and run it in your terminal.

Open Your AI Agent

Launch Claude Code, Cursor, or your preferred AI coding agent.

Try It Out

Use the prompt template or examples below to test the skill.

Customize

Adapt the skill to your specific use case and workflow.

Usage Examples

Prompt Template

Act as a Smart Tree system to automate [TASK] for [PROJECT/TEAM]. Use semantic search to pull relevant context from [DOCUMENTS/FILES], then apply AST-smart editing to modify code/files as needed. Finally, use MEM8 quantum compression to summarize changes and partnership memory to ensure consistency with prior work. [ADDITIONAL_CONTEXT].

Example Output

For a project like 'E-Commerce Checkout Redesign', the Smart Tree system would:

1. **Semantic Search**: Scan 15+ repositories (React frontend, Python backend, SQL schemas) and 47 documentation files to identify all checkout-related components, APIs, and business logic. It flags a critical inconsistency in the `PaymentService` class where the `processPayment()` method’s return type differs between the frontend (Promise<boolean>) and backend (PaymentResult).

2. **AST-Smart Editing**: Using the Abstract Syntax Tree (AST) of both frontend and backend, it automatically refactors the `PaymentService` to return a standardized `PaymentResult` object across all layers. The system generates a diff showing 3 files modified (frontend: `PaymentService.ts`, backend: `payment_service.py`, schema: `payment_result.graphql`), with a 98% semantic match to prior refactors in the codebase.

3. **MEM8 Compression**: Compresses the changes into a 12-line summary: 'Standardized PaymentResult across checkout flow. Added validation for `transactionId` in `processPayment()`. Updated GraphQL schema to include `paymentStatus` enum. No breaking changes to existing integrations.' This summary is stored in partnership memory for future reference.

4. **Partnership Memory**: Cross-references with the team’s prior work on the 'User Authentication Overhaul' to ensure naming conventions (e.g., `snake_case` in Python, `camelCase` in JavaScript) are consistent. It also checks the Jira ticket #CHK-423 to confirm the refactor aligns with the sprint goal.

**Output**: A pull request draft with:
- 3 modified files (frontend/backend/schema)
- 12-line summary
- Link to MEM8-compressed changes
- Tagged reviewers based on prior partnership memory (e.g., @dev-lead for backend, @qa-lead for testing).