📌 Spotted on GitHub Trending: tirth8205/code-review-graph — let's break it down.

🔗 https://github.com/tirth8205/code-review-graph
📝 Local-first code intelligence graph for MCP and CLI. Builds a persistent map of your codebase so AI coding tools read only what matters, with benchmarked context reductions on reviews and large-repo workflows.
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Code Review Made Smart: The code-review-graph repository revolutionizes code reviews by building a structural map of your codebase and providing your AI assistant with precise context, reducing token waste and increasing efficiency.

Key features include:
- Incremental updates in under 2 seconds
- Broad language coverage, including support for Jupyter notebooks and the ability to add custom languages
- Risk-scored PR reviews in CI through a GitHub Action

To get started, simply run pip install code-review-graph and code-review-graph install to set up everything.

The repository boasts an impressive 82x median per-question token reduction across 6 real repositories, making it a game-changer for developers.

In short, code-review-graph is a must-have for any development team looking to streamline their code review process and make the most out of their AI assistants.
The punchy one-liner takeaway: Stop burning tokens, start reviewing smarter with code-review-graph.

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🧠 Channel: https://t.iss.one/GithubRe

🌟 1jehuang/jcode caught my eye on GitHub Trending today.

🔗 https://github.com/1jehuang/jcode
📝 The most intelligent agent harness for code
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The jcode project is a next-generation coding agent harness designed for multi-session workflows, infinite customizability, and performance. It's built to raise the skill ceiling, and its key features include infinite customizability and high performance. To get started with jcode, you can install it using a simple curl command or by using the provided PowerShell script for Windows.

One of the standout features of jcode is its resource efficiency, with a focus on optimizing every metric to the bone. This is particularly important for scaling multi-session workflows. The project includes detailed comparisons with other tools, showcasing its superiority in terms of RAM usage and boot-up time.

The jcode project is suitable for developers and power users looking to streamline their coding workflow. With its highly customizable and performant nature, it's an attractive option for those seeking to take their coding skills to the next level.

The project's technical highlights include a memory system that allows the agent to automatically recall relevant information, as well as explicit memory tools for active searching and storing of memories.

In a nutshell, jcode is the ultimate coding agent harness for those who want to code faster, better, and more efficiently - and it's available now!

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🧠 Channel: https://t.iss.one/GithubRe