explaingit

cclank/x-algorithm-wiki

Analysis updated 2026-06-24

146HTMLAudience · researcherComplexity · 2/5Setup · easy

TLDR

Community wiki of 34 cross linked Markdown pages explaining the open source X (Twitter) For You recommendation system with file and line references back to the xai-org/x-algorithm source.

Mindmap

mindmap
  root((x-algorithm-wiki))
    Inputs
      xai-org x-algorithm source
      Rust structs
      Python inference scripts
    Outputs
      Markdown wiki
      Mermaid diagrams
      Plain language tour
    Use Cases
      Understand For You ranking
      Debunk shadowban myths
      Onboard to recsys code
    Tech Stack
      Markdown
      Mermaid
      Obsidian
      HTML
Click or tap to explore — scroll the page freely

Code map

Detail Auto

An interactive map of this repo's files and how they connect — its source is parsed live in your browser. Click Visualize to build it.

filefunction / class

What do people build with it?

USE CASE 1

Read a plain language tour of how X picks the next post in the For You timeline

USE CASE 2

Trace shadowban and cold start behaviour back to specific lines in the xai-org source

USE CASE 3

Onboard to the Phoenix ranking model and Thunder post store before contributing to x-algorithm

What is it built with?

MarkdownMermaidObsidian

How does it compare?

cclank/x-algorithm-wikilimin112/wechat-publish-templatealiu-airobot/eseilane
Stars146149136
LanguageHTMLHTMLHTML
Setup difficultyeasyeasymoderate
Complexity2/51/53/5
Audienceresearcherwriterdeveloper

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · easy Time to first run · 5min

Pages are Obsidian friendly, open the folder in Obsidian or use the hosted preview site for the best navigation.

In plain English

This repository is a documentation wiki, not running code, that explains the open-source X (Twitter) For You recommendation system in detail. The author read through the xai-org/x-algorithm source code at a specific commit and wrote up what each part does, with file and line-number references back to the original code so readers can check the claims themselves. The wiki is organized as 34 cross-linked Markdown pages totalling over 6,800 lines. Eleven of them are a plain-language tour for readers who do not want to read code, covering questions like how a post is picked, what data the algorithm uses, what shadowbanning actually looks like in the source, how cold-start treats new accounts, and a list of popular myths held up against what the code actually says. The remaining pages go into technical depth on the five components that make up For You: an orchestration layer, the candidate pipeline framework, the in-network post store called Thunder, the machine-learning retrieval and ranking stack called Phoenix with a Grok-style transformer, and the content-understanding service Grox with classifiers and multimodal embedders. It also includes five entity-reference pages that walk through specific Rust structs and Python scripts, such as the candidate pipeline executor, the Phoenix ranking and retrieval model constructors, the Thunder PostStore, and an end-to-end inference script. The README points to a hosted preview site that renders the wiki with a sidebar, and notes that the files are designed to be opened directly in Obsidian using its wiki-link navigation. Pages include real code snippets, Mermaid diagrams, design-decision notes, and FAQs. It is community-made, not official xAI documentation, and is based on a specific source-code snapshot tagged in the README.

Copy-paste prompts

Prompt 1
Summarize what the wiki says about how the Phoenix ranking model scores candidate posts in For You
Prompt 2
List every page in the wiki that touches shadowbanning and quote the relevant source line references
Prompt 3
Open this wiki in Obsidian and explain how the candidate pipeline executor flows into the Thunder PostStore
Prompt 4
Compare the wiki's description of cold start treatment for new accounts with what the actual Rust code does
Prompt 5
Generate a Mermaid diagram of the five For You components based on the orchestration page of this wiki

Frequently asked questions

What is x-algorithm-wiki?

Community wiki of 34 cross linked Markdown pages explaining the open source X (Twitter) For You recommendation system with file and line references back to the xai-org/x-algorithm source.

What language is x-algorithm-wiki written in?

Mainly HTML. The stack also includes Markdown, Mermaid, Obsidian.

How hard is x-algorithm-wiki to set up?

Setup difficulty is rated easy, with roughly 5min to a first successful run.

Who is x-algorithm-wiki for?

Mainly researcher.

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