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freestylefly/CodexGuide

0
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3,970 stars·355 forks·TypeScript·MIT·2 viewscodexguide.ai↗

CodexGuide

CodexGuide is a documentation website and learning resource for the Codex AI coding assistant. It walks newcomers through an ordered reading path: installing, signing in, subscribing, configuring, and running a first low-risk task. The path then continues toward team use. It also helps readers compare the desktop app, command line, cloud, IDE, and chat entry points so they can choose the one that fits their workflow.

The guide is built around practical, checkable work. Its task recipes are copyable templates with defined inputs, outputs, and verification steps. They cover coding tasks such as Git use, testing, and CI repair, as well as slides, diagrams, browsers, notes, literature review, messaging, and design. Each task follows a loop of reading the project, editing files, running commands, testing, and checking the result. Separate guidance addresses writers, researchers, and other knowledge workers who use the assistant for non-coding work.

Configuration and safety are covered as their own topics: command-line options, configuration files, and project-level rule files that encode a repository's conventions, plus sandbox, approval, network, and credential boundaries that limit what the assistant can do. The guide also explains how to turn one successful task into shared templates, rules, case libraries, and review structures that a whole team can reuse.

Key pages carry last-checked dates tied to official documentation so time-sensitive details can be confirmed. The site is built as a static site that can be previewed with a local development server and published as plain files. A contribution guide covers submitting tutorials, reproducible cases, error fixes, and updates that follow changes in the official documentation.

Features

  • Beginner-to-Advanced Learning Paths - Takes newcomers through installing, signing in, subscribing, configuring, and a first low-risk task in an ordered path toward team use.
  • Coding Agent Usage Guides - Teaches readers how to install, configure, and use an AI coding assistant through tutorials, workflows, and reference notes.
  • Agentic Coding Workflows - Walks through coding tasks such as Git use, testing, and CI repair, with each result checkable.
  • AI Coding Assistant Guidance - Collects task recipes, rules, and safe-use practices for getting reliable results from an AI agent that edits code and runs commands.

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  • AI Task Recipes - Provides copyable task templates with defined inputs, outputs, and verification steps for coding, slides, research, and other workflows.
  • AI Assistant Configurations - Covers project rule files, configuration files, sandbox limits, and approvals that keep an AI coding assistant within repository conventions.
  • CLI Project Configuration Files - Teaches setting command-line options, configuration files, and project-level rule files so the assistant follows a repository's conventions.
  • Onboarding Guides - Walks beginners through installation, sign-in, configuration, and a first low-risk task, plus choosing the right interface.
  • Task Recipe Libraries - Provides copyable task templates for slides, diagrams, notes, literature review, and CI repair, each with inputs, outputs, and verification steps.
  • Agent Rule Files - Explains how command-line options, configuration files, and project rule files layer together to shape assistant behaviour in a repository.
  • Verifiable Agent Task Loops - Structures every task as read, edit, run, test, and check so each assistant output can be confirmed.
  • AI-Assisted Knowledge Work - Gives guidance for writers, researchers, and knowledge workers using the assistant for writing, slides, literature review, and notes.
  • Knowledge Work Assistants - Gives guidance for writers, researchers, and knowledge workers using the assistant for writing, slides, notes, and workflow automation.
  • Static Documentation Sites - Builds the guide's pages into a static site that can be previewed locally and published as plain files.
  • Team AI Asset Sharing - Shows how to turn one successful AI task into shared templates, rules, permission boundaries, and review practices for a team.
  • Learning Path Guides - Organises pages into an ordered route from beginner setup to team use so readers follow a guided path.
  • Interface Selection Guides - Compares desktop app, command line, cloud, IDE, and chat entry points so readers can choose the one that fits their workflow.
  • Step-by-Step Tutorials - Offers a guided, ordered walkthrough from first setup and sign-in through configuration to a first completed task.
  • Sandbox Permissions - Covers sandbox, approval, network, and credential boundaries that limit which files, commands, and resources the assistant can touch.
  • Scoped Sandbox Host Access - Explains how to limit the assistant's file access, commands, network use, and credentials through sandbox and approval boundaries.
  • Shared Team Standards - Explains how to capture a successful task as shared templates, rules, case libraries, and review structures a team can reuse.

    • Star history

    Star history chart for freestylefly/codexguideStar history chart for freestylefly/codexguide

    How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.

    Frequently asked questions

    What does freestylefly/codexguide do?

    CodexGuide is a documentation website and learning resource for the Codex AI coding assistant. It walks newcomers through an ordered reading path: installing, signing in, subscribing, configuring, and running a first low-risk task. The path then continues toward team use. It also helps readers compare the desktop app, command line, cloud, IDE, and chat entry points so they can choose the one that fits their workflow.

    What are the main features of freestylefly/codexguide?

    The main features of freestylefly/codexguide are: Beginner-to-Advanced Learning Paths, Coding Agent Usage Guides, Agentic Coding Workflows, AI Coding Assistant Guidance, AI Task Recipes, AI Assistant Configurations, CLI Project Configuration Files, Onboarding Guides.

    Which projects share features with freestylefly/codexguide?

    Projects with overlapping indexed features include: rivet-dev/agentos — Agent OS is a lightweight sandbox runtime for running code written by AI agents. It provides a virtualized POSIX… meta/astryx — Astryx is an open-source React design system built from typed, accessible components styled with StyleX. The library… astrid-runtime/handbook — This repository is the contributor handbook for the Astrid runtime, a runtime split across many separate repositories.… bozhoudev/codex-orange-book — This is an unofficial, open-source Chinese-language handbook for the Codex AI coding agent, distributed as a… saladday/cc-switch-cli — cc-switch-cli is a cross-platform command-line tool, written in Rust, that manages provider, prompt, MCP server and… twostraws/swiftui-agent-skill — SwiftUI Agent Skill is a set of plain-text instruction files that teach AI coding assistants to write simpler, more…

    Projects sharing features with CodexGuide

    These projects share indexed features with CodexGuide. Shared tags can include platform or build tooling; verify the primary use case before treating a result as a replacement.
    • rivet-dev/agentosrivet-dev avatar

      rivet-dev/agentos

      4,858View on GitHub↗

      Agent OS is a lightweight sandbox runtime for running code written by AI agents. It provides a virtualized POSIX userspace inside WebAssembly, with processes, signals, files, sockets, a shell, and core utilities, so unmodified Linux programs and Node.js, TypeScript, and Python scripts execute in isolation from the host. It is used as an embeddable library inside an existing backend process, or through a hosted HTTP API. Many isolated environments run inside one compact runtime on ordinary Linux hosts, with no hypervisor, nested virtualization, or full virtual machine per agent. Every file, pr

      Rustagentaijavascript
      View on GitHub↗4,858
    • meta/astryxmeta avatar

      meta/astryx

      14,432View on GitHub↗

      Astryx is an open-source React design system built from typed, accessible components styled with StyleX. The library ships with pre-built CSS and requires no build plugin for basic use. It is paired with a command-line tool that looks up component documentation, scaffolds starter apps and page templates, applies codemods for version migrations, and ejects component source into a project for direct modification. The system is written to be used by AI coding agents as well as people. Component indexes and guidance can be written into agent instruction files, and the CLI returns a self-describin

      TypeScript
      View on GitHub↗14,432
    • astrid-runtime/handbookastrid-runtime avatar

      astrid-runtime/handbook

      7,390View on GitHub↗

      This repository is the contributor handbook for the Astrid runtime, a runtime split across many separate repositories. It explains how to contribute: where each piece of code lives, how the parts fit together, and which rules govern changes. The handbook is written as source files and compiled into a searchable, browsable online book. The guidance covers the project's contribution governance. Contributors choose a contribution tier that matches the scope of their change, and they sign their commits. Core pull requests are linked to closed issues, and contributors review their own changes adve

      View on GitHub↗7,390
    • bozhoudev/codex-orange-bookbozhouDev avatar

      bozhouDev/codex-orange-book

      3,506View on GitHub↗

      This is an unofficial, open-source Chinese-language handbook for the Codex AI coding agent, distributed as a downloadable PDF alongside its source. It walks readers from first installation through full project delivery, explaining how an agent reads project files, plans work, edits code, runs commands and returns changes as diffs for human review, and how that differs from a conversational chat assistant. The book covers the ways of reaching the agent: the desktop app, command line, editor sidebars such as VS Code, Cursor and Windsurf, and a cloud runner connected to a GitHub repository. It a

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