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## Summary This switches skill discovery to the simpler same-connection scalar request shape. After reading a skills directory, discovery now starts the existing `fs/getMetadata` calls for all visible entries in that directory before awaiting the results. There is no JSON-RPC batch frame and no new filesystem API; remote filesystems use the existing request-id multiplexing on the same exec-server connection. This is the scoped alternative to the batch-frame approach in #29074 / #29075. ## What changed - Collect visible directory entries before processing them. - Run their existing `fs.get_metadata(...)` calls with `join_all`. - Process the results in the original directory order, so skill discovery behavior stays the same. ## Benchmarks Fresh local benchmark against generated skill trees over a real exec-server remote filesystem. The benchmark calls the actual `load_skills_from_roots` path, so this includes directory reads, metadata stats, `SKILL.md` reads, and parsing. Times are p50 milliseconds from 5 samples after 1 warmup, using warmed runs. | Scenario | Legacy `main` | Batch frame stack (#29074 / #29075) | Same-connection scalar stack | | --- | ---: | ---: | ---: | | 100 flat skills | 377.4 | 389.0 | 378.6 | | 500 flat skills | 1983.2 | 1856.6 | 1757.5 | Takeaway: for the actual skill discovery path, same-connection scalar is tied with legacy at 100 skills and best at 500 skills. The batch-frame stack does not show enough win here to justify the extra protocol/API surface. Benchmark command: - `just test -p codex-exec-server benchmark_remote_skill_discovery --run-ignored ignored-only --no-capture` Checked locally with: - `just test -p codex-core-skills` - `just bazel-lock-update` - `just bazel-lock-check`
c2fbf4247a
·
2026-06-21 14:04:18 +02:00
7,654 Commits
Codex CLI is a coding agent from OpenAI that runs locally on your computer.
If you want Codex in your code editor (VS Code, Cursor, Windsurf), install in your IDE.
If you want the desktop app experience, run
codex app or visit the Codex App page.
If you are looking for the cloud-based agent from OpenAI, Codex Web, go to chatgpt.com/codex.
Quickstart
Installing and running Codex CLI
Run the following on Mac or Linux to install Codex CLI:
curl -fsSL https://chatgpt.com/codex/install.sh | sh
Run the following on Windows to install Codex CLI:
powershell -ExecutionPolicy ByPass -c "irm https://chatgpt.com/codex/install.ps1 | iex"
Codex CLI can also be installed via the following package managers:
# Install using npm
npm install -g @openai/codex
# Install using Homebrew
brew install --cask codex
Then simply run codex to get started.
You can also go to the latest GitHub Release and download the appropriate binary for your platform.
Each GitHub Release contains many executables, but in practice, you likely want one of these:
- macOS
- Apple Silicon/arm64:
codex-aarch64-apple-darwin.tar.gz - x86_64 (older Mac hardware):
codex-x86_64-apple-darwin.tar.gz
- Apple Silicon/arm64:
- Linux
- x86_64:
codex-x86_64-unknown-linux-musl.tar.gz - arm64:
codex-aarch64-unknown-linux-musl.tar.gz
- x86_64:
Each archive contains a single entry with the platform baked into the name (e.g., codex-x86_64-unknown-linux-musl), so you likely want to rename it to codex after extracting it.
Using Codex with your ChatGPT plan
Run codex and select Sign in with ChatGPT. We recommend signing into your ChatGPT account to use Codex as part of your Plus, Pro, Business, Edu, or Enterprise plan. Learn more about what's included in your ChatGPT plan.
You can also use Codex with an API key, but this requires additional setup.
Docs
This repository is licensed under the Apache-2.0 License.