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Felipe Coury
48f117d0a2
# Summary This removes startup `skills/list` from the critical path to first input. In release measurements, median startup-to-input time improved from `307.5 ms` to `191.0 ms` across 30 measured runs with 5 warmups. # Background Startup currently waits for a forced `skills/list` app-server request before scheduling the first usable TUI frame. That makes skill metadata freshness part of the process-launch-to-input path, even though the prompt can safely accept normal input before skill metadata has finished loading. I measured startup from process launch until the TUI reports that the user can type. The measurement harness watched the startup measurement record, killed Codex after a successful sample, and enforced a timeout so repeated runs would not leave TUI processes behind. The debug runs had enough outliers that I used median as the primary signal and ran a baseline self-compare to understand the noise floor. # Why skills/list The `skills/list` cut was the best practical optimization because it improved startup without changing the important readiness contract: when the prompt is shown, it is still backed by an active session. Only enrichment data arrives later. | Candidate | Result | Decision | | --- | --- | --- | | Defer startup `skills/list` | Debug median improved from `524.0 ms` to `348.0 ms`; release median improved from `307.5 ms` to `191.0 ms`. | Keep | | Defer fresh `thread/start` | Debug median improved from `494.0 ms` to `256.0 ms`, but the prompt could appear before an active thread was attached. | Reject as too risky for this PR | | Avoid forced skills config reload | Debug median moved from `509.0 ms` to `512.0 ms`. | Reject as neutral | | Skip fresh history metadata | Debug median moved from `496.5 ms` to `531.5 ms`. | Reject as regression/noise | | Defer app-server startup | Not implemented because it would only permit a loading frame unless the TUI gained a deliberate pre-server state. | Out of scope | # Implementation `App::refresh_startup_skills` now clones the app-server request handle, spawns a background task, and issues the same forced `skills/list` request after the first frame is scheduled. When the request completes, the task sends `AppEvent::SkillsListLoaded` back through the normal app event queue. The existing skills response handling still converts the app-server response, updates the chat widget, and emits invalid `SKILL.md` warnings. Explicit user-initiated skills refreshes still use the existing synchronous app command path, so callers that intentionally requested fresh skill state do not race ahead of their own refresh. # Tradeoffs The main tradeoff is a narrow theoretical race at startup: skill mention completion depends on a background `skills/list` response, so it could briefly show stale or empty metadata if opened before that response arrives. In manual testing, pressing `$` as soon as possible after launch still showed populated skill metadata, so this risk appears minimal in normal use. Plain input remains available immediately, and the UI updates through the existing skills response path once the refresh completes. This PR does not change how skills are discovered, cached, force-reloaded, displayed, enabled, or warned about. It only changes when the startup refresh is allowed to complete relative to the first usable TUI frame. # Verification - `cargo test -p codex-tui`
48f117d0a2
·
2026-04-17 16:55:00 -03:00
5,500 Commits
npm i -g @openai/codex
or brew install --cask codex
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
Install globally with your preferred package manager:
# 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.