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## Why A selected executor environment can be unavailable in one model step and ready in the next. The model should see its skills only while that environment is ready, without rescanning stable files on every sample. The product assumption is simple: - an environment ID names one stable logical environment; - the selected root contents do not change during the thread. ## Behavior ```text E1 unavailable -> do not show E1 skills E1 ready -> discover once, cache, show through World State E1 unavailable -> hide skills, keep cache E1 ready again -> reuse cache, show skills again resume -> create a new thread cache and discover again ``` The cache key is the full `SelectedCapabilityRoot`. Availability does not invalidate it; dropping the extension's thread state does. The step supplies the ready selected roots directly. They do not have to be turn environments: ```text turn environment: laptop selected root: worker:/plugins/lint-fix worker ready -> lint-fix skills are visible ``` ## What changes - Keeps executor skill catalogs in the existing skills extension. - Passes the roots resolved as ready for the step into World State contributors. - Loads each ready selected root at most once per thread. - Contributes the executor catalog as the `skills` World State section. - Uses the exact step catalog for explicit skill selection and body reads. - Leaves host and orchestrator skill behavior where it already lives. Taking a step snapshot itself does not add an RPC. Executor filesystem calls happen only on the first discovery of a stable root for that thread. ## What does not change - No filesystem watcher or content-based invalidation. - No retry/generation framework. - No skill runtime migration into core. - No general rewrite of the skills extension. ## Stack 1. Extension-owned World State sections. 2. **This PR:** project cached executor skills through World State. 3. Pin one MCP runtime to each model step. 4. Project selected MCP/app/connector metadata by environment availability. 5. One end-to-end integration scenario.
5eebeb8169
·
2026-06-26 00:13:43 +01:00
7,863 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.