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## Why
`selectedCapabilityRoots` is durable thread intent: “use this capability
root from environment `worker`.”
The important product assumption is:
> One environment ID always names the same logical executor and stable
contents.
`worker` does not silently change from executor A to an unrelated
executor B. The process-local connection handle for `worker` can still
be replaced while Codex is running, though, for example when
`environment/add` registers a fresh handle for the same logical
environment.
The thread should persist only the stable selection. Each model step
should pair that selection with the exact ready handle captured for that
step.
## The boundary
```text
persisted thread intent
plugin@1 -> environment "worker"
|
| capture the current step
v
model-step view
unavailable, or
plugin@1 + worker's exact captured ready handle
```
The environment ID is the stable identity and cache key. The
`Arc<Environment>` is only a process-local handle retained so consumers
of one model step use the same captured environment. It is never
persisted and it does not imply different environment contents.
## What changes
### Persist the stable selection
Selected roots are written into `SessionMeta` and restored with the
thread. Forked subagents inherit the same selections, including
bounded-history forks.
Only stable data is persisted: root ID, environment ID, and root path.
### Capture readiness together with the exact handle
The environment snapshot records:
```rust
environment_id -> Some(Arc<Environment>) // ready in this step
environment_id -> None // still starting in this step
```
This prevents readiness and execution from coming from different
registry snapshots.
For example:
```text
step snapshot: worker -> handle A, ready
environment/add: worker -> fresh handle B for the same logical environment
current step: plugin@1 still uses captured handle A
```
Without carrying handle A in the snapshot, the resolver could combine “A
was ready” with handle B and treat B as ready before it had finished
starting.
This does not change cache invalidation. Stable capability metadata
remains identified by environment ID and capability root. Replacing a
process-local handle under the same stable environment ID does not
invalidate or rediscover that metadata.
### Resolve availability per model step
- A ready captured environment produces resolved roots using its
captured handle.
- A starting, missing, or failed environment is omitted from that step.
- A selected lazy environment that is outside the turn's captured
environment set is asked to start, and a later step can observe it as
ready.
- No capability files are scanned here.
Transient transport disconnects remain the remote client's reconnect
concern. This PR models initial attachment/readiness; it does not add
live socket-connectivity state.
## Example
```text
thread selection: plugin@1 -> environment "worker"
step 1: worker is starting -> plugin@1 unavailable
step 2: worker is ready -> plugin@1 resolves through worker's captured handle
step 3: fresh local handle -> current step remains pinned; a later step captures its own view
```
Temporary unavailability does not discard the durable selection. Later
PRs can retain stable metadata caches while projecting only currently
available capabilities into model-visible World State.
## Compatibility
The app-server request shape does not change. Older rollouts without
`selected_capability_roots` deserialize to an empty list.
## Stack
1. **This PR:** persist stable selected roots and resolve them through
an exact model-step handle.
2. #29960: cache stable skill metadata and project available skills into
World State.
3. #29946: cache stable plugin declarations and manage the separate live
MCP runtime.
8f02973d25
·
2026-06-25 17:49:43 +00:00
7,842 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.