Follow-up to https://github.com/openai/codex/pull/18178, where we called
out enabling the await-holding lint as a follow-up.
The long-term goal is to enable Clippy coverage for async guards held
across awaits. This PR is intentionally only the first, low-risk cleanup
pass: it narrows obvious lock guard lifetimes and leaves
`codex-rs/Cargo.toml` unchanged so the lint is not enabled until the
remaining cases are fixed or explicitly justified. It intentionally
leaves the active-turn/turn-state locking pattern alone because those
checks and mutations need to stay atomic.
## Common fixes used here
These are the main patterns reviewers should expect in this PR, and they
are also the patterns to reach for when fixing future `await_holding_*`
findings:
- **Scope the guard to the synchronous work.** If the code only needs
data from a locked value, move the lock into a small block, clone or
compute the needed values, and do the later `.await` after the block.
- **Use direct one-line mutations when there is no later await.** Cases
like `map.lock().await.remove(&id)` are acceptable when the guard is
only needed for that single mutation and the statement ends before any
async work.
- **Drain or clone work out of the lock before notifying or awaiting.**
For example, the JS REPL drains pending exec senders into a local vector
and the websocket writer clones buffered envelopes before it serializes
or sends them.
- **Use a `Semaphore` only when serialization is intentional across
async work.** The test serialization guards intentionally span awaited
setup or execution, so using a semaphore communicates "one at a time"
without holding a mutex guard.
- **Remove the mutex when there is only one owner.** The PTY stdin
writer task owns `stdin` directly; the old `Arc<Mutex<_>>` did not
protect shared access because nothing else had access to the writer.
- **Do not split locks that protect an atomic invariant.** This PR
deliberately leaves active-turn/turn-state paths alone because those
checks and mutations need to stay atomic. Those cases should be fixed
separately with a design change or documented with `#[expect]`.
## What changed
- Narrow scoped async mutex guards in app-server, JS REPL, network
approval, remote-control websocket, and the RMCP test server.
- Replace test-only async mutex serialization guards with semaphores
where the guard intentionally lives across async work.
- Let the PTY pipe writer task own stdin directly instead of wrapping it
in an async mutex.
## Verification
- `just fix -p codex-core -p codex-app-server -p codex-rmcp-client -p
codex-shell-escalation -p codex-utils-pty -p codex-utils-readiness`
- `just clippy -p codex-core`
- `cargo test -p codex-core -p codex-app-server -p codex-rmcp-client -p
codex-shell-escalation -p codex-utils-pty -p codex-utils-readiness` was
run; the app-server suite passed, and `codex-core` failed in the local
sandbox on six otel approval tests plus
`suite::user_shell_cmd::user_shell_command_does_not_set_network_sandbox_env_var`,
which appear to depend on local command approval/default rules and
`CODEX_SANDBOX_NETWORK_DISABLED=1` in this environment.
## Summary
- preserve a small fs-helper runtime env allowlist (`PATH`, temp vars)
instead of launching the sandboxed helper with an empty env
- add unit coverage for the allowlist and transformed sandbox request
env
- add a Linux smoke test that starts the test exec-server with a fake
`bwrap` on `PATH`, runs a sandboxed fs write through the remote fs
helper path, and asserts that bwrap path was exercised
## Validation
- `cd /tmp/codex-worktrees/fs-helper-env-defaults/codex-rs && export
PATH=$HOME/code/openai/project/dotslash-gen/bin:$HOME/.local/bin:$PATH
&& bazel test --bes_backend= --bes_results_url=
//codex-rs/exec-server:exec-server-file_system-test
--test_filter=sandboxed_file_system_helper_finds_bwrap_on_preserved_path`
- `cd /tmp/codex-worktrees/fs-helper-env-defaults/codex-rs && export
PATH=$HOME/code/openai/project/dotslash-gen/bin:$HOME/.local/bin:$PATH
&& bazel test --bes_backend= --bes_results_url=
//codex-rs/exec-server:exec-server-unit-tests
--test_filter="helper_env|sandbox_exec_request_carries_helper_env"`
- earlier on this branch before the smoke-test harness adjustment: `cd
/tmp/codex-worktrees/fs-helper-env-defaults/codex-rs && export
PATH=$HOME/code/openai/project/dotslash-gen/bin:$HOME/.local/bin:$PATH
&& bazel test --bes_backend= --bes_results_url=
//codex-rs/exec-server:all`
Co-authored-by: Codex <noreply@openai.com>
## Summary
First PR in the split from #17956.
- adds the core/app-server `RateLimitReachedType` shape
- maps backend `rate_limit_reached_type` into Codex rate-limit snapshots
- carries the field through app-server notifications/responses and
generated schemas
- updates existing constructors/tests for the new optional field
## Validation
- `cargo test -p codex-backend-client`
- `cargo test -p codex-app-server-protocol`
- `cargo test -p codex-app-server rate_limits`
- `cargo test -p codex-tui workspace_`
- `cargo test -p codex-tui status_`
- `just fmt`
- `just fix -p codex-backend-client`
- `just fix -p codex-app-server-protocol`
- `just fix -p codex-app-server`
- `just fix -p codex-tui`
This PR moves `/plugins` onto the shared tabbed selection-list
infrastructure and introduces the new v2 menu. The menu now groups
plugins into All Plugins, Installed, OpenAI Curated, and per-marketplace
tabs.
- Rebuild /plugins on top of the shared tabbed selection list
- Add All Plugins, Installed, OpenAI Curated, and per-marketplace tabs
- Preserve active tab and selected-row behavior across popup refreshes
- Add duplicate marketplace tab-label disambiguation
- Update browse-mode popup tests and snapshots
Co-authored-by: Codex <noreply@openai.com>
# 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`
## Summary
- Move local MCP stdio process startup behind a launcher trait.
- Preserve existing local stdio behavior while making transport creation
explicit.
## Stack
```text
o #18027 [6/6] Fail exec client operations after disconnect
│
o #18212 [5/6] Wire executor-backed MCP stdio
│
@ #18087 [4/6] Abstract MCP stdio server launching
│
o #18020 [3/6] Add pushed exec process events
│
o #18086 [2/6] Support piped stdin in exec process API
│
o #18085 [1/6] Add MCP server environment config
│
o main
```
---------
Co-authored-by: Codex <noreply@openai.com>
Follow-up to https://github.com/openai/codex/pull/18178. This handles the straightforward await-holding cleanup first, without enabling the Clippy lint yet; the long-term goal is to enable the lint in a follow-up once the remaining cases are resolved or explicitly justified.
## Summary
PR Babysitter can reply directly to GitHub code review comments when
feedback is non-actionable, already addressed, or not valid. Those
replies should be visibly attributed so reviewers do not mistake an
automated Codex response for a message from the human operator.
This updates the skill instructions to require GitHub code review
replies from the babysitter to start with `[codex]`.
## Changes
- Adds the `[codex]` prefix requirement to the core PR Babysitter
workflow.
- Repeats the requirement in the review comment handling guidance where
agents decide whether to reply to a review thread.
## Summary
- Add a pushed `ExecProcessEvent` stream alongside retained
`process/read` output.
- Publish local and remote output, exit, close, and failure events.
- Cover the event stream with shared local/remote exec process tests.
## Testing
- `cargo check -p codex-exec-server`
- `cargo check -p codex-rmcp-client`
- Not run: `cargo test` per repo instruction; CI will cover.
## Stack
```text
o #18027 [6/6] Fail exec client operations after disconnect
│
o #18212 [5/6] Wire executor-backed MCP stdio
│
o #18087 [4/6] Abstract MCP stdio server launching
│
@ #18020 [3/6] Add pushed exec process events
│
o #18086 [2/6] Support piped stdin in exec process API
│
o #18085 [1/6] Add MCP server environment config
│
o main
```
---------
Co-authored-by: Codex <noreply@openai.com>
Follow-up to https://github.com/openai/codex/pull/18178. This handles the straightforward await-holding cleanup first, without enabling the Clippy lint yet; the long-term goal is to enable the lint in a follow-up once the remaining cases are resolved or explicitly justified.
To improve performance of UI loads from the app, add two main
improvements:
1. The `thread/list` api now gets a `sortDirection` request field and a
`backwardsCursor` to the response, which lets you paginate forwards and
backwards from a window. This lets you fetch the first few items to
display immediately while you paginate to fill in history, then can
paginate "backwards" on future loads to catch up with any changes since
the last UI load without a full reload of the entire data set.
2. Added a new `thread/turns/list` api which also has sortDirection and
backwardsCursor for the same behavior as `thread/list`, allowing you the
same small-fetch for immediate display followed by background fill-in
and resync catchup.
## Why
The Bazel workflow has multiple jobs that run concurrently for the same
target triple. In particular, the Windows `test`, `clippy`, and
`verify-release-build` jobs could all miss and then attempt to save the
same Bazel repository cache key:
```text
bazel-cache-${target}-${lockhash}
```
Because `actions/cache` entries are immutable, only one job can reserve
that key. The others can report failures such as:
```text
Failed to save: Unable to reserve cache with key bazel-cache-x86_64-pc-windows-gnullvm-..., another job may be creating this cache.
```
Adding only the workflow name would not separate these jobs because they
all run inside the same `Bazel` workflow. The key needs a job-level
namespace as well.
## What Changed
- Added a required `cache-scope` input to
`.github/actions/prepare-bazel-ci/action.yml`.
- Moved Bazel repository cache key construction into the shared action
and exposed the computed key as `repository-cache-key`.
- Exposed the exact restore result as `repository-cache-hit` so save
steps can skip exact cache hits.
- Updated `.github/workflows/bazel.yml` to pass `cache-scope: bazel-${{
github.job }}` for the `test`, `clippy`, and `verify-release-build`
jobs.
- The scoped restore key is now the only fallback. This avoids carrying
a temporary restore path for the old unscoped cache namespace.
## Verification
- Parsed `.github/actions/prepare-bazel-ci/action.yml` and
`.github/workflows/bazel.yml` with Ruby's YAML parser.
- `actionlint` is not installed in this workspace, so I could not run a
GitHub Actions semantic lint locally.
