Send input now sends messages as assistant message and with this format:
```
author: /root/worker_a
recipient: /root/worker_a/tester
other_recipients: []
Content: bla bla bla. Actual content. Only text for now
```
## Summary
- queue input after the user submits `/compact` until that manual
compact turn ends
- mirror the same behavior in the app-server TUI
- add regressions for input queued before compact starts and while it is
running
Co-authored-by: Codex <noreply@openai.com>
- Split the feature system into a new `codex-features` crate.
- Cut `codex-core` and workspace consumers over to the new config and
warning APIs.
Co-authored-by: Ahmed Ibrahim <219906144+aibrahim-oai@users.noreply.github.com>
Co-authored-by: Codex <noreply@openai.com>
## Summary
Some background. We're looking to instrument GA turns end to end. Right
now a big gap is grouping mcp tool calls with their codex sessions. We
send session id and turn id headers to the responses call but not the
mcp/wham calls.
Ideally we could pass the args as headers like with responses, but given
the setup of the rmcp client, we can't send as headers without either
changing the rmcp package upstream to allow per request headers or
introducing a mutex which break concurrency. An earlier attempt made the
assumption that we had 1 client per thread, which allowed us to set
headers at the start of a turn. @pakrym mentioned that this assumption
might break in the near future.
So the solution now is to package the turn metadata/session id into the
_meta field in the post body and pull out in codex-backend.
- send turn metadata to MCP servers via `tools/call` `_meta` instead of
assuming per-thread request headers on shared clients
- preserve the existing `_codex_apps` metadata while adding
`x-codex-turn-metadata` for all MCP tool calls
- extend tests to cover both custom MCP servers and the codex apps
search flow
---------
Co-authored-by: Codex <noreply@openai.com>
- Move core/src/terminal.rs and its tests into a standalone
terminal-detection workspace crate.
- Update direct consumers to depend on codex-terminal-detection and
import terminal APIs directly.
---------
Co-authored-by: Codex <noreply@openai.com>
## Summary
Persist Stop-hook continuation prompts as `user` messages instead of
hidden `developer` messages + some requested integration tests
This is a followup to @pakrym 's comment in
https://github.com/openai/codex/pull/14532 to make sure stop-block
continuation prompts match training for turn loops
- Stop continuation now writes `<hook_prompt hook_run_id="...">stop
hook's user prompt<hook_prompt>`
- Introduces quick-xml dependency, though we already indirectly depended
on it anyway via syntect
- This PR only has about 500 lines of actual logic changes, the rest is
tests/schema
## Testing
Example run (with a sessionstart hook and 3 stop hooks) - this shows
context added by session start, then two stop hooks sending their own
additional prompts in a new turn. The model responds with a single
message addressing both. Then when that turn ends, the hooks detect that
they just ran using `stop_hook_active` and decide not to infinite loop
test files for this (unzip, move codex -> .codex):
[codex.zip](https://github.com/user-attachments/files/26075806/codex.zip)
```
› cats
• Running SessionStart hook: lighting the observatory
SessionStart hook (completed)
warning: Hi, I'm a session start hook for wizard-tower (startup).
hook context: A wimboltine stonpet is an exotic cuisine from hyperspace
• Cats are tiny zen wizards, my friend: equal parts nap, mystery, and chaos. If you want, we can talk
cat facts, cat breeds, cat names, or build something cat-themed in this repo.
• Running Stop hook: checking the tower wards
• Running Stop hook: sacking the guards
• Running Stop hook: hiring the guards
Stop hook (completed)
warning: Wizard Tower Stop hook reviewed the completed reply (177 chars).
Stop hook (blocked)
warning: Wizard Tower Stop hook continuing conversation
feedback: cook the stonpet
Stop hook (blocked)
warning: Wizard Tower Stop hook continuing conversation
feedback: eat the cooked stonpet
• Stonpet’s cooked, aloha style: flash-seared over a blue quasiflame, glazed with nebula salt, and
rested until the hyperspace juices settle.
Now we eat with gratitude, my friend. One mindful bite in, and the flavor is pure cosmic surf:
smoky, bright, and totally out of this dimension.
• Running Stop hook: checking the tower wards
• Running Stop hook: sacking the guards
• Running Stop hook: hiring the guards
Stop hook (completed)
warning: Wizard Tower Stop hook reviewed the completed reply (285 chars).
Stop hook (completed)
warning: Wizard Tower Stop hook saw a second pass and stayed calm to avoid a loop.
Stop hook (completed)
warning: Wizard Tower Stop hook saw a second pass and stayed calm to avoid a loop.
```
The idea is that codex-exec exposes an Environment struct with services
on it. Each of those is a trait.
Depending on construction parameters passed to Environment they are
either backed by local or remote server but core doesn't see these
differences.
## Summary
- forward request-scoped task headers through MCP tool metadata lookups
and tool calls
- apply those headers to streamable HTTP initialize, tools/list, and
tools/call requests
- update affected rmcp/core tests for the new request_headers plumbing
## Testing
- cargo test -p codex-rmcp-client
- cargo test -p codex-core (fails on pre-existing unrelated error in
core/src/auth_env_telemetry.rs: missing websocket_connect_timeout_ms in
ModelProviderInfo initializer)
- just fix -p codex-rmcp-client
- just fix -p codex-core (hits the same unrelated auth_env_telemetry.rs
error)
- just fmt
---------
Co-authored-by: Codex <noreply@openai.com>
Resubmit https://github.com/openai/codex/pull/15020 with correct
content.
1. Use requirement-resolved config.features as the plugin gate.
2. Guard plugin/list, plugin/read, and related flows behind that gate.
3. Skip bad marketplace.json files instead of failing the whole list.
4. Simplify plugin state and caching.
1. Use requirement-resolved config.features as the plugin gate.
2. Guard plugin/list, plugin/read, and related flows behind that gate.
3. Skip bad marketplace.json files instead of failing the whole list.
4. Simplify plugin state and caching.
## Summary
If a subagent requests approval, and the user persists that approval to
the execpolicy, it should (by default) propagate. We'll need to rethink
this a bit in light of coming Permissions changes, though I think this
is closer to the end state that we'd want, which is that execpolicy
changes to one permissions profile should be synced across threads.
## Testing
- [x] Added integration test
---------
Co-authored-by: Codex <noreply@openai.com>
- this allows blocking the user's prompts from executing, and also
prevents them from entering history
- handles the edge case where you can both prevent the user's prompt AND
add n amount of additionalContexts
- refactors some old code into common.rs where hooks overlap
functionality
- refactors additionalContext being previously added to user messages,
instead we use developer messages for them
- handles queued messages correctly
Sample hook for testing - if you write "[block-user-submit]" this hook
will stop the thread:
example run
```
› sup
• Running UserPromptSubmit hook: reading the observatory notes
UserPromptSubmit hook (completed)
warning: wizard-tower UserPromptSubmit demo inspected: sup
hook context: Wizard Tower UserPromptSubmit demo fired. For this reply only, include the exact
phrase 'observatory lanterns lit' exactly once near the end.
• Just riding the cosmic wave and ready to help, my friend. What are we building today? observatory
lanterns lit
› and [block-user-submit]
• Running UserPromptSubmit hook: reading the observatory notes
UserPromptSubmit hook (stopped)
warning: wizard-tower UserPromptSubmit demo blocked the prompt on purpose.
stop: Wizard Tower demo block: remove [block-user-submit] to continue.
```
.codex/config.toml
```
[features]
codex_hooks = true
```
.codex/hooks.json
```
{
"hooks": {
"UserPromptSubmit": [
{
"hooks": [
{
"type": "command",
"command": "/usr/bin/python3 .codex/hooks/user_prompt_submit_demo.py",
"timeoutSec": 10,
"statusMessage": "reading the observatory notes"
}
]
}
]
}
}
```
.codex/hooks/user_prompt_submit_demo.py
```
#!/usr/bin/env python3
import json
import sys
from pathlib import Path
def prompt_from_payload(payload: dict) -> str:
prompt = payload.get("prompt")
if isinstance(prompt, str) and prompt.strip():
return prompt.strip()
event = payload.get("event")
if isinstance(event, dict):
user_prompt = event.get("user_prompt")
if isinstance(user_prompt, str):
return user_prompt.strip()
return ""
def main() -> int:
payload = json.load(sys.stdin)
prompt = prompt_from_payload(payload)
cwd = Path(payload.get("cwd", ".")).name or "wizard-tower"
if "[block-user-submit]" in prompt:
print(
json.dumps(
{
"systemMessage": (
f"{cwd} UserPromptSubmit demo blocked the prompt on purpose."
),
"decision": "block",
"reason": (
"Wizard Tower demo block: remove [block-user-submit] to continue."
),
}
)
)
return 0
prompt_preview = prompt or "(empty prompt)"
if len(prompt_preview) > 80:
prompt_preview = f"{prompt_preview[:77]}..."
print(
json.dumps(
{
"systemMessage": (
f"{cwd} UserPromptSubmit demo inspected: {prompt_preview}"
),
"hookSpecificOutput": {
"hookEventName": "UserPromptSubmit",
"additionalContext": (
"Wizard Tower UserPromptSubmit demo fired. "
"For this reply only, include the exact phrase "
"'observatory lanterns lit' exactly once near the end."
),
},
}
)
)
return 0
if __name__ == "__main__":
raise SystemExit(main())
```
Adds an environment crate and environment + file system abstraction.
Environment is a combination of attributes and services specific to
environment the agent is connected to:
File system, process management, OS, default shell.
The goal is to move most of agent logic that assumes environment to work
through the environment abstraction.
CXC-410 Emit Env Var Status with `/feedback` report
Add more observability on top of #14611
[Unset](https://openai.sentry.io/issues/7340419168/?project=4510195390611458&query=019cfa8d-c1ba-7002-96fa-e35fc340551d&referrer=issue-stream)
[Set](https://openai.sentry.io/issues/7340426331/?project=4510195390611458&query=019cfa91-aba1-7823-ab7e-762edfbc0ed4&referrer=issue-stream)
<img width="1063" height="610" alt="image"
src="https://github.com/user-attachments/assets/937ab026-1c2d-4757-81d5-5f31b853113e"
/>
###### Summary
- Adds auth-env telemetry that records whether key auth-related env
overrides were present on session start and request paths.
- Threads those auth-env fields through `/responses`, websocket, and
`/models` telemetry and feedback metadata.
- Buckets custom provider `env_key` configuration to a safe
`"configured"` value instead of emitting raw config text.
- Keeps the slice observability-only: no raw token values or raw URLs
are emitted.
###### Rationale (from spec findings)
- 401 and auth-path debugging needs a way to distinguish env-driven auth
paths from sessions with no auth env override.
- Startup and model-refresh failures need the same auth-env diagnostics
as normal request failures.
- Feedback and Sentry tags need the same auth-env signal as OTel events
so reports can be triaged consistently.
- Custom provider config is user-controlled text, so the telemetry
contract must stay presence-only / bucketed.
###### Scope
- Adds a small `AuthEnvTelemetry` bundle for env presence collection and
threads it through the main request/session telemetry paths.
- Does not add endpoint/base-url/provider-header/geo routing attribution
or broader telemetry API redesign.
###### Trade-offs
- `provider_env_key_name` is bucketed to `"configured"` instead of
preserving the literal configured env var name.
- `/models` is included because startup/model-refresh auth failures need
the same diagnostics, but broader parity work remains out of scope.
- This slice keeps the existing telemetry APIs and layers auth-env
fields onto them rather than redesigning the metadata model.
###### Client follow-up
- Add the separate endpoint/base-url attribution slice if routing-source
diagnosis is still needed.
- Add provider-header or residency attribution only if auth-env presence
proves insufficient in real reports.
- Revisit whether any additional auth-related env inputs need safe
bucketing after more 401 triage data.
###### Testing
- `cargo test -p codex-core emit_feedback_request_tags -- --nocapture`
- `cargo test -p codex-core
collect_auth_env_telemetry_buckets_provider_env_key_name -- --nocapture`
- `cargo test -p codex-core
models_request_telemetry_emits_auth_env_feedback_tags_on_failure --
--nocapture`
- `cargo test -p codex-otel
otel_export_routing_policy_routes_api_request_auth_observability --
--nocapture`
- `cargo test -p codex-otel
otel_export_routing_policy_routes_websocket_connect_auth_observability
-- --nocapture`
- `cargo test -p codex-otel
otel_export_routing_policy_routes_websocket_request_transport_observability
-- --nocapture`
- `cargo test -p codex-core --no-run --message-format short`
- `cargo test -p codex-otel --no-run --message-format short`
---------
Co-authored-by: Codex <noreply@openai.com>
## What is flaky
The Windows shell-driven integration tests in `codex-rs/core` were
intermittently unstable, especially:
- `apply_patch_cli_can_use_shell_command_output_as_patch_input`
- `websocket_test_codex_shell_chain`
- `websocket_v2_test_codex_shell_chain`
## Why it was flaky
These tests were exercising real shell-tool flows through whichever
shell Codex selected on Windows, and the `apply_patch` test also nested
a PowerShell read inside `cmd /c`.
There were multiple independent sources of nondeterminism in that setup:
- The test harness depended on the model-selected Windows shell instead
of pinning the shell it actually meant to exercise.
- `cmd.exe /c powershell.exe -Command "..."` is quoting-sensitive; on CI
that could leave the read command wrapped as a literal string instead of
executing it.
- Even after getting the quoting right, PowerShell could emit CLIXML
progress records like module-initialization output onto stdout.
- The `apply_patch` test was building a patch directly from shell
stdout, so any quoting artifact or progress noise corrupted the patch
input.
So the failures were driven by shell startup and output-shape variance,
not by the `apply_patch` or websocket logic themselves.
## How this PR fixes it
- Add a test-only `user_shell_override` path so Windows integration
tests can pin `cmd.exe` explicitly.
- Use that override in the websocket shell-chain tests and in the
`apply_patch` harness.
- Change the nested Windows file read in
`apply_patch_cli_can_use_shell_command_output_as_patch_input` to a UTF-8
PowerShell `-EncodedCommand` script.
- Run that nested PowerShell process with `-NonInteractive`, set
`$ProgressPreference = 'SilentlyContinue'`, and read the file with
`[System.IO.File]::ReadAllText(...)`.
## Why this fix fixes the flakiness
The outer harness now runs under a deterministic shell, and the inner
PowerShell read no longer depends on fragile `cmd` quoting or on
progress output staying quiet by accident. The shell tool returns only
the file contents, so patch construction and websocket assertions depend
on stable test inputs instead of on runner-specific shell behavior.
---------
Co-authored-by: Ahmed Ibrahim <219906144+aibrahim-oai@users.noreply.github.com>
Co-authored-by: Codex <noreply@openai.com>
It now supports:
- Connectors that are from installed and enabled plugins that are not
installed yet
- Plugins that are on the allowlist that are not installed yet.
## Description
This PR fixes a bad first-turn failure mode in app-server when the
startup websocket prewarm hangs. Before this change, `initialize ->
thread/start -> turn/start` could sit behind the prewarm for up to five
minutes, so the client would not see `turn/started`, and even
`turn/interrupt` would block because the turn had not actually started
yet.
Now, we:
- set a (configurable) timeout of 15s for websocket startup time,
exposed as `websocket_startup_timeout_ms` in config.toml
- `turn/started` is sent immediately on `turn/start` even if the
websocket is still connecting
- `turn/interrupt` can be used to cancel a turn that is still waiting on
the websocket warmup
- the turn task will wait for the full 15s websocket warming timeout
before falling back
## Why
The old behavior made app-server feel stuck at exactly the moment the
client expects turn lifecycle events to start flowing. That was
especially painful for external clients, because from their point of
view the server had accepted the request but then went silent for
minutes.
## Configuring the websocket startup timeout
Can set it in config.toml like this:
```
[model_providers.openai]
supports_websockets = true
websocket_connect_timeout_ms = 15000
```
## Stack Position
2/4. Built on top of #14828.
## Base
- #14828
## Unblocks
- #14829
- #14827
## Scope
- Port the realtime v2 wire parsing, session, app-server, and
conversation runtime behavior onto the split websocket-method base.
- Branch runtime behavior directly on the current realtime session kind
instead of parser-derived flow flags.
- Keep regression coverage in the existing e2e suites.
---------
Co-authored-by: Codex <noreply@openai.com>
## Why
Once the repo-local lint exists, `codex-rs` needs to follow the
checked-in convention and CI needs to keep it from drifting. This commit
applies the fallback `/*param*/` style consistently across existing
positional literal call sites without changing those APIs.
The longer-term preference is still to avoid APIs that require comments
by choosing clearer parameter types and call shapes. This PR is
intentionally the mechanical follow-through for the places where the
existing signatures stay in place.
After rebasing onto newer `main`, the rollout also had to cover newly
introduced `tui_app_server` call sites. That made it clear the first cut
of the CI job was too expensive for the common path: it was spending
almost as much time installing `cargo-dylint` and re-testing the lint
crate as a representative test job spends running product tests. The CI
update keeps the full workspace enforcement but trims that extra
overhead from ordinary `codex-rs` PRs.
## What changed
- keep a dedicated `argument_comment_lint` job in `rust-ci`
- mechanically annotate remaining opaque positional literals across
`codex-rs` with exact `/*param*/` comments, including the rebased
`tui_app_server` call sites that now fall under the lint
- keep the checked-in style aligned with the lint policy by using
`/*param*/` and leaving string and char literals uncommented
- cache `cargo-dylint`, `dylint-link`, and the relevant Cargo
registry/git metadata in the lint job
- split changed-path detection so the lint crate's own `cargo test` step
runs only when `tools/argument-comment-lint/*` or `rust-ci.yml` changes
- continue to run the repo wrapper over the `codex-rs` workspace, so
product-code enforcement is unchanged
Most of the code changes in this commit are intentionally mechanical
comment rewrites or insertions driven by the lint itself.
## Verification
- `./tools/argument-comment-lint/run.sh --workspace`
- `cargo test -p codex-tui-app-server -p codex-tui`
- parsed `.github/workflows/rust-ci.yml` locally with PyYAML
---
* -> #14652
* #14651
Fix https://github.com/openai/codex/issues/14161
This fixes sub-agent [[skills.config]] overrides being ignored when
parent and child share the same cwd. The root cause was that turn skill
loading rebuilt from cwd-only state and reused a cwd-scoped cache, so
role-local skill enable/disable overrides did not reliably affect the
spawned agent's effective skill set.
This change switches turn construction to use the effective per-turn
config and adds a config-aware skills cache keyed by skill roots plus
final disabled paths.
## Summary
- reuse a guardian subagent session across approvals so reviews keep a
stable prompt cache key and avoid one-shot startup overhead
- clear the guardian child history before each review so prior guardian
decisions do not leak into later approvals
- include the `smart_approvals` -> `guardian_approval` feature flag
rename in the same PR to minimize release latency on a very tight
timeline
- add regression coverage for prompt-cache-key reuse without
prior-review prompt bleed
## Request
- Bug/enhancement request: internal guardian prompt-cache and latency
improvement request
---------
Co-authored-by: Codex <noreply@openai.com>
- [x] Bypass tool search and stuff tool specs directly into model
context when either a. Tool search is not available for the model or b.
There are not that many tools to search for.
This extends dynamic_tool_calls to allow us to hide a tool from the
model context but still use it as part of the general tool calling
runtime (for ex from js_repl/code_mode)
Move the general `Apps`, `Skills` and `Plugins` instructions blocks out
of `user_instructions` and into the developer message, with new `Apps ->
Skills -> Plugins` order for better clarity.
Also wrap those sections in stable XML-style instruction tags (like
other sections) and update prompt-layout tests/snapshots. This makes the
tests less brittle in snapshot output (we can parse the sections), and
it consolidates the capability instructions in one place.
#### Tests
Updated snapshots, added tests.
`<AGENTS_MD>` disappearing in snapshots is expected: before this change,
the wrapped user-instructions message was kept alive by `Skills`
content. Now that `Skills` and `Plugins` are in the developer message,
that wrapper only appears when there is real
project-doc/user-instructions content.
---------
Co-authored-by: Charley Cunningham <ccunningham@openai.com>
## Summary
- apply persisted execpolicy network rules when booting the managed
network proxy
- pass the current execpolicy into managed proxy startup so host
approvals selected with "allow this host in the future" survive new
sessions
## Summary
- reuse rollout reconstruction when applying a backtrack rollback so
`reference_context_item` is restored from persisted rollout state
- build rollback replay from the flushed rollout items plus the rollback
marker, avoiding the extra reread/fallback path
- add regression coverage for rollback after compaction so turn-context
diffing stays aligned after backtracking
Co-authored-by: Codex <noreply@openai.com>
## Why
The unified-exec path was carrying zsh-fork state in a partially
flattened way.
First, the decision about whether zsh-fork was active came from feature
selection in `ToolsConfig`, while the real prerequisites lived in
session state. That left the handler and runtime defending against
partially configured cases later.
Second, once zsh-fork was active, its two runtime-only paths were
threaded through the runtime as separate arguments even though they form
one coherent piece of configuration.
This change keeps unified-exec on a single session-derived source of
truth and bundles the zsh-fork-specific paths into a named config type
so the runtime can pass them around as one unit.
In particular, this PR introduces this enum so the `ZshFork` variant can
carry the appropriate state with it:
```rust
#[derive(Debug, Clone, Eq, PartialEq)]
pub enum UnifiedExecShellMode {
Direct,
ZshFork(ZshForkConfig),
}
#[derive(Debug, Clone, Eq, PartialEq)]
pub struct ZshForkConfig {
pub(crate) shell_zsh_path: AbsolutePathBuf,
pub(crate) main_execve_wrapper_exe: AbsolutePathBuf,
}
```
This cleanup was done in preparation for
https://github.com/openai/codex/pull/13432.
## What Changed
- Replaced the feature-only `UnifiedExecBackendConfig` split with
`UnifiedExecShellMode` in `codex-rs/core/src/tools/spec.rs`.
- Derived the unified-exec mode from session-backed inputs when building
turn `ToolsConfig`, and preserved that mode across model switches and
review turns.
- Introduced `ZshForkConfig`, which stores the resolved zsh-fork
`AbsolutePathBuf` values for the configured `zsh` binary and `execve`
wrapper.
- Threaded `ZshForkConfig` through unified-exec command construction and
the zsh-fork preparation path so zsh-fork-specific runtime code consumes
a single config object instead of separate path arguments.
- Added focused tests for constructing zsh-fork mode only when session
prerequisites are available, and updated the zsh-fork expectations to be
target-platform aware.
## Testing
- `cargo test -p codex-core zsh_fork --lib`
---
[//]: # (BEGIN SAPLING FOOTER)
Stack created with [Sapling](https://sapling-scm.com). Best reviewed
with [ReviewStack](https://reviewstack.dev/openai/codex/pull/14633).
* #13432
* __->__ #14633
Stop hooks now receive `stop_hook_active` and enable stop hooks to loop
forever if they'd like to. In the initial hooks PR, we implemented a
simpler mechanic that the stop-blocking could only happen once in a row
- support stop hook adding a continuation prompt to add a further task
- if multiple stop-blocks happen that have continuation prompts, they
are concatenated
example run:
```
› hey :)
• Running SessionStart hook: lighting the observatory
SessionStart hook (completed)
warning: Hi, I'm a session start hook for wizard-tower (startup).
hook context: Startup context: A wimboltine stonpet is an exotic cuisine from hyperspace
• Aloha :) Happy to jam with you. What are we building today?
• Running Stop hook: updating the guards
Stop hook (blocked)
warning: Wizard Tower Stop hook continuing conversation
feedback: cook the stonpet
• Aloha, here’s the hyperspace move for cooking a wimboltine stonpet:
1. Sear the stonpet in a hot pan with moon-oil until the edges shimmer.
2. Add star-lime, black salt, and a little fermented nebula paste.
3. Lower the heat and let it braise for 8 cosmic minutes with a splash of comet broth.
4. Finish with sky herbs and serve over warm asteroid rice.
The vibe: crispy outside, tender center, deep interdimensional savor.
• Running Stop hook: updating the guards
Stop hook (completed)
warning: Wizard Tower Stop hook saw a second pass and stayed calm to avoid a loop.
```
.codex/config.toml
```
[features]
codex_hooks = true
```
.codex/hooks.json
```
{
"hooks": {
"SessionStart": [
{
"matcher": "startup|resume",
"hooks": [
{
"type": "command",
"command": "/usr/bin/python3 .codex/hooks/session_start_demo.py",
"timeoutSec": 10,
"statusMessage": "lighting the observatory"
}
]
}
],
"Stop": [
{
"hooks": [
{
"type": "command",
"command": "/usr/bin/python3 .codex/hooks/stop_demo_block.py",
"timeoutSec": 10,
"statusMessage": "updating the guards"
}
]
}
]
}
}
```
.codex/hooks/session_start_demo.py
```
#!/usr/bin/env python3
import json
import sys
from pathlib import Path
def main() -> int:
payload = json.load(sys.stdin)
cwd = Path(payload.get("cwd", ".")).name or "wizard-tower"
source = payload.get("source", "startup")
source_label = "resume" if source == "resume" else "startup"
source_prefix = (
"Resume context:"
if source == "resume"
else "Startup context:"
)
output = {
"systemMessage": (
f"Hi, I'm a session start hook for {cwd} ({source_label})."
),
"hookSpecificOutput": {
"hookEventName": "SessionStart",
"additionalContext": (
f"{source_prefix} A wimboltine stonpet is an exotic cuisine from hyperspace"
),
},
}
print(json.dumps(output))
return 0
if __name__ == "__main__":
raise SystemExit(main())
```
.codex/hooks/stop_demo_block.py
```
#!/usr/bin/env python3
import json
import sys
def main() -> int:
payload = json.load(sys.stdin)
stop_hook_active = payload.get("stop_hook_active", False)
last_assistant_message = payload.get("last_assistant_message") or ""
char_count = len(last_assistant_message.strip())
if stop_hook_active:
system_message = (
"Wizard Tower Stop hook saw a second pass and stayed calm to avoid a loop."
)
print(json.dumps({"systemMessage": system_message}))
else:
system_message = (
f"Wizard Tower Stop hook continuing conversation"
)
print(json.dumps({"systemMessage": system_message, "decision": "block", "reason": "cook the stonpet"}))
return 0
if __name__ == "__main__":
raise SystemExit(main())
```
## Summary
- add `approvals_reviewer = "user" | "guardian_subagent"` as the runtime
control for who reviews approval requests
- route Smart Approvals guardian review through core for command
execution, file changes, managed-network approvals, MCP approvals, and
delegated/subagent approval flows
- expose guardian review in app-server with temporary unstable
`item/autoApprovalReview/{started,completed}` notifications carrying
`targetItemId`, `review`, and `action`
- update the TUI so Smart Approvals can be enabled from `/experimental`,
aligned with the matching `/approvals` mode, and surfaced clearly while
reviews are pending or resolved
## Runtime model
This PR does not introduce a new `approval_policy`.
Instead:
- `approval_policy` still controls when approval is needed
- `approvals_reviewer` controls who reviewable approval requests are
routed to:
- `user`
- `guardian_subagent`
`guardian_subagent` is a carefully prompted reviewer subagent that
gathers relevant context and applies a risk-based decision framework
before approving or denying the request.
The `smart_approvals` feature flag is a rollout/UI gate. Core runtime
behavior keys off `approvals_reviewer`.
When Smart Approvals is enabled from the TUI, it also switches the
current `/approvals` settings to the matching Smart Approvals mode so
users immediately see guardian review in the active thread:
- `approval_policy = on-request`
- `approvals_reviewer = guardian_subagent`
- `sandbox_mode = workspace-write`
Users can still change `/approvals` afterward.
Config-load behavior stays intentionally narrow:
- plain `smart_approvals = true` in `config.toml` remains just the
rollout/UI gate and does not auto-set `approvals_reviewer`
- the deprecated `guardian_approval = true` alias migration does
backfill `approvals_reviewer = "guardian_subagent"` in the same scope
when that reviewer is not already configured there, so old configs
preserve their original guardian-enabled behavior
ARC remains a separate safety check. For MCP tool approvals, ARC
escalations now flow into the configured reviewer instead of always
bypassing guardian and forcing manual review.
## Config stability
The runtime reviewer override is stable, but the config-backed
app-server protocol shape is still settling.
- `thread/start`, `thread/resume`, and `turn/start` keep stable
`approvalsReviewer` overrides
- the config-backed `approvals_reviewer` exposure returned via
`config/read` (including profile-level config) is now marked
`[UNSTABLE]` / experimental in the app-server protocol until we are more
confident in that config surface
## App-server surface
This PR intentionally keeps the guardian app-server shape narrow and
temporary.
It adds generic unstable lifecycle notifications:
- `item/autoApprovalReview/started`
- `item/autoApprovalReview/completed`
with payloads of the form:
- `{ threadId, turnId, targetItemId, review, action? }`
`review` is currently:
- `{ status, riskScore?, riskLevel?, rationale? }`
- where `status` is one of `inProgress`, `approved`, `denied`, or
`aborted`
`action` carries the guardian action summary payload from core when
available. This lets clients render temporary standalone pending-review
UI, including parallel reviews, even when the underlying tool item has
not been emitted yet.
These notifications are explicitly documented as `[UNSTABLE]` and
expected to change soon.
This PR does **not** persist guardian review state onto `thread/read`
tool items. The intended follow-up is to attach guardian review state to
the reviewed tool item lifecycle instead, which would improve
consistency with manual approvals and allow thread history / reconnect
flows to replay guardian review state directly.
## TUI behavior
- `/experimental` exposes the rollout gate as `Smart Approvals`
- enabling it in the TUI enables the feature and switches the current
session to the matching Smart Approvals `/approvals` mode
- disabling it in the TUI clears the persisted `approvals_reviewer`
override when appropriate and returns the session to default manual
review when the effective reviewer changes
- `/approvals` still exposes the reviewer choice directly
- the TUI renders:
- pending guardian review state in the live status footer, including
parallel review aggregation
- resolved approval/denial state in history
## Scope notes
This PR includes the supporting core/runtime work needed to make Smart
Approvals usable end-to-end:
- shell / unified-exec / apply_patch / managed-network / MCP guardian
review
- delegated/subagent approval routing into guardian review
- guardian review risk metadata and action summaries for app-server/TUI
- config/profile/TUI handling for `smart_approvals`, `guardian_approval`
alias migration, and `approvals_reviewer`
- a small internal cleanup of delegated approval forwarding to dedupe
fallback paths and simplify guardian-vs-parent approval waiting (no
intended behavior change)
Out of scope for this PR:
- redesigning the existing manual approval protocol shapes
- persisting guardian review state onto app-server `ThreadItem`s
- delegated MCP elicitation auto-review (the current delegated MCP
guardian shim only covers the legacy `RequestUserInput` path)
---------
Co-authored-by: Codex <noreply@openai.com>
Summary
- add the code_mode_only feature flag/config schema and wire its
dependency on code_mode
- update code mode tool descriptions to list nested tools with detailed
headers
- restrict available tools for prompt and exec descriptions when
code_mode_only is enabled and test the behavior
Testing
- Not run (not requested)
## Description
This PR expands tracing coverage across app-server thread startup, core
session initialization, and the Responses transport layer. It also gives
core dispatch spans stable operation-specific names so traces are easier
to follow than the old generic `submission_dispatch` spans.
Also use `fmt::Display` for types that we serialize in traces so we send
strings instead of rust types
## Summary
- create the turn-scoped `ToolCallRuntime` before starting the code mode
worker so the worker reuses the same runtime and router
- thread the shared runtime through the code mode service/worker path
and use it for nested tool calls
- model aborted tool calls as a concrete `ToolOutput` so aborted
responses still produce valid tool output shapes
## Testing
- `just fmt`
- `cargo test -p codex-core` (still running locally)
as reported in https://github.com/openai/codex/issues/14367 users can
explicitly enable unified_exec which will bypass the sandbox even when
it should be enabled.
Until we support unified_exec with the Windows Sandbox, we will disallow
it unless the sandbox is disabled
## Summary
- start a code mode worker once per turn and let it pump nested tool
calls through a dedicated queue
- simplify code mode request/response dispatch around request ids and
generic runner-unavailable errors
- clean up the code mode process API and runner protocol plumbing
## Testing
- not run yet
## Summary
- address the follow-up review nits from #13996 in a separate PR
- make the approvals test command a raw string and keep the
managed-network path using env proxy routing
- inline `--apply-seccomp-then-exec` in the Linux sandbox inner command
builder
- remove the bubblewrap-specific sandbox metric tag path and drop the
`use_legacy_landlock` shim from `sandbox_tag`/`TurnMetadataState::new`
- restore the `Feature` import that `origin/main` currently still needs
in `connectors.rs`
## Testing
- `cargo test -p codex-linux-sandbox`
- focused `codex-core` tests were rerun/started, but the final
verification pass was interrupted when I pushed at request
## Summary
- make bubblewrap the default Linux sandbox and keep
`use_legacy_landlock` as the only override
- remove `use_linux_sandbox_bwrap` from feature, config, schema, and
docs surfaces
- update Linux sandbox selection, CLI/config plumbing, and related
tests/docs to match the new default
- fold in the follow-up CI fixes for request-permissions responses and
Linux read-only sandbox error text
jif-oai ·
Charley Cunningham ·
Dylan Hurd ·
Matthew Zeng ·
Ahmed Ibrahim ·
nicholasclark-openai ·
pakrym-oai ·
Andrei Eternal ·
xl-openai ·
Colin Young ·
Owen Lin ·
Michael Bolin ·
Channing Conger ·
sayan-oai ·
viyatb-oai ·
Jack Mousseau ·
alexsong-oai ·
iceweasel-oai ·