## What changed
- The duration-recording fixture sleep was reduced from a large
artificial delay to `0.2s`, and the assertion floor was lowered to
`0.1s`.
- The shell tool fixtures now force `login = false` so they do not
invoke login-shell startup paths.
## Why this fixes the flake
- The old tests were paying for two kinds of noise that had nothing to
do with the feature being validated: oversized sleep time and variable
shell initialization cost.
- Login shells can pick up runner-specific startup files and incur
inconsistent startup latency.
- The test only needs to prove that we record a nontrivial duration and
preserve shell output. A shorter fixture delay plus a non-login shell
keeps that coverage while removing runner-dependent wall-clock variance.
## Scope
- Test-only change.
## Why
After `#13440` and `#13445`, macOS Seatbelt policy generation was still
deriving filesystem and network behavior from the legacy `SandboxPolicy`
projection.
That projection loses explicit unreadable carveouts and conflates split
network decisions, so the generated Seatbelt policy could still be wider
than the split policy that Codex had already computed.
## What changed
- added Seatbelt entrypoints that accept `FileSystemSandboxPolicy` and
`NetworkSandboxPolicy` directly
- built read and write policy stanzas from access roots plus excluded
subpaths so explicit unreadable carveouts survive into the generated
Seatbelt policy
- switched network policy generation to consult `NetworkSandboxPolicy`
directly
- failed closed when managed-network or proxy-constrained sessions do
not yield usable loopback proxy endpoints
- updated the macOS callers and test helpers that now need to carry the
split policies explicitly
## Verification
- added regression coverage in `core/src/seatbelt.rs` for unreadable
carveouts under both full-disk and scoped-readable policies
- verified the current PR state with `just clippy`
---
[//]: # (BEGIN SAPLING FOOTER)
Stack created with [Sapling](https://sapling-scm.com). Best reviewed
with [ReviewStack](https://reviewstack.dev/openai/codex/pull/13448).
* #13453
* #13452
* #13451
* #13449
* __->__ #13448
* #13445
* #13440
* #13439
---------
Co-authored-by: viyatb-oai <viyatb@openai.com>
## Summary
- add the guardian reviewer flow for `on-request` approvals in command,
patch, sandbox-retry, and managed-network approval paths
- keep guardian behind `features.guardian_approval` instead of exposing
a public `approval_policy = guardian` mode
- route ordinary `OnRequest` approvals to the guardian subagent when the
feature is enabled, without changing the public approval-mode surface
## Public model
- public approval modes stay unchanged
- guardian is enabled via `features.guardian_approval`
- when that feature is on, `approval_policy = on-request` keeps the same
approval boundaries but sends those approval requests to the guardian
reviewer instead of the user
- `/experimental` only persists the feature flag; it does not rewrite
`approval_policy`
- CLI and app-server no longer expose a separate `guardian` approval
mode in this PR
## Guardian reviewer
- the reviewer runs as a normal subagent and reuses the existing
subagent/thread machinery
- it is locked to a read-only sandbox and `approval_policy = never`
- it does not inherit user/project exec-policy rules
- it prefers `gpt-5.4` when the current provider exposes it, otherwise
falls back to the parent turn's active model
- it fail-closes on timeout, startup failure, malformed output, or any
other review error
- it currently auto-approves only when `risk_score < 80`
## Review context and policy
- guardian mirrors `OnRequest` approval semantics rather than
introducing a separate approval policy
- explicit `require_escalated` requests follow the same approval surface
as `OnRequest`; the difference is only who reviews them
- managed-network allowlist misses that enter the approval flow are also
reviewed by guardian
- the review prompt includes bounded recent transcript history plus
recent tool call/result evidence
- transcript entries and planned-action strings are truncated with
explicit `<guardian_truncated ... />` markers so large payloads stay
bounded
- apply-patch reviews include the full patch content (without
duplicating the structured `changes` payload)
- the guardian request layout is snapshot-tested using the same
model-visible Responses request formatter used elsewhere in core
## Guardian network behavior
- the guardian subagent inherits the parent session's managed-network
allowlist when one exists, so it can use the same approved network
surface while reviewing
- exact session-scoped network approvals are copied into the guardian
session with protocol/port scope preserved
- those copied approvals are now seeded before the guardian's first turn
is submitted, so inherited approvals are available during any immediate
review-time checks
## Out of scope / follow-ups
- the sandbox-permission validation split was pulled into a separate PR
and is not part of this diff
- a future follow-up can enable `serde_json` preserve-order in
`codex-core` and then simplify the guardian action rendering further
---------
Co-authored-by: Codex <noreply@openai.com>
## Summary
- distinguish reject-policy handling for prefix-rule approvals versus
sandbox approvals in Unix shell escalation
- keep prompting for skill-script execution when `rules=true` but
`sandbox_approval=false`, instead of denying the command up front
- add regression coverage for both skill-script reject-policy paths in
`codex-rs/core/tests/suite/skill_approval.rs`
## Why
`#13434` introduces split `FileSystemSandboxPolicy` and
`NetworkSandboxPolicy`, but the runtime still made most execution-time
sandbox decisions from the legacy `SandboxPolicy` projection.
That projection loses information about combinations like unrestricted
filesystem access with restricted network access. In practice, that
means the runtime can choose the wrong platform sandbox behavior or set
the wrong network-restriction environment for a command even when config
has already separated those concerns.
This PR carries the split policies through the runtime so sandbox
selection, process spawning, and exec handling can consult the policy
that actually matters.
## What changed
- threaded `FileSystemSandboxPolicy` and `NetworkSandboxPolicy` through
`TurnContext`, `ExecRequest`, sandbox attempts, shell escalation state,
unified exec, and app-server exec overrides
- updated sandbox selection in `core/src/sandboxing/mod.rs` and
`core/src/exec.rs` to key off `FileSystemSandboxPolicy.kind` plus
`NetworkSandboxPolicy`, rather than inferring behavior only from the
legacy `SandboxPolicy`
- updated process spawning in `core/src/spawn.rs` and the platform
wrappers to use `NetworkSandboxPolicy` when deciding whether to set
`CODEX_SANDBOX_NETWORK_DISABLED`
- kept additional-permissions handling and legacy `ExternalSandbox`
compatibility projections aligned with the split policies, including
explicit user-shell execution and Windows restricted-token routing
- updated callers across `core`, `app-server`, and `linux-sandbox` to
pass the split policies explicitly
## Verification
- added regression coverage in `core/tests/suite/user_shell_cmd.rs` to
verify `RunUserShellCommand` does not inherit
`CODEX_SANDBOX_NETWORK_DISABLED` from the active turn
- added coverage in `core/src/exec.rs` for Windows restricted-token
sandbox selection when the legacy projection is `ExternalSandbox`
- updated Linux sandbox coverage in
`linux-sandbox/tests/suite/landlock.rs` to exercise the split-policy
exec path
- verified the current PR state with `just clippy`
---
[//]: # (BEGIN SAPLING FOOTER)
Stack created with [Sapling](https://sapling-scm.com). Best reviewed
with [ReviewStack](https://reviewstack.dev/openai/codex/pull/13439).
* #13453
* #13452
* #13451
* #13449
* #13448
* #13445
* #13440
* __->__ #13439
---------
Co-authored-by: viyatb-oai <viyatb@openai.com>
Previously, we could only configure whether web search was on/off.
This PR enables sending along a web search config, which includes all
the stuff responsesapi supports: filters, location, etc.
## Summary
- Treat skill scripts with no permission profile, or an explicitly empty
one, as permissionless and run them with the turn's existing sandbox
instead of forcing an exec approval prompt.
- Keep the approval flow unchanged for skills that do declare additional
permissions.
- Update the skill approval tests to assert that permissionless skill
scripts do not prompt on either the initial run or a rerun.
## Why
Permissionless skills should inherit the current turn sandbox directly.
Prompting for exec approval in that case adds friction without granting
any additional capability.
## Summary
This is a purely mechanical refactor of `OtelManager` ->
`SessionTelemetry` to better convey what the struct is doing. No
behavior change.
## Why
`OtelManager` ended up sounding much broader than what this type
actually does. It doesn't manage OTEL globally; it's the session-scoped
telemetry surface for emitting log/trace events and recording metrics
with consistent session metadata (`app_version`, `model`, `slug`,
`originator`, etc.).
`SessionTelemetry` is a more accurate name, and updating the call sites
makes that boundary a lot easier to follow.
## Validation
- `just fmt`
- `cargo test -p codex-otel`
- `cargo test -p codex-core`
- add experimental_realtime_ws_startup_context to override or disable
realtime websocket startup context
- preserve generated startup context when unset and cover the new
override paths in tests
## Why
`SandboxPolicy` currently mixes together three separate concerns:
- parsing layered config from `config.toml`
- representing filesystem sandbox state
- carrying basic network policy alongside filesystem choices
That makes the existing config awkward to extend and blocks the new TOML
proposal where `[permissions]` becomes a table of named permission
profiles selected by `default_permissions`. (The idea is that if
`default_permissions` is not specified, we assume the user is opting
into the "traditional" way to configure the sandbox.)
This PR adds the config-side plumbing for those profiles while still
projecting back to the legacy `SandboxPolicy` shape that the current
macOS and Linux sandbox backends consume.
It also tightens the filesystem profile model so scoped entries only
exist for `:project_roots`, and so nested keys must stay within a
project root instead of using `.` or `..` traversal.
This drops support for the short-lived `[permissions.network]` in
`config.toml` because now that would be interpreted as a profile named
`network` within `[permissions]`.
## What Changed
- added `PermissionsToml`, `PermissionProfileToml`,
`FilesystemPermissionsToml`, and `FilesystemPermissionToml` so config
can parse named profiles under `[permissions.<profile>.filesystem]`
- added top-level `default_permissions` selection, validation for
missing or unknown profiles, and compilation from a named profile into
split `FileSystemSandboxPolicy` and `NetworkSandboxPolicy` values
- taught config loading to choose between the legacy `sandbox_mode` path
and the profile-based path without breaking legacy users
- introduced `codex-protocol::permissions` for the split filesystem and
network sandbox types, and stored those alongside the legacy projected
`sandbox_policy` in runtime `Permissions`
- modeled `FileSystemSpecialPath` so only `ProjectRoots` can carry a
nested `subpath`, matching the intended config syntax instead of
allowing invalid states for other special paths
- restricted scoped filesystem maps to `:project_roots`, with validation
that nested entries are non-empty descendant paths and cannot use `.` or
`..` to escape the project root
- kept existing runtime consumers working by projecting
`FileSystemSandboxPolicy` back into `SandboxPolicy`, with an explicit
error for profiles that request writes outside the workspace root
- loaded proxy settings from top-level `[network]`
- regenerated `core/config.schema.json`
## Verification
- added config coverage for profile deserialization,
`default_permissions` selection, top-level `[network]` loading, network
enablement, rejection of writes outside the workspace root, rejection of
nested entries for non-`:project_roots` special paths, and rejection of
parent-directory traversal in `:project_roots` maps
- added protocol coverage for the legacy bridge rejecting non-workspace
writes
## Docs
- update the Codex config docs on developers.openai.com/codex to
document named `[permissions.<profile>]` entries, `default_permissions`,
scoped `:project_roots` syntax, the descendant-path restriction for
nested `:project_roots` entries, and top-level `[network]` proxy
configuration
---
[//]: # (BEGIN SAPLING FOOTER)
Stack created with [Sapling](https://sapling-scm.com). Best reviewed
with [ReviewStack](https://reviewstack.dev/openai/codex/pull/13434).
* #13453
* #13452
* #13451
* #13449
* #13448
* #13445
* #13440
* #13439
* __->__ #13434
#### What
Add structured `@plugin` parsing and TUI support for plugin mentions.
- Core: switch from plain-text `@display_name` parsing to structured
`plugin://...` mentions via `UserInput::Mention` and
`[$...](plugin://...)` links in text, same pattern as apps/skills.
- TUI: add plugin mention popup, autocomplete, and chips when typing
`$`. Load plugin capability summaries and feed them into the composer;
plugin mentions appear alongside skills and apps.
- Generalize mention parsing to a sigil parameter, still defaults to `$`
<img width="797" height="119" alt="image"
src="https://github.com/user-attachments/assets/f0fe2658-d908-4927-9139-73f850805ceb"
/>
Builds on #13510. Currently clients have to build their own `id` via
`plugin@marketplace` and filter plugins to show by `enabled`, but we
will add `id` and `available` as fields returned from `plugin/list`
soon.
####Tests
Added tests, verified locally.
## Summary
Today `SandboxPermissions::requires_additional_permissions()` does not
actually mean "is `WithAdditionalPermissions`". It returns `true` for
any non-default sandbox override, including `RequireEscalated`. That
broad behavior is relied on in multiple `main` callsites.
The naming is security-sensitive because `SandboxPermissions` is used on
shell-like tool calls to tell the executor how a single command should
relate to the turn sandbox:
- `UseDefault`: run with the turn sandbox unchanged
- `RequireEscalated`: request execution outside the sandbox
- `WithAdditionalPermissions`: stay sandboxed but widen permissions for
that command only
## Problem
The old helper name reads as if it only applies to the
`WithAdditionalPermissions` variant. In practice it means "this command
requested any explicit sandbox override."
That ambiguity made it easy to read production checks incorrectly and
made the guardian change look like a standalone `main` fix when it is
not.
On `main` today:
- `shell` and `unified_exec` intentionally reject any explicit
`sandbox_permissions` request unless approval policy is `OnRequest`
- `exec_policy` intentionally treats any explicit sandbox override as
prompt-worthy in restricted sandboxes
- tests intentionally serialize both `RequireEscalated` and
`WithAdditionalPermissions` as explicit sandbox override requests
So changing those callsites from the broad helper to a narrow
`WithAdditionalPermissions` check would be a behavior change, not a pure
cleanup.
## What This PR Does
- documents `SandboxPermissions` as a per-command sandbox override, not
a generic permissions bag
- adds `requests_sandbox_override()` for the broad meaning: anything
except `UseDefault`
- adds `uses_additional_permissions()` for the narrow meaning: only
`WithAdditionalPermissions`
- keeps `requires_additional_permissions()` as a compatibility alias to
the broad meaning for now
- updates the current broad callsites to use the accurately named broad
helper
- adds unit coverage that locks in the semantics of all three helpers
## What This PR Does Not Do
This PR does not change runtime behavior. That is intentional.
---------
Co-authored-by: Codex <noreply@openai.com>
- Replay thread rollback from the persisted rollout history instead of
truncating in-memory state.\n- Add rollback coverage, including
rollback-behind-compaction snapshot coverage.
## Summary
- group recent work by git repo when available, otherwise by directory
- render recent work as bounded user asks with per-thread cwd context
- exclude hidden files and directories from workspace trees
## Note-- added plugin mentions via @, but that conflicts with file
mentions
depends and builds upon #13433.
- introduces explicit `@plugin` mentions. this injects the plugin's mcp
servers, app names, and skill name format into turn context as a dev
message.
- we do not yet have UI for these mentions, so we currently parse raw
text (as opposed to skills and apps which have UI chips, autocomplete,
etc.) this depends on a `plugins/list` app-server endpoint we can feed
the UI with, which is upcoming
- also annotate mcp and app tool descriptions with the plugin(s) they
come from. this gives the model a first class way of understanding what
tools come from which plugins, which will help implicit invocation.
### Tests
Added and updated tests, unit and integration. Also confirmed locally a
raw `@plugin` injects the dev message, and the model knows about its
apps, mcps, and skills.
This PR adds a durable trace linkage for each turn by storing the active
trace ID on the rollout TurnContext record stored in session rollout
files.
Before this change, we propagated trace context at runtime but didn’t
persist a stable per-turn trace key in rollout history. That made
after-the-fact debugging harder (for example, mapping a historical turn
to the corresponding trace in datadog). This sets us up for much easier
debugging in the future.
### What changed
- Added an optional `trace_id` to TurnContextItem (rollout schema).
- Added a small OTEL helper to read the current span trace ID.
- Captured `trace_id` when creating `TurnContext` and included it in
`to_turn_context_item()`.
- Updated tests and fixtures that construct TurnContextItem so
older/no-trace cases still work.
### Why this approach
TurnContext is already the canonical durable per-turn metadata in
rollout. This keeps ownership clean: trace linkage lives with other
persisted turn metadata.
## Summary
- Change `js_repl` failed-cell persistence so later cells keep prior
bindings plus only the current-cell bindings whose initialization
definitely completed before the throw.
- Preserve initialized lexical bindings across failed cells via
module-namespace readability, including top-level destructuring that
partially succeeds before a later throw.
- Preserve hoisted `var` and `function` bindings only when execution
clearly reached their declaration site, and preserve direct top-level
pre-declaration `var` writes and updates through explicit write-site
markers.
- Preserve top-level `for...in` / `for...of` `var` bindings when the
loop body executes at least once, using a first-iteration guard to avoid
per-iteration bookkeeping overhead.
- Keep prior module state intact across link-time failures and
evaluation failures before the prelude runs, while still allowing failed
cells that already recreated prior bindings to persist updates to those
existing bindings.
- Hide internal commit hooks from user `js_repl` code after the prelude
aliases them, so snippets cannot spoof committed bindings by calling the
raw `import.meta` hooks directly.
- Add focused regression coverage for the supported failed-cell
behaviors and the intentionally unsupported boundaries.
- Update `js_repl` docs and generated instructions to describe the new,
narrower failed-cell persistence model.
## Motivation
We saw `js_repl` drop bindings that had already been initialized
successfully when a later statement in the same cell threw, for example:
const { context: liveContext, session } =
await initializeGoogleSheetsLiveForTab(tab);
// later statement throws
That was surprising in practice because successful earlier work
disappeared from the next cell.
This change makes failed-cell persistence more useful without trying to
model every possible partially executed JavaScript edge case. The
resulting behavior is narrower and easier to reason about:
- prior bindings are always preserved
- lexical bindings persist when their initialization completed before
the throw
- hoisted `var` / `function` bindings persist only when execution
clearly reached their declaration or a supported top-level `var` write
site
- failed cells that already recreated prior bindings can persist writes
to those existing bindings even if they introduce no new bindings
The detailed edge-case matrix stays in `docs/js_repl.md`. The
model-facing `project_doc` guidance is intentionally shorter and focused
on generation-relevant behavior.
## Supported Failed-Cell Behavior
- Prior bindings remain available after a failed cell.
- Initialized lexical bindings remain available after a failed cell.
- Top-level destructuring like `const { a, b } = ...` preserves names
whose initialization completed before a later throw.
- Hoisted `function` bindings persist when execution reached the
declaration statement before the throw.
- Direct top-level pre-declaration `var` writes and updates persist, for
example:
- `x = 1`
- `x += 1`
- `x++`
- short-circuiting logical assignments only persist when the write
branch actually runs
- Non-empty top-level `for...in` / `for...of` `var` loops persist their
loop bindings.
- Failed cells can persist updates to existing carried bindings after
the prelude has run, even when the cell commits no new bindings.
- Link failures and eval failures before the prelude do not poison
`@prev`.
## Intentionally Unsupported Failed-Cell Cases
- Hoisted function reads before the declaration, such as `foo(); ...;
function foo() {}`
- Aliasing or inference-based recovery from reads before declaration
- Nested writes inside already-instrumented assignment RHS expressions
- Destructuring-assignment recovery for hoisted `var`
- Partial `var` destructuring recovery
- Pre-declaration `undefined` reads for hoisted `var`
- Empty top-level `for...in` / `for...of` loop vars
- Nested or scope-sensitive pre-declaration `var` writes outside direct
top-level expression statements
add `web_search_tool_type` on model_info that can be populated from
backend. will be used to filter which models can use `web_search` with
images and which cant.
added small unit test.
### first half of changes, followed by #13510
Track plugin capabilities as derived summaries on `PluginLoadOutcome`
for enabled plugins with at least one skill/app/mcp.
Also add `Plugins` section to `user_instructions` injected on session
start. These introduce the plugins concept and list enabled plugins, but
do NOT currently include paths to enabled plugins or details on what
apps/mcps the plugins contain (current plan is to inject this on
@-mention). that can be adjusted in a follow up and based on evals.
### tests
Added/updated tests, confirmed locally that new `Plugins` section +
currently enabled plugins show up in `user_instructions`.
Follow-up to [#13388](https://github.com/openai/codex/pull/13388). This
uses the same general fix pattern as
[#12421](https://github.com/openai/codex/pull/12421), but in the
`codex-core` compact/resume/fork path.
## Why
`compact_resume_after_second_compaction_preserves_history` started
overflowing the stack on Windows CI after `#13388`.
The important part is that this was not a compaction-recursion bug. The
test exercises a path with several thin `async fn` wrappers around much
larger thread-spawn, resume, and fork futures. When one `async fn`
awaits another inline, the outer future stores the callee future as part
of its own state machine. In a long wrapper chain, that means a caller
can accidentally inline a lot more state than the source code suggests.
That is exactly what was happening here:
- `ThreadManager` convenience methods such as `start_thread`,
`resume_thread_from_rollout`, and `fork_thread` were inlining the larger
spawn/resume futures beneath them.
- `core_test_support::test_codex` added another wrapper layer on top of
those same paths.
- `compact_resume_fork` adds a few more helpers, and this particular
test drives the resume/fork path multiple times.
On Windows, that was enough to push both the libtest thread and Tokio
worker threads over the edge. The previous 8 MiB test-thread workaround
proved the failure was stack-related, but it did not address the
underlying future size.
## How This Was Debugged
The useful debugging pattern here was to turn the CI-only failure into a
local low-stack repro.
1. First, remove the explicit large-stack harness so the test runs on
the normal `#[tokio::test]` path.
2. Build the test binary normally.
3. Re-run the already-built `tests/all` binary directly with
progressively smaller `RUST_MIN_STACK` values.
Running the built binary directly matters: it keeps the reduced stack
size focused on the test process instead of also applying it to `cargo`
and `rustc`.
That made it possible to answer two questions quickly:
- Does the failure still reproduce without the workaround? Yes.
- Does boxing the wrapper futures actually buy back stack headroom? Also
yes.
After this change, the built test binary passes with
`RUST_MIN_STACK=917504` and still overflows at `786432`, which is enough
evidence to justify removing the explicit 8 MiB override while keeping a
deterministic low-stack repro for future debugging.
If we hit a similar issue again, the first places to inspect are thin
`async fn` wrappers that mostly forward into a much larger async
implementation.
## `Box::pin()` Primer
`async fn` compiles into a state machine. If a wrapper does this:
```rust
async fn wrapper() {
inner().await;
}
```
then `wrapper()` stores the full `inner()` future inline as part of its
own state.
If the wrapper instead does this:
```rust
async fn wrapper() {
Box::pin(inner()).await;
}
```
then the child future lives on the heap, and the outer future only
stores a pinned pointer to it. That usually trades one allocation for a
substantially smaller outer future, which is exactly the tradeoff we
want when the problem is stack pressure rather than raw CPU time.
Useful references:
-
[`Box::pin`](https://doc.rust-lang.org/std/boxed/struct.Box.html#method.pin)
- [Async book:
Pinning](https://rust-lang.github.io/async-book/04_pinning/01_chapter.html)
## What Changed
- Boxed the wrapper futures in `core/src/thread_manager.rs` around
`start_thread`, `resume_thread_from_rollout`, `fork_thread`, and the
corresponding `ThreadManagerState` spawn helpers so callers no longer
inline the full spawn/resume state machine through multiple layers.
- Boxed the matching test-only wrapper futures in
`core/tests/common/test_codex.rs` and
`core/tests/suite/compact_resume_fork.rs`, which sit directly on top of
the same path.
- Restored `compact_resume_after_second_compaction_preserves_history` in
`core/tests/suite/compact_resume_fork.rs` to a normal `#[tokio::test]`
and removed the explicit `TEST_STACK_SIZE_BYTES` thread/runtime sizing.
- Simplified a tiny helper in `compact_resume_fork` by making
`fetch_conversation_path()` synchronous, which removes one more
unnecessary future layer from the test path.
## Verification
- `cargo test -p codex-core --test all
suite::compact_resume_fork::compact_resume_after_second_compaction_preserves_history
-- --exact --nocapture`
- `cargo test -p codex-core --test all suite::compact_resume_fork --
--nocapture`
- Re-ran the built `codex-core` `tests/all` binary directly with reduced
stack sizes:
- `RUST_MIN_STACK=917504` passes
- `RUST_MIN_STACK=786432` still overflows
- `cargo test -p codex-core`
- Still fails locally in unrelated existing integration areas that
expect the `codex` / `test_stdio_server` binaries or hit the existing
`search_tool` wiremock mismatches.
## Why
Enterprises can already constrain approvals, sandboxing, and web search
through `requirements.toml` and MDM, but feature flags were still only
configurable as managed defaults. That meant an enterprise could suggest
feature values, but it could not actually pin them.
This change closes that gap and makes enterprise feature requirements
behave like the other constrained settings. The effective feature set
now stays consistent with enterprise requirements during config load,
when config writes are validated, and when runtime code mutates feature
flags later in the session.
It also tightens the runtime API for managed features. `ManagedFeatures`
now follows the same constraint-oriented shape as `Constrained<T>`
instead of exposing panic-prone mutation helpers, and production code
can no longer construct it through an unconstrained `From<Features>`
path.
The PR also hardens the `compact_resume_fork` integration coverage on
Windows. After the feature-management changes,
`compact_resume_after_second_compaction_preserves_history` was
overflowing the libtest/Tokio thread stacks on Windows, so the test now
uses an explicit larger-stack harness as a pragmatic mitigation. That
may not be the ideal root-cause fix, and it merits a parallel
investigation into whether part of the async future chain should be
boxed to reduce stack pressure instead.
## What Changed
Enterprises can now pin feature values in `requirements.toml` with the
requirements-side `features` table:
```toml
[features]
personality = true
unified_exec = false
```
Only canonical feature keys are allowed in the requirements `features`
table; omitted keys remain unconstrained.
- Added a requirements-side pinned feature map to
`ConfigRequirementsToml`, threaded it through source-preserving
requirements merge and normalization in `codex-config`, and made the
TOML surface use `[features]` (while still accepting legacy
`[feature_requirements]` for compatibility).
- Exposed `featureRequirements` from `configRequirements/read`,
regenerated the JSON/TypeScript schema artifacts, and updated the
app-server README.
- Wrapped the effective feature set in `ManagedFeatures`, backed by
`ConstrainedWithSource<Features>`, and changed its API to mirror
`Constrained<T>`: `can_set(...)`, `set(...) -> ConstraintResult<()>`,
and result-returning `enable` / `disable` / `set_enabled` helpers.
- Removed the legacy-usage and bulk-map passthroughs from
`ManagedFeatures`; callers that need those behaviors now mutate a plain
`Features` value and reapply it through `set(...)`, so the constrained
wrapper remains the enforcement boundary.
- Removed the production loophole for constructing unconstrained
`ManagedFeatures`. Non-test code now creates it through the configured
feature-loading path, and `impl From<Features> for ManagedFeatures` is
restricted to `#[cfg(test)]`.
- Rejected legacy feature aliases in enterprise feature requirements,
and return a load error when a pinned combination cannot survive
dependency normalization.
- Validated config writes against enterprise feature requirements before
persisting changes, including explicit conflicting writes and
profile-specific feature states that normalize into invalid
combinations.
- Updated runtime and TUI feature-toggle paths to use the constrained
setter API and to persist or apply the effective post-constraint value
rather than the requested value.
- Updated the `core_test_support` Bazel target to include the bundled
core model-catalog fixtures in its runtime data, so helper code that
resolves `core/models.json` through runfiles works in remote Bazel test
environments.
- Renamed the core config test coverage to emphasize that effective
feature values are normalized at runtime, while conflicting persisted
config writes are rejected.
- Ran `compact_resume_after_second_compaction_preserves_history` inside
an explicit 8 MiB test thread and Tokio runtime worker stack, following
the existing larger-stack integration-test pattern, to keep the Windows
`compact_resume_fork` test slice from aborting while a parallel
investigation continues into whether some of the underlying async
futures should be boxed.
## Verification
- `cargo test -p codex-config`
- `cargo test -p codex-core feature_requirements_ -- --nocapture`
- `cargo test -p codex-core
load_requirements_toml_produces_expected_constraints -- --nocapture`
- `cargo test -p codex-core
compact_resume_after_second_compaction_preserves_history -- --nocapture`
- `cargo test -p codex-core compact_resume_fork -- --nocapture`
- Re-ran the built `codex-core` `tests/all` binary with
`RUST_MIN_STACK=262144` for
`compact_resume_after_second_compaction_preserves_history` to confirm
the explicit-stack harness fixes the deterministic low-stack repro.
- `cargo test -p codex-core`
- This still fails locally in unrelated integration areas that expect
the `codex` / `test_stdio_server` binaries or hit existing `search_tool`
wiremock mismatches.
## Docs
`developers.openai.com/codex` should document the requirements-side
`[features]` table for enterprise and MDM-managed configuration,
including that it only accepts canonical feature keys and that
conflicting config writes are rejected.
load plugin-apps from `.app.json`.
make apps runtime-mentionable iff `codex_apps` MCP actually exposes
tools for that `connector_id`.
if the app isn't available, it's filtered out of runtime connector set,
so no tools are added and no app-mentions resolve.
right now we don't have a clean cli-side error for an app not being
installed. can look at this after.
### Tests
Added tests, tested locally that using a plugin that bundles an app
picks up the app.
## Summary
Instead of always adding inner function call outputs to the model
context, let js code decide which ones to return.
- Stop auto-hoisting nested tool outputs from `codex.tool(...)` into the
outer `js_repl` function output.
- Keep `codex.tool(...)` return values unchanged as structured JS
objects.
- Add `codex.emitImage(...)` as the explicit path for attaching an image
to the outer `js_repl` function output.
- Support emitting from a direct image URL, a single `input_image` item,
an explicit `{ bytes, mimeType }` object, or a raw tool response object
containing exactly one image.
- Preserve existing `view_image` original-resolution behavior when JS
emits the raw `view_image` tool result.
- Suppress the special `ViewImageToolCall` event for `js_repl`-sourced
`view_image` calls so nested inspection stays side-effect free until JS
explicitly emits.
- Update the `js_repl` docs and generated project instructions with both
recommended patterns:
- `await codex.emitImage(codex.tool("view_image", { path }))`
- `await codex.emitImage({ bytes: await page.screenshot({ type: "jpeg",
quality: 85 }), mimeType: "image/jpeg" })`
#### [git stack](https://github.com/magus/git-stack-cli)
- ✅ `1` https://github.com/openai/codex/pull/13050
- 👉 `2` https://github.com/openai/codex/pull/13331
- ⏳ `3` https://github.com/openai/codex/pull/13049
## Summary
Add original-resolution support for `view_image` behind the
under-development `view_image_original_resolution` feature flag.
When the flag is enabled and the target model is `gpt-5.3-codex` or
newer, `view_image` now preserves original PNG/JPEG/WebP bytes and sends
`detail: "original"` to the Responses API instead of using the legacy
resize/compress path.
## What changed
- Added `view_image_original_resolution` as an under-development feature
flag.
- Added `ImageDetail` to the protocol models and support for serializing
`detail: "original"` on tool-returned images.
- Added `PromptImageMode::Original` to `codex-utils-image`.
- Preserves original PNG/JPEG/WebP bytes.
- Keeps legacy behavior for the resize path.
- Updated `view_image` to:
- use the shared `local_image_content_items_with_label_number(...)`
helper in both code paths
- select original-resolution mode only when:
- the feature flag is enabled, and
- the model slug parses as `gpt-5.3-codex` or newer
- Kept local user image attachments on the existing resize path; this
change is specific to `view_image`.
- Updated history/image accounting so only `detail: "original"` images
use the docs-based GPT-5 image cost calculation; legacy images still use
the old fixed estimate.
- Added JS REPL guidance, gated on the same feature flag, to prefer JPEG
at 85% quality unless lossless is required, while still allowing other
formats when explicitly requested.
- Updated tests and helper code that construct
`FunctionCallOutputContentItem::InputImage` to carry the new `detail`
field.
## Behavior
### Feature off
- `view_image` keeps the existing resize/re-encode behavior.
- History estimation keeps the existing fixed-cost heuristic.
### Feature on + `gpt-5.3-codex+`
- `view_image` sends original-resolution images with `detail:
"original"`.
- PNG/JPEG/WebP source bytes are preserved when possible.
- History estimation uses the GPT-5 docs-based image-cost calculation
for those `detail: "original"` images.
#### [git stack](https://github.com/magus/git-stack-cli)
- 👉 `1` https://github.com/openai/codex/pull/13050
- ⏳ `2` https://github.com/openai/codex/pull/13331
- ⏳ `3` https://github.com/openai/codex/pull/13049
Update config.toml plugin entries to use
<plugin_name>@<marketplace_name> as the key.
Plugin now stays in
[plugins/cache/marketplace-name/plugin-name/$version/]
Clean up the plugin code structure.
Add plugin install functionality (not used yet).
## Summary
- Route delegated realtime handoff turns from all handoff message texts,
preserving order
- Fallback to input_transcript only when no messages are present
- Add regression coverage for multi-message handoff requests
- add a local Fast mode setting in codex-core (similar to how model id
is currently stored on disk locally)
- send `service_tier=priority` on requests when Fast is enabled
- add `/fast` in the TUI and persist it locally
- feature flag
## Summary
This change removes the compiled permissions field from skill metadata
and keeps permission_profile as the single source of truth.
Skill loading no longer compiles skill permissions eagerly. Instead, the
zsh-fork skill escalation path compiles `skill.permission_profile` when
it needs to determine the sandbox to apply for a skill script.
## Behavior change
For skills that declare:
```
permissions: {}
```
we now treat that the same as having no skill permissions override,
instead of creating and using a default readonly sandbox. This change
makes the behavior more intuitive:
- only non-empty skill permission profiles affect sandboxing
- omitting permissions and writing permissions: {} now mean the same
thing
- skill metadata keeps a single permissions representation instead of
storing derived state too
Overall, this makes skill sandbox behavior easier to understand and more
predictable.
- migrate the realtime websocket transport to the new session and
handoff flow
- make the realtime model configurable in config.toml and use API-key
auth for the websocket
---------
Co-authored-by: Codex <noreply@openai.com>
## Summary
- record a realtime close developer message when a new realtime session
replaces an active one
- assert the replacement marker through the mocked responses request
path
---------
Co-authored-by: Codex <noreply@openai.com>
Co-authored-by: Charles Cunningham <ccunningham@openai.com>
Support loading plugins.
Plugins can now be enabled via [plugins.<name>] in config.toml. They are
loaded as first-class entities through PluginsManager, and their default
skills/ and .mcp.json contributions are integrated into the existing
skills and MCP flows.
## Why
[#12964](https://github.com/openai/codex/pull/12964) added
`host_executable()` support to `codex-execpolicy`, but the zsh-fork
interception path in `unix_escalation.rs` was still evaluating commands
with the default exact-token matcher.
That meant an intercepted absolute executable such as `/usr/bin/git
status` could still miss basename rules like `prefix_rule(pattern =
["git", "status"])`, even when the policy also defined a matching
`host_executable(name = "git", ...)` entry.
This PR adopts the new matching behavior in the zsh-fork runtime only.
That keeps the rollout intentionally narrow: zsh-fork already requires
explicit user opt-in, so it is a safer first caller to exercise the new
`host_executable()` scheme before expanding it to other execpolicy call
sites.
It also brings zsh-fork back in line with the current `prefix_rule()`
execution model. Until prefix rules can carry their own permission
profiles, a matched `prefix_rule()` is expected to rerun the intercepted
command unsandboxed on `allow`, or after the user accepts `prompt`,
instead of merely continuing inside the inherited shell sandbox.
## What Changed
- added `evaluate_intercepted_exec_policy()` in
`core/src/tools/runtimes/shell/unix_escalation.rs` to centralize
execpolicy evaluation for intercepted commands
- switched intercepted direct execs in the zsh-fork path to
`check_multiple_with_options(...)` with `MatchOptions {
resolve_host_executables: true }`
- added `commands_for_intercepted_exec_policy()` so zsh-fork policy
evaluation works from intercepted `(program, argv)` data instead of
reconstructing a synthetic command before matching
- left shell-wrapper parsing intentionally disabled by default behind
`ENABLE_INTERCEPTED_EXEC_POLICY_SHELL_WRAPPER_PARSING`, so
path-sensitive matching relies on later direct exec interception rather
than shell-script parsing
- made matched `prefix_rule()` decisions rerun intercepted commands with
`EscalationExecution::Unsandboxed`, while unmatched-command fallback
keeps the existing sandbox-preserving behavior
- extracted the zsh-fork test harness into
`core/tests/common/zsh_fork.rs` so both the skill-focused and
approval-focused integration suites can exercise the same runtime setup
- limited this change to the intercepted zsh-fork path rather than
changing every execpolicy caller at once
- added runtime coverage in
`core/src/tools/runtimes/shell/unix_escalation_tests.rs` for allowed and
disallowed `host_executable()` mappings and the wrapper-parsing modes
- added integration coverage in `core/tests/suite/approvals.rs` to
verify a saved `prefix_rule(pattern=["touch"], decision="allow")` reruns
under zsh-fork outside a restrictive `WorkspaceWrite` sandbox
---
[//]: # (BEGIN SAPLING FOOTER)
Stack created with [Sapling](https://sapling-scm.com). Best reviewed
with [ReviewStack](https://reviewstack.dev/openai/codex/pull/13046).
* #13065
* __->__ #13046
## Summary
This PR unifies rollout history reconstruction and resume/fork metadata
hydration under a single `Session::reconstruct_history_from_rollout`
implementation.
The key change from main is that replay metadata now comes from the same
reconstruction pass that rebuilds model-visible history, instead of
doing a second bespoke rollout scan to recover `previous_model` /
`reference_context_item`.
## What Changed
### Unified reconstruction output
`reconstruct_history_from_rollout` now returns a single
`RolloutReconstruction` bundle containing:
- rebuilt `history`
- `previous_model`
- `reference_context_item`
Resume and fork both consume that shared output directly.
### Reverse replay core
The reconstruction logic moved into
`codex-rs/core/src/codex/rollout_reconstruction.rs` and now scans
rollout items newest-to-oldest.
That reverse pass:
- derives `previous_model`
- derives whether `reference_context_item` is preserved or cleared
- stops early once it has both resume metadata and a surviving
`replacement_history` checkpoint
History materialization is still bridged eagerly for now by replaying
only the surviving suffix forward, which keeps the history result stable
while moving the control flow toward the future lazy reverse loader
design.
### Removed bespoke context lookup
This deletes `last_rollout_regular_turn_context_lookup` and its separate
compaction-aware scan.
The previous model / baseline metadata is now computed from the same
replay state that rebuilds history, so resume/fork cannot drift from the
reconstructed transcript view.
### `TurnContextItem` persistence contract
`TurnContextItem` is now treated as the replay source of truth for
durable model-visible baselines.
This PR keeps the following contract explicit:
- persist `TurnContextItem` for the first real user turn so resume can
recover `previous_model`
- persist it for later turns that emit model-visible context updates
- if mid-turn compaction reinjects full initial context into replacement
history, persist a fresh `TurnContextItem` after `Compacted` so
resume/fork can re-establish the baseline from the rewritten history
- do not treat manual compaction or pre-sampling compaction as creating
a new durable baseline on their own
## Behavior Preserved
- rollback replay stays aligned with `drop_last_n_user_turns`
- rollback skips only user turns
- incomplete active user turns are dropped before older finalized turns
when rollback applies
- unmatched aborts do not consume the current active turn
- missing abort IDs still conservatively clear stale compaction state
- compaction clears `reference_context_item` until a later
`TurnContextItem` re-establishes it
- `previous_model` still comes from the newest surviving user turn that
established one
## Tests
Targeted validation run for the current branch shape:
- `cd codex-rs && cargo test -p codex-core --lib
codex::rollout_reconstruction_tests -- --nocapture`
- `cd codex-rs && just fmt`
The branch also extracts the rollout reconstruction tests into
`codex-rs/core/src/codex/rollout_reconstruction_tests.rs` so this logic
has a dedicated home instead of living inline in `codex.rs`.
## Why
`PermissionProfile` should describe filesystem roots as absolute paths
at the type level. Using `PathBuf` in `FileSystemPermissions` made the
shared type too permissive and blurred together three different
deserialization cases:
- skill metadata in `agents/openai.yaml`, where relative paths should
resolve against the skill directory
- app-server API payloads, where callers should have to send absolute
paths
- local tool-call payloads for commands like `shell_command` and
`exec_command`, where `additional_permissions.file_system` may
legitimately be relative to the command `workdir`
This change tightens the shared model without regressing the existing
local command flow.
## What Changed
- changed `protocol::models::FileSystemPermissions` and the app-server
`AdditionalFileSystemPermissions` mirror to use `AbsolutePathBuf`
- wrapped skill metadata deserialization in `AbsolutePathBufGuard`, so
relative permission roots in `agents/openai.yaml` resolve against the
containing skill directory
- kept app-server/API deserialization strict, so relative
`additionalPermissions.fileSystem.*` paths are rejected at the boundary
- restored cwd/workdir-relative deserialization for local tool-call
payloads by parsing `shell`, `shell_command`, and `exec_command`
arguments under an `AbsolutePathBufGuard` rooted at the resolved command
working directory
- simplified runtime additional-permission normalization so it only
canonicalizes and deduplicates absolute roots instead of trying to
recover relative ones later
- updated the app-server schema fixtures, `app-server/README.md`, and
the affected transport/TUI tests to match the final behavior
- replace show_nux with structured availability_nux model metadata
- expose availability NUX data through the app-server model API
- update shared fixtures and tests for the new field
Addresses bug https://github.com/openai/codex/issues/12589
Builds on community PR #12763.
This adds `oauth_resource` support for MCP `streamable_http` servers and
wires it through the relevant config and login paths. It fixes the bug
where the configured OAuth resource was not reliably included in the
authorization request, causing MCP login to omit the expected
`resource` parameter.
## Summary
This changes `custom_tool_call_output` to use the same output payload
shape as `function_call_output`, so freeform tools can return either
plain text or structured content items.
The main goal is to let `js_repl` return image content from nested
`view_image` calls in its own `custom_tool_call_output`, instead of
relying on a separate injected message.
## What changed
- Changed `custom_tool_call_output.output` from `string` to
`FunctionCallOutputPayload`
- Updated freeform tool plumbing to preserve structured output bodies
- Updated `js_repl` to aggregate nested tool content items and attach
them to the outer `js_repl` result
- Removed the old `js_repl` special case that injected `view_image`
results as a separate pending user image message
- Updated normalization/history/truncation paths to handle multimodal
`custom_tool_call_output`
- Regenerated app-server protocol schema artifacts
## Behavior
Direct `view_image` calls still return a `function_call_output` with
image content.
When `view_image` is called inside `js_repl`, the outer `js_repl`
`custom_tool_call_output` now carries:
- an `input_text` item if the JS produced text output
- one or more `input_image` items from nested tool results
So the nested image result now stays inside the `js_repl` tool output
instead of being injected as a separate message.
## Compatibility
This is intended to be backward-compatible for resumed conversations.
Older histories that stored `custom_tool_call_output.output` as a plain
string still deserialize correctly, and older histories that used the
previous injected-image-message flow also continue to resume.
Added regression coverage for resuming a pre-change rollout containing:
- string-valued `custom_tool_call_output`
- legacy injected image message history
#### [git stack](https://github.com/magus/git-stack-cli)
- 👉 `1` https://github.com/openai/codex/pull/12948
## Summary\n- add a websocket test-server request waiter so tests can
synchronize on recorded client messages\n- use that waiter in the
realtime delegation test instead of a fixed audio timeout\n- add
temporary timing logs in the test and websocket mock to inspect where
the flake stalls
