## Summary
Changes the permission profile shape from a bare network boolean to a
nested object.
Before:
```yaml
permissions:
network: true
```
After:
```yaml
permissions:
network:
enabled: true
```
This also updates the shared Rust and app-server protocol types so
`PermissionProfile.network` is no longer `Option<bool>`, but
`Option<NetworkPermissions>` with `enabled: Option<bool>`.
## What Changed
- Updated `PermissionProfile` in `codex-rs/protocol/src/models.rs`:
- `pub network: Option<bool>` -> `pub network:
Option<NetworkPermissions>`
- Added `NetworkPermissions` with:
- `pub enabled: Option<bool>`
- Changed emptiness semantics so `network` is only considered empty when
`enabled` is `None`
- Updated skill metadata parsing to accept `permissions.network.enabled`
- Updated core permission consumers to read
`network.enabled.unwrap_or(false)` where a concrete boolean is needed
- Updated app-server v2 protocol types and regenerated schema/TypeScript
outputs
- Updated docs to mention `additionalPermissions.network.enabled`
## 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.
## Summary
`PermissionProfile.network` could not be preserved when additional or
compiled permissions resolved to
`SandboxPolicy::ReadOnly`, because `ReadOnly` had no network_access
field. This change makes read-only + network
enabled representable directly and threads that through the protocol,
app-server v2 mirror, and permission-
merging logic.
## What changed
- Added `network_access: bool` to `SandboxPolicy::ReadOnly` in the core
protocol and app-server v2 protocol.
- Kept backward compatibility by defaulting the new field to false, so
legacy read-only payloads still
deserialize unchanged.
- Updated `has_full_network_access()` and sandbox summaries to respect
read-only network access.
- Preserved PermissionProfile.network when:
- compiling skill permission profiles into sandbox policies
- normalizing additional permissions
- merging additional permissions into existing sandbox policies
- Updated the approval overlay to show network in the rendered
permission rule when requested.
- Regenerated app-server schema fixtures for the new v2 wire shape.
# External (non-OpenAI) Pull Request Requirements
Before opening this Pull Request, please read the dedicated
"Contributing" markdown file or your PR may be closed:
https://github.com/openai/codex/blob/main/docs/contributing.md
If your PR conforms to our contribution guidelines, replace this text
with a detailed and high quality description of your changes.
Include a link to a bug report or enhancement request.
• Keep Windows sandbox runner launches working from packaged installs by
running the helper from a user-owned runtime location.
On some Windows installs, the packaged helper location is difficult to
use reliably for sandboxed runner launches even though the binaries are
present. This change works around that by copying codex-
command-runner.exe into CODEX_HOME/.sandbox-bin/, reusing that copy
across launches, and falling back to the existing packaged-path lookup
if anything goes wrong.
The runtime copy lives in a dedicated directory with tighter ACLs than
.sandbox: sandbox users can read and execute the runner there, but they
cannot modify it. This keeps the workaround focused on the
command runner, leaves the setup helper on its trusted packaged path,
and adds logging so it is clear which runner path was selected at
launch.
### Summary
Propagate trace context originating at app-server RPC method handlers ->
codex core submission loop (so this includes spans such as `run_turn`!).
This implements PR 2 of the app-server tracing rollout.
This also removes the old lower-level env-based reparenting in core so
explicit request/submission ancestry wins instead of being overridden by
ambient `TRACEPARENT` state.
### What changed
- Added `trace: Option<W3cTraceContext>` to codex_protocol::Submission
- Taught `Codex::submit()` / `submit_with_id()` to automatically capture
the current span context when constructing or forwarding a submission
- Wrapped the core submission loop in a submission_dispatch span
parented from Submission.trace
- Warn on invalid submission trace carriers and ignore them cleanly
- Removed the old env-based downstream reparenting path in core task
execution
- Stopped OTEL provider init from implicitly attaching env trace context
process-wide
- Updated mcp-server Submission call sites for the new field
Added focused unit tests for:
- capturing trace context into Submission
- preferring `Submission.trace` when building the core dispatch span
### Why
PR 1 gave us consistent inbound request spans in app-server, but that
only covered the transport boundary. For long-running work like turns
and reviews, the important missing piece was preserving ancestry after
the request handler returns and core continues work on a different async
path.
This change makes that handoff explicit and keeps the parentage rules
simple:
- app-server request span sets the current context
- `Submission.trace` snapshots that context
- core restores it once, at the submission boundary
- deeper core spans inherit naturally
That also lets us stop relying on env-based reparenting for this path,
which was too ambient and could override explicit ancestry.
This adds a first-class app-server v2 `skills/changed` notification for
the existing skills live-reload signal.
Before this change, clients only had the legacy raw
`codex/event/skills_update_available` event. With this PR, v2 clients
can listen for a typed JSON-RPC notification instead of depending on the
legacy `codex/event/*` stream, which we want to remove soon.
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
