# 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.
### What
Add JSON Schema generation for `config.toml`, with checked‑in
`docs/config.schema.json`. We can move the schema elsewhere if preferred
(and host it if there's demand).
Add fixture test to prevent drift and `just write-config-schema` to
regenerate on schema changes.
Generate MCP config schema from `RawMcpServerConfig` instead of
`McpServerConfig` because that is the runtime type used for
deserialization.
Populate feature flag values into generated schema so they can be
autocompleted.
### Tests
Added tests + regenerate script to prevent drift. Tested autocompletions
using generated jsonschema locally with Even Better TOML.
https://github.com/user-attachments/assets/5aa7cd39-520c-4a63-96fb-63798183d0bc
Add metrics capabilities to Codex. The `README.md` is up to date.
This will not be merged with the metrics before this PR of course:
https://github.com/openai/codex/pull/8350
Adds a new feature
`enable_request_compression` that will compress using zstd requests to
the codex-backend. Currently only enabled for codex-backend so only enabled for openai providers when using chatgpt::auth even when the feature is enabled
Added a new info log line too for evaluating the compression ratio and
overhead off compressing before requesting. You can enable with
`RUST_LOG=$RUST_LOG,codex_client::transport=info`
```
2026-01-06T00:09:48.272113Z INFO codex_client::transport: Compressed request body with zstd pre_compression_bytes=28914 post_compression_bytes=11485 compression_duration_ms=0
```
Add `web_search_cached` feature to config. Enables `web_search` tool
with access only to cached/indexed results (see
[docs](https://platform.openai.com/docs/guides/tools-web-search#live-internet-access)).
This takes precedence over the existing `web_search_request`, which
continues to enable `web_search` over live results as it did before.
`web_search_cached` is disabled for review mode, as `web_search_request`
is.
- We now support `.codex/config.toml` in repo (from `cwd` up to the
first `.git` found, if any) as layers in `ConfigLayerStack`. A new
`ConfigLayerSource::Project` variant was added to support this.
- In doing this work, I realized that we were resolving relative paths
in `config.toml` after merging everything into one `toml::Value`, which
is wrong: paths should be relativized with respect to the folder
containing the `config.toml` that was deserialized. This PR introduces a
deserialize/re-serialize strategy to account for this in
`resolve_config_paths()`. (This is why `Serialize` is added to so many
types as part of this PR.)
- Added tests to verify this new behavior.
---
[//]: # (BEGIN SAPLING FOOTER)
Stack created with [Sapling](https://sapling-scm.com). Best reviewed
with [ReviewStack](https://reviewstack.dev/openai/codex/pull/8354).
* #8359
* __->__ #8354
## Summary
Adds a FeatureFlag to enforce UTF8 encoding in powershell, particularly
Windows Powershell v5. This should help address issues like #7290.
Notably, this PR does not include the ability to parse `apply_patch`
invocations within UTF8 shell commands (calls to the freeform tool
should not be impacted). I am leaving this out of scope for now. We
should address before this feature becomes Stable, but those cases are
not the default behavior at this time so we're okay for experimentation
phase. We should continue cleaning up the `apply_patch::invocation`
logic and then can handle it more cleanly.
## Testing
- [x] Adds additional testing
### Summary
With codesigning on Mac, Windows and Linux, we should be able to safely
remove `features.rmcp_client` and `use_experimental_use_rmcp_client`
check from the codebase now.
1. Remove PUBLIC skills and introduce SYSTEM skills embedded in the
binary and installed into $CODEX_HOME/skills/.system at startup.
2. Skills are now always enabled (feature flag removed).
3. Update skills/list to accept forceReload and plumb it through (not
used by clients yet).
Introduce a new codex-tui2 crate that re-exports the existing
interactive TUI surface and delegates run_main directly to codex-tui.
This keeps behavior identical while giving tui2 its own crate for future
viewport work.
Wire the codex CLI to select the frontend via the tui2 feature flag.
When the merged CLI overrides include features.tui2=true (e.g. via
--enable tui2), interactive runs are routed through
codex_tui2::run_main; otherwise they continue to use the original
codex_tui::run_main.
Register Feature::Tui2 in the core feature registry and add the tui2
crate and dependency entries so the new frontend builds alongside the
existing TUI.
This is a stub that only wires up the feature flag for this.
<img width="619" height="364" alt="image"
src="https://github.com/user-attachments/assets/4893f030-932f-471e-a443-63fe6b5d8ed9"
/>
# 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.
Add a warning message as a user turn to the model if the model does not
behave as expected (here, for example, if the model opens too many
`unified_exec` sessions)
This change prototypes support for Skills with the CLI. This is an
**experimental** feature for internal testing.
---------
Co-authored-by: Gav Verma <gverma@openai.com>
This PR threads execpolicy2 into codex-core.
activated via feature flag: exec_policy (on by default)
reads and parses all .codexpolicy files in `codex_home/codex`
refactored tool runtime API to integrate execpolicy logic
---------
Co-authored-by: Michael Bolin <mbolin@openai.com>
`--disable shell_tool` disables the built-in shell tool. This is useful
for MCP-only operation.
---------
Co-authored-by: Michael Bolin <mbolin@openai.com>
This adds support for a new variant of the shell tool behind a flag. To
test, run `codex` with `--enable shell_command_tool`, which will
register the tool with Codex under the name `shell_command` that accepts
the following shape:
```python
{
command: str
workdir: str | None,
timeout_ms: int | None,
with_escalated_permissions: bool | None,
justification: str | None,
}
```
This is comparable to the existing tool registered under
`shell`/`container.exec`. The primary difference is that it accepts
`command` as a `str` instead of a `str[]`. The `shell_command` tool
executes by running `execvp(["bash", "-lc", command])`, though the exact
arguments to `execvp(3)` depend on the user's default shell.
The hypothesis is that this will simplify things for the model. For
example, on Windows, instead of generating:
```json
{"command": ["pwsh.exe", "-NoLogo", "-Command", "ls -Name"]}
```
The model could simply generate:
```json
{"command": "ls -Name"}
```
As part of this change, I extracted some logic out of `user_shell.rs` as
`Shell::derive_exec_args()` so that it can be reused in
`codex-rs/core/src/tools/handlers/shell.rs`. Note the original code
generated exec arg lists like:
```javascript
["bash", "-lc", command]
["zsh", "-lc", command]
["pwsh.exe", "-NoProfile", "-Command", command]
```
Using `-l` for Bash and Zsh, but then specifying `-NoProfile` for
PowerShell seemed inconsistent to me, so I changed this in the new
implementation while also adding a `use_login_shell: bool` option to
make this explicit. If we decide to add a `login: bool` to
`ShellCommandToolCallParams` like we have for unified exec:
https://github.com/openai/codex/blob/807e2c27f0a9f2e85c50e7e6df5533f0d9b853c7/codex-rs/core/src/tools/handlers/unified_exec.rs#L33-L34
Then this should make it straightforward to support.
jif-oaiandGitHub
Ahmed IbrahimandGitHub
Dylan HurdandGitHub
pakrym-oaiandGitHub
sayan-oaiandGitHub
Channing CongerandGitHub
Michael BolinandGitHub
Shijie RaoandGitHub
xl-openaiandGitHub
Koichi ShiraishiandGitHub
iceweasel-oaiandGitHub
Eric TrautandGitHub
Josh McKinneyandGitHub
