## Summary
This PR keeps app-server RPC request trace context alive for the full
lifetime of the work that request kicks off (e.g. for `thread/start`,
this is `app-server rpc handler -> tokio background task -> core op
submissions`). Previously we lose trace lineage once the request handler
returns or hands work off to background tasks.
This approach is especially relevant for `thread/start` and other RPC
handlers that run in a non-blocking way. In the near future we'll most
likely want to make all app-server handlers run in a non-blocking way by
default, and only queue operations that must operate in order (e.g.
thread RPCs per thread?), so we want to make sure tracing in app-server
just generally works.
Depends on https://github.com/openai/codex/pull/14300
**Before**
<img width="155" height="207" alt="image"
src="https://github.com/user-attachments/assets/c9487459-36f1-436c-beb7-fafeb40737af"
/>
**After**
<img width="299" height="337" alt="image"
src="https://github.com/user-attachments/assets/727392b2-d072-4427-9dc4-0502d8652dea"
/>
## What changed
- Keep request-scoped trace context around until we send the final
response or error, or the connection closes.
- Thread that trace context through detached `thread/start` work so
background startup stays attached to the originating request.
- Pass request trace context through to downstream core operations,
including:
- thread creation
- resume/fork flows
- turn submission
- review
- interrupt
- realtime conversation operations
- Add tracing tests that verify:
- remote W3C trace context is preserved for `thread/start`
- remote W3C trace context is preserved for `turn/start`
- downstream core spans stay under the originating request span
- request-scoped tracing state is cleaned up correctly
- Clean up shutdown behavior so detached background tasks and spawned
threads are drained before process exit.
## Summary
request_permissions flows should support persisting results for the
session.
Open Question: Still deciding if we need within-turn approvals - this
adds complexity but I could see it being useful
## Testing
- [x] Updated unit tests
---------
Co-authored-by: Codex <noreply@openai.com>
Adds a built-in `request_permissions` tool and wires it through the
Codex core, protocol, and app-server layers so a running turn can ask
the client for additional permissions instead of relying on a static
session policy.
The new flow emits a `RequestPermissions` event from core, tracks the
pending request by call ID, forwards it through app-server v2 as an
`item/permissions/requestApproval` request, and resumes the tool call
once the client returns an approved subset of the requested permission
profile.
## 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
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.
## Summary
- reuse the parent shell snapshot when spawning/forking/resuming
`SessionSource::SubAgent(SubAgentSource::ThreadSpawn { .. })` sessions
- plumb inherited snapshot through `AgentControl -> ThreadManager ->
Codex::spawn -> SessionConfiguration`
- skip shell snapshot refresh on cwd updates for thread-spawn subagents
so inherited snapshots are not replaced
## Why
- avoids per-subagent shell snapshot creation and cleanup work
- keeps thread-spawn subagents on the parent snapshot path, matching the
intended parent/child snapshot model
## Validation
- `just fmt` (in `codex-rs`)
- `cargo test -p codex-core --no-run`
- `cargo test -p codex-core spawn_agent -- --nocapture`
- `cargo test -p codex-core --test all
suite::agent_jobs::spawn_agents_on_csv_runs_and_exports`
## Notes
- full `cargo test -p codex-core --test all` was left running separately
for broader verification
Co-authored-by: Codex <noreply@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.
Command-approval clients currently infer which choices to show from
side-channel fields like `networkApprovalContext`,
`proposedExecpolicyAmendment`, and `additionalPermissions`. That makes
the request shape harder to evolve, and it forces each client to
replicate the server's heuristics instead of receiving the exact
decision list for the prompt.
This PR introduces a mapping between `CommandExecutionApprovalDecision`
and `codex_protocol::protocol::ReviewDecision`:
```rust
impl From<CoreReviewDecision> for CommandExecutionApprovalDecision {
fn from(value: CoreReviewDecision) -> Self {
match value {
CoreReviewDecision::Approved => Self::Accept,
CoreReviewDecision::ApprovedExecpolicyAmendment {
proposed_execpolicy_amendment,
} => Self::AcceptWithExecpolicyAmendment {
execpolicy_amendment: proposed_execpolicy_amendment.into(),
},
CoreReviewDecision::ApprovedForSession => Self::AcceptForSession,
CoreReviewDecision::NetworkPolicyAmendment {
network_policy_amendment,
} => Self::ApplyNetworkPolicyAmendment {
network_policy_amendment: network_policy_amendment.into(),
},
CoreReviewDecision::Abort => Self::Cancel,
CoreReviewDecision::Denied => Self::Decline,
}
}
}
```
And updates `CommandExecutionRequestApprovalParams` to have a new field:
```rust
available_decisions: Option<Vec<CommandExecutionApprovalDecision>>
```
when, if specified, should make it easier for clients to display an
appropriate list of options in the UI.
This makes it possible for `CoreShellActionProvider::prompt()` in
`unix_escalation.rs` to specify the `Vec<ReviewDecision>` directly,
adding support for `ApprovedForSession` when approving a skill script,
which was previously missing in the TUI.
Note this results in a significant change to `exec_options()` in
`approval_overlay.rs`, as the displayed options are now derived from
`available_decisions: &[ReviewDecision]`.
## What Changed
- Add `available_decisions` to
[`ExecApprovalRequestEvent`](de00e932dd/codex-rs/protocol/src/approvals.rs (L111-L175)),
including helpers to derive the legacy default choices when older
senders omit the field.
- Map `codex_protocol::protocol::ReviewDecision` to app-server
`CommandExecutionApprovalDecision` and expose the ordered list as
experimental `availableDecisions` in
[`CommandExecutionRequestApprovalParams`](de00e932dd/codex-rs/app-server-protocol/src/protocol/v2.rs (L3798-L3807)).
- Thread optional `available_decisions` through the core approval path
so Unix shell escalation can explicitly request `ApprovedForSession` for
session-scoped approvals instead of relying on client heuristics.
[`unix_escalation.rs`](de00e932dd/codex-rs/core/src/tools/runtimes/shell/unix_escalation.rs (L194-L214))
- Update the TUI approval overlay to build its buttons from the ordered
decision list, while preserving the legacy fallback when
`available_decisions` is missing.
- Update the app-server README, test client output, and generated schema
artifacts to document and surface the new field.
## Testing
- Add `approval_overlay.rs` coverage for explicit decision lists,
including the generic `ApprovedForSession` path and network approval
options.
- Update `chatwidget/tests.rs` and app-server protocol tests to populate
the new optional field and keep older event shapes working.
## Developers Docs
- If we document `item/commandExecution/requestApproval` on
[developers.openai.com/codex](https://developers.openai.com/codex), add
experimental `availableDecisions` as the preferred source of approval
choices and note that older servers may omit it.
Add service name to the app-server so that the app can use it's own
service name
This is on thread level because later we might plan the app-server to
become a singleton on the computer
## Summary
Introduces the initial implementation of Feature::RequestPermissions.
RequestPermissions allows the model to request that a command be run
inside the sandbox, with additional permissions, like writing to a
specific folder. Eventually this will include other rules as well, and
the ability to persist these permissions, but this PR is already quite
large - let's get the core flow working and go from there!
<img width="1279" height="541" alt="Screenshot 2026-02-15 at 2 26 22 PM"
src="https://github.com/user-attachments/assets/0ee3ec0f-02ec-4509-91a2-809ac80be368"
/>
## Testing
- [x] Added tests
- [x] Tested locally
- [x] Feature
zsh fork PR stack:
- https://github.com/openai/codex/pull/12051👈
- https://github.com/openai/codex/pull/12052
With upcoming support for a fork of zsh that allows us to intercept
`execve` and run execpolicy checks for each subcommand as part of a
`CommandExecution`, it will be possible for there to be multiple
approval requests for a shell command like `/path/to/zsh -lc 'git status
&& rg \"TODO\" src && make test'`.
To support that, this PR introduces a new `approval_id` field across
core, protocol, and app-server so that we can associate approvals
properly for subcommands.
### Description
#### Summary
Introduces the core plumbing required for structured network approvals
#### What changed
- Added structured network policy decision modeling in core.
- Added approval payload/context types needed for network approval
semantics.
- Wired shell/unified-exec runtime plumbing to consume structured
decisions.
- Updated related core error/event surfaces for structured handling.
- Updated protocol plumbing used by core approval flow.
- Included small CLI debug sandbox compatibility updates needed by this
layer.
#### Why
establishes the minimal backend foundation for network approvals without
yet changing high-level orchestration or TUI behavior.
#### Notes
- Behavior remains constrained by existing requirements/config gating.
- Follow-up PRs in the stack handle orchestration, UX, and app-server
integration.
---------
Co-authored-by: Codex <199175422+chatgpt-codex-connector[bot]@users.noreply.github.com>
This PR adds an experimental `persist_extended_history` bool flag to
app-server thread APIs so rollout logs can retain a richer set of
EventMsgs for non-lossy Thread > Turn > ThreadItems reconstruction (i.e.
on `thread/resume`).
### Motivation
Today, our rollout recorder only persists a small subset (e.g. user
message, reasoning, assistant message) of `EventMsg` types, dropping a
good number (like command exec, file change, etc.) that are important
for reconstructing full item history for `thread/resume`, `thread/read`,
and `thread/fork`.
Some clients want to be able to resume a thread without lossiness. This
lossiness is primarily a UI thing, since what the model sees are
`ResponseItem` and not `EventMsg`.
### Approach
This change introduces an opt-in `persist_full_history` flag to preserve
those events when you start/resume/fork a thread (defaults to `false`).
This is done by adding an `EventPersistenceMode` to the rollout
recorder:
- `Limited` (existing behavior, default)
- `Extended` (new opt-in behavior)
In `Extended` mode, persist additional `EventMsg` variants needed for
non-lossy app-server `ThreadItem` reconstruction. We now store the
following ThreadItems that we didn't before:
- web search
- command execution
- patch/file changes
- MCP tool calls
- image view calls
- collab tool outcomes
- context compaction
- review mode enter/exit
For **command executions** in particular, we truncate the output using
the existing `truncate_text` from core to store an upper bound of 10,000
bytes, which is also the default value for truncating tool outputs shown
to the model. This keeps the size of the rollout file and command
execution items returned over the wire reasonable.
And we also persist `EventMsg::Error` which we can now map back to the
Turn's status and populates the Turn's error metadata.
#### Updates to EventMsgs
To truly make `thread/resume` non-lossy, we also needed to persist the
`status` on `EventMsg::CommandExecutionEndEvent` and
`EventMsg::PatchApplyEndEvent`. Previously it was not obvious whether a
command failed or was declined (similar for apply_patch). These
EventMsgs were never persisted before so I made it a required field.
Problem:
1. turn id is constructed in-memory;
2. on resuming threads, turn_id might not be unique;
3. client cannot no the boundary of a turn from rollout files easily.
This PR does three things:
1. persist `task_started` and `task_complete` events;
1. persist `turn_id` in rollout turn events;
5. generate turn_id as unique uuids instead of incrementing it in
memory.
This helps us resolve the issue of clients wanting to have unique turn
ids for resuming a thread, and knowing the boundry of each turn in
rollout files.
example debug logs
```
2026-02-11T00:32:10.746876Z DEBUG codex_app_server_protocol::protocol::thread_history: built turn from rollout items turn_index=8 turn=Turn { id: "019c4a07-d809-74c3-bc4b-fd9618487b4b", items: [UserMessage { id: "item-24", content: [Text { text: "hi", text_elements: [] }] }, AgentMessage { id: "item-25", text: "Hi. I’m in the workspace with your current changes loaded and ready. Send the next task and I’ll execute it end-to-end." }], status: Completed, error: None }
2026-02-11T00:32:10.746888Z DEBUG codex_app_server_protocol::protocol::thread_history: built turn from rollout items turn_index=9 turn=Turn { id: "019c4a18-1004-76c0-a0fb-a77610f6a9b8", items: [UserMessage { id: "item-26", content: [Text { text: "hello", text_elements: [] }] }, AgentMessage { id: "item-27", text: "Hello. Ready for the next change in `codex-rs`; I can continue from the current in-progress diff or start a new task." }], status: Completed, error: None }
2026-02-11T00:32:10.746899Z DEBUG codex_app_server_protocol::protocol::thread_history: built turn from rollout items turn_index=10 turn=Turn { id: "019c4a19-41f0-7db0-ad78-74f1503baeb8", items: [UserMessage { id: "item-28", content: [Text { text: "hello", text_elements: [] }] }, AgentMessage { id: "item-29", text: "Hello. Send the specific change you want in `codex-rs`, and I’ll implement it and run the required checks." }], status: Completed, error: None }
```
backward compatibility:
if you try to resume an old session without task_started and
task_complete event populated, the following happens:
- If you resume and do nothing: those reconstructed historical IDs can
differ next time you resume.
- If you resume and send a new turn: the new turn gets a fresh UUID from
live submission flow and is persisted, so that new turn’s ID is stable
on later resumes.
I think this behavior is fine, because we only care about deterministic
turn id once a turn is triggered.
Add a centralized FileWatcher in codex-core (using notify) that watches
skill roots from the config layer stack (recursive)
Send `SkillsChanged` events when relevant file system changes are
detected
On `SkillsChanged`:
* Invalidate the skills cache immediately in ThreadManager
* Emit EventMsg::SkillsUpdateAvailable to active sessions
~~* Broadcast a new app-server notification:
SkillsListUpdatedNotification~~
This change does not inject new items into the event stream. That means
the agent will not know about new skills, so it won't be able to
implicitly invoke new skills. It also won't know about changes to
existing skills, so if it has already read the contents of a modified
skill, it will not honor the new behavior.
This change also does not detect modifications to AGENTS.md.
I plan to address these limitations in a follow-on PR modeled after
#9985. Injection of new skills and AGENTS was deemed to risky, hence the
need to split the feature into two stages. The changes in this PR were
designed to easily accommodate the second stage once we have some other
foundational changes in place.
Testing: In addition to automated tests, I did manual testing to confirm
that newly-created skills, deleted skills, and renamed skills are
reflected in the TUI skill picker menu. Also confirmed that
modifications to behaviors for explicitly-invoked skills are honored.
---------
Co-authored-by: Xin Lin <xl@openai.com>
One of our partners flagged that they were seeing the wrong order of
events when running `review/start` with command exec approvals:
```
{"method":"item/commandExecution/requestApproval","id":0,"params":{"threadId":"019c0b6b-6a42-7c02-99c4-98c80e88ac27","turnId":"0","itemId":"0","reason":"`/bin/zsh -lc 'git show b7a92b4eacf262c575f26b1e1ed621a357642e55 --stat'` requires approval: Xcode-required approval: Require explicit user confirmation for all commands.","proposedExecpolicyAmendment":null}}
{"method":"item/started","params":{"item":{"type":"commandExecution","id":"call_AEjlbHqLYNM7kbU3N6uw1CNi","command":"/bin/zsh -lc 'git show b7a92b4eacf262c575f26b1e1ed621a357642e55 --stat'","cwd":"/Users/devingreen/Desktop/SampleProject","processId":null,"status":"inProgress","commandActions":[{"type":"unknown","command":"git show b7a92b4eacf262c575f26b1e1ed621a357642e55 --stat"}],"aggregatedOutput":null,"exitCode":null,"durationMs":null},"threadId":"019c0b6b-6a42-7c02-99c4-98c80e88ac27","turnId":"0"}}
```
**Key fix**: In the review sub‑agent delegate we were forwarding exec
(and patch) approvals using the parent turn id (`parent_ctx.sub_id`) as
the approval call_id. That made
`item/commandExecution/requestApproval.itemId` differ from the actual
`item/started` id. We now forward the sub‑agent’s `call_id` from the
approval event instead, so the approval item id matches the
commandExecution item id in review flows.
Here’s the expected event order for an inline `review/start` that
triggers an exec approval after this fix:
1. Response to review/start (JSON‑RPC response)
- Includes `turn` (status inProgress) and `review_thread_id` (same as
parent thread for inline).
2. `turn/started` notification
- turnId is the review turn id (e.g., "0").
3. `item/started` → EnteredReviewMode
- item.id == turnId, marks entry into review mode.
4. `item/started` → commandExecution
- item.id == <call_id> (e.g., "review-call-1"), status: inProgress.
5. `item/commandExecution/requestApproval` request
- JSON‑RPC request (not a notification).
- params.itemId == <call_id> and params.turnId == turnId.
6. Client replies to approval request (Approved / Declined / etc).
7. If approved:
- Optional `item/commandExecution/outputDelta` notifications.
- `item/completed` → commandExecution with status and exitCode.
8. Review finishes:
- `item/started` → ExitedReviewMode
- `item/completed` → ExitedReviewMode
- (Agent message items may also appear, depending on review output.)
9. `turn/completed` notification
The key being #4 and #5 are now in the proper order with the correct
item id.
Session renaming:
- `/rename my_session`
- `/rename` without arg and passing an argument in `customViewPrompt`
- AppExitInfo shows resume hint using the session name if set instead of
uuid, defaults to uuid if not set
- Names are stored in `CODEX_HOME/sessions.jsonl`
Session resuming:
- codex resume <name> lookup for `CODEX_HOME/sessions.jsonl` first entry
matching the name and resumes the session
---------
Co-authored-by: jif-oai <jif@openai.com>
## Summary
Add dynamic tool injection to thread startup in API v2, wire dynamic
tool calls through the app server to clients, and plumb responses back
into the model tool pipeline.
### Flow (high level)
- Thread start injects `dynamic_tools` into the model tool list for that
thread (validation is done here).
- When the model emits a tool call for one of those names, core raises a
`DynamicToolCallRequest` event.
- The app server forwards it to the client as `item/tool/call`, waits
for the client’s response, then submits a `DynamicToolResponse` back to
core.
- Core turns that into a `function_call_output` in the next model
request so the model can continue.
### What changed
- Added dynamic tool specs to v2 thread start params and protocol types;
introduced `item/tool/call` (request/response) for dynamic tool
execution.
- Core now registers dynamic tool specs at request time and routes those
calls via a new dynamic tool handler.
- App server validates tool names/schemas, forwards dynamic tool call
requests to clients, and publishes tool outputs back into the session.
- Integration tests
Add implementation for the `wait` tool.
For this we consider all status different from `PendingInit` and
`Running` as terminal. The `wait` tool call will return either after a
given timeout or when the tool reaches a non-terminal status.
A few points to note:
* The usage of a channel is preferred to prevent some races (just
looping on `get_status()` could "miss" a terminal status)
* The order of operations is very important, we need to first subscribe
and then check the last known status to prevent race conditions
* If the channel gets dropped, we return an error on purpose
Added an agent control plane that lets sessions spawn or message other
conversations via `AgentControl`.
`AgentBus` (core/src/agent/bus.rs) keeps track of the last known status
of a conversation.
ConversationManager now holds shared state behind an Arc so AgentControl
keeps only a weak back-reference, the goal is just to avoid explicit
cycle reference.
Follow-ups:
* Build a small tool in the TUI to be able to see every agent and send
manual message to each of them
* Handle approval requests in this TUI
* Add tools to spawn/communicate between agents (see related design)
* Define agent types
What changed
- Added `outputSchema` support to the app-server APIs, mirroring `codex
exec --output-schema` behavior.
- V1 `sendUserTurn` now accepts `outputSchema` and constrains the final
assistant message for that turn.
- V2 `turn/start` now accepts `outputSchema` and constrains the final
assistant message for that turn (explicitly per-turn only).
Core behavior
- `Op::UserTurn` already supported `final_output_json_schema`; now V1
`sendUserTurn` forwards `outputSchema` into that field.
- `Op::UserInput` now carries `final_output_json_schema` for per-turn
settings updates; core maps it into
`SessionSettingsUpdate.final_output_json_schema` so it applies to the
created turn context.
- V2 `turn/start` does NOT persist the schema via `OverrideTurnContext`
(it’s applied only for the current turn). Other overrides
(cwd/model/etc) keep their existing persistent behavior.
API / docs
- `codex-rs/app-server-protocol/src/protocol/v1.rs`: add `output_schema:
Option<serde_json::Value>` to `SendUserTurnParams` (serialized as
`outputSchema`).
- `codex-rs/app-server-protocol/src/protocol/v2.rs`: add `output_schema:
Option<JsonValue>` to `TurnStartParams` (serialized as `outputSchema`).
- `codex-rs/app-server/README.md`: document `outputSchema` for
`turn/start` and clarify it applies only to the current turn.
- `codex-rs/docs/codex_mcp_interface.md`: document `outputSchema` for v1
`sendUserTurn` and v2 `turn/start`.
Tests added/updated
- New app-server integration tests asserting `outputSchema` is forwarded
into outbound `/responses` requests as `text.format`:
- `codex-rs/app-server/tests/suite/output_schema.rs`
- `codex-rs/app-server/tests/suite/v2/output_schema.rs`
- Added per-turn semantics tests (schema does not leak to the next
turn):
- `send_user_turn_output_schema_is_per_turn_v1`
- `turn_start_output_schema_is_per_turn_v2`
- Added protocol wire-compat tests for the merged op:
- serialize omits `final_output_json_schema` when `None`
- deserialize works when field is missing
- serialize includes `final_output_json_schema` when `Some(schema)`
Call site updates (high level)
- Updated all `Op::UserInput { .. }` constructions to include
`final_output_json_schema`:
- `codex-rs/app-server/src/codex_message_processor.rs`
- `codex-rs/core/src/codex_delegate.rs`
- `codex-rs/mcp-server/src/codex_tool_runner.rs`
- `codex-rs/tui/src/chatwidget.rs`
- `codex-rs/tui2/src/chatwidget.rs`
- plus impacted core tests.
Validation
- `just fmt`
- `cargo test -p codex-core`
- `cargo test -p codex-app-server`
- `cargo test -p codex-mcp-server`
- `cargo test -p codex-tui`
- `cargo test -p codex-tui2`
- `cargo test -p codex-protocol`
- `cargo clippy --all-features --tests --profile dev --fix -- -D
warnings`
last token count in context manager is initialized to 0. Gets populated
only on events from server.
This PR populates it on resume so we can decide if we need to compact or
not.
# 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.
https://github.com/openai/codex/pull/8235 introduced `ConfigBuilder` and
this PR updates all call non-test call sites to use it instead of
`Config::load_from_base_config_with_overrides()`.
This is important because `load_from_base_config_with_overrides()` uses
an empty `ConfigRequirements`, which is a reasonable default for testing
so the tests are not influenced by the settings on the host. This method
is now guarded by `#[cfg(test)]` so it cannot be used by business logic.
Because `ConfigBuilder::build()` is `async`, many of the test methods
had to be migrated to be `async`, as well. On the bright side, this made
it possible to eliminate a bunch of `block_on_future()` stuff.
refactor the way we load and manage skills:
1. Move skill discovery/caching into SkillsManager and reuse it across
sessions.
2. Add the skills/list API (Op::ListSkills/SkillsListResponse) to fetch
skills for one or more cwds. Also update app-server for VSCE/App;
3. Trigger skills/list during session startup so UIs preload skills and
handle errors immediately.
## Refactor of the `execpolicy` crate
To illustrate why we need this refactor, consider an agent attempting to
run `apple | rm -rf ./`. Suppose `apple` is allowed by `execpolicy`.
Before this PR, `execpolicy` would consider `apple` and `pear` and only
render one rule match: `Allow`. We would skip any heuristics checks on
`rm -rf ./` and immediately approve `apple | rm -rf ./` to run.
To fix this, we now thread a `fallback` evaluation function into
`execpolicy` that runs when no `execpolicy` rules match a given command.
In our example, we would run `fallback` on `rm -rf ./` and prevent
`apple | rm -rf ./` from being run without approval.
this PR enables TUI to approve commands and add their prefixes to an
allowlist:
<img width="708" height="605" alt="Screenshot 2025-11-21 at 4 18 07 PM"
src="https://github.com/user-attachments/assets/56a19893-4553-4770-a881-becf79eeda32"
/>
note: we only show the option to whitelist the command when
1) command is not multi-part (e.g `git add -A && git commit -m 'hello
world'`)
2) command is not already matched by an existing rule
This PR moves `ModelsFamily` to `openai_models`. It also propagates
`ModelsManager` to session services and use it to drive model family. We
also make `derive_default_model_family` private because it's a step
towards what we want: one place that gives model configuration.
This is a second step at having one source of truth for models
information and config: `ModelsManager`.
Next steps would be to remove `ModelsFamily` from config. That's massive
because it's being used in 41 occasions mostly pre launching `codex`.
Also, we need to make `find_family_for_model` private. It's also big
because it's being used in 21 occasions ~ all tests.
In this PR, I am exploring migrating task kind to an invocation of
Codex. The main reason would be getting rid off multiple
`ConversationHistory` state and streamlining our context/history
management.
This approach depends on opening a channel between the sub-codex and
codex. This channel is responsible for forwarding `interactive`
(`approvals`) and `non-interactive` events. The `task` is responsible
for handling those events.
This opens the door for implementing `codex as a tool`, replacing
`compact` and `review`, and potentially subagents.
One consideration is this code is very similar to `app-server` specially
in the approval part. If in the future we wanted an interactive
`sub-codex` we should consider using `codex-mcp`
