- production logic plus tests; cancel running tasks before clearing
pending turn state
- suppress follow-up model requests after cancellation and assert on
stabilized request counts instead of fixed sleeps
## 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>
## 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
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`
#### 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.
This branch:
* Avoid flushing DB when not necessary
* Filter events for which we perfom an `upsert` into the DB
* Add a dedicated update function of the `thread:updated_at` that is
lighter
This should significantly reduce the DB lock contention. If it is not
sufficient, we can de-sync the flush of the DB for `updated_at`
### Summary
This adds turn-level latency metrics for the first model output and the
first completed agent message.
- `codex.turn.ttft.duration_ms` starts at turn start and records on the
first output signal we see from the model. That includes normal
assistant text, reasoning deltas, and non-text outputs like tool-call
items.
- `codex.turn.ttfm.duration_ms` also starts at turn start, but it
records when the first agent message finishes streaming rather than when
its first delta arrives.
### Implementation notes
The timing is tracked in codex-core, not app-server, so the definition
stays consistent across CLI, TUI, and app-server clients.
I reused the existing turn lifecycle boundary that already drives
`codex.turn.e2e_duration_ms`, stored the turn start timestamp in turn
state, and record each metric once per turn.
I also wired the new metric names into the OTEL runtime metrics summary
so they show up in the same in-memory/debug snapshot path as the
existing timing metrics.
## Summary
- delete the network proxy admin server and its runtime listener/task
plumbing
- remove the admin endpoint config, runtime, requirement, protocol,
schema, and debug-surface fields
- update proxy docs to reflect the remaining HTTP and SOCKS listeners
only
- Replay thread rollback from the persisted rollout history instead of
truncating in-memory state.\n- Add rollback coverage, including
rollback-behind-compaction snapshot coverage.
## 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.
This adds a first-class server request for MCP server elicitations:
`mcpServer/elicitation/request`.
Until now, MCP elicitation requests only showed up as a raw
`codex/event/elicitation_request` event from core. That made it hard for
v2 clients to handle elicitations using the same request/response flow
as other server-driven interactions (like shell and `apply_patch`
tools).
This also updates the underlying MCP elicitation request handling in
core to pass through the full MCP request (including URL and form data)
so we can expose it properly in app-server.
### Why not `item/mcpToolCall/elicitationRequest`?
This is because MCP elicitations are related to MCP servers first, and
only optionally to a specific MCP tool call.
In the MCP protocol, elicitation is a server-to-client capability: the
server sends `elicitation/create`, and the client replies with an
elicitation result. RMCP models it that way as well.
In practice an elicitation is often triggered by an MCP tool call, but
not always.
### What changed
- add `mcpServer/elicitation/request` to the v2 app-server API
- translate core `codex/event/elicitation_request` events into the new
v2 server request
- map client responses back into `Op::ResolveElicitation` so the MCP
server can continue
- update app-server docs and generated protocol schema
- add an end-to-end app-server test that covers the full round trip
through a real RMCP elicitation flow
- The new test exercises a realistic case where an MCP tool call
triggers an elicitation, the app-server emits
mcpServer/elicitation/request, the client accepts it, and the tool call
resumes and completes successfully.
### app-server API flow
- Client starts a thread with `thread/start`.
- Client starts a turn with `turn/start`.
- App-server sends `item/started` for the `mcpToolCall`.
- While that tool call is in progress, app-server sends
`mcpServer/elicitation/request`.
- Client responds to that request with `{ action: "accept" | "decline" |
"cancel" }`.
- App-server sends `serverRequest/resolved`.
- App-server sends `item/completed` for the mcpToolCall.
- App-server sends `turn/completed`.
- If the turn is interrupted while the elicitation is pending,
app-server still sends `serverRequest/resolved` before the turn
finishes.
- lower `submission_dispatch` span logging to debug for realtime audio
submissions only
- keep other submission spans at info and add a targeted test for the
level selection
---------
Co-authored-by: Codex <noreply@openai.com>
### 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`.
This is PR 3 of the app-server tracing rollout.
PRs https://github.com/openai/codex/pull/13285 and
https://github.com/openai/codex/pull/13368 gave us inbound request spans
in app-server and propagated trace context through Submission. This
change finishes the next piece in core: when a request actually starts a
turn, we now create a core-owned long-lived span that stays open for the
real lifetime of the turn.
What changed:
- `Session::spawn_task` can now optionally create a long-lived turn span
and run the spawned task inside it
- `turn/start` uses that path, so normal turn execution stays under a
single core-owned span after the async handoff
- `review/start` uses the same pattern
- added a unit test that verifies the spawned turn task inherits the
submission dispatch trace ancestry
**Why**
The app-server request span is intentionally short-lived. Once work
crosses into core, we still want one span that covers the actual
execution window until completion or interruption. This keeps that
ownership where it belongs: in the layer that owns the runtime
lifecycle.
## 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
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.
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
- submit `Enter` steers immediately while a turn is already running
instead of routing them through `queued_user_messages`
- keep those submitted steers visible in the footer as `pending_steers`
until core records them as a user message or aborts the turn
- reconcile pending steers on `ItemCompleted(UserMessage)`, not
`RawResponseItem`
- emit user-message item lifecycle for leftover pending input at task
finish, then remove the TUI `TurnComplete` fallback
- keep `queued_user_messages` for actual queued drafts, rendered below
pending steers
## Problem
While the assistant was generating, pressing `Enter` could send the
input into `queued_user_messages`. That queue only drains after the turn
ends, so ordinary steers behaved like queued drafts instead of landing
at the next core sampling boundary.
The first version of this fix also used `RawResponseItem` to decide when
a steer had landed. Review feedback was that this is the wrong
abstraction for client behavior.
There was also a late edge case in core: if pending steer input was
accepted after the final sampling decision but before `TurnComplete`,
core would record that user message into history at task finish without
emitting `ItemStarted(UserMessage)` / `ItemCompleted(UserMessage)`. TUI
had a fallback to paper over that gap locally.
## Approach
- `Enter` during an active turn now submits a normal `Op::UserTurn`
immediately
- TUI keeps a local pending-steer preview instead of rendering that user
message into history immediately
- when core records the steer as `ItemCompleted(UserMessage)`, TUI
matches and removes the corresponding pending preview, then renders the
committed user message
- core now emits the same user-message lifecycle when
`on_task_finished(...)` drains leftover pending user input, before
`TurnComplete`
- with that lifecycle gap closed in core, TUI no longer needs to flush
pending steers into history on `TurnComplete`
- if the turn is interrupted, pending steers and queued drafts are both
restored into the composer, with pending steers first
## Notes
- `Tab` still uses the real queued-message path
- `queued_user_messages` and `pending_steers` are separate state with
separate semantics
- the pending-steer matching key is built directly from `UserInput`
- this removes the new TUI dependency on `RawResponseItem`
## Validation
- `just fmt`
- `cargo test -p codex-core
task_finish_emits_turn_item_lifecycle_for_leftover_pending_user_input --
--nocapture`
- `cargo test -p codex-tui`
followup to https://github.com/openai/codex/pull/13212 to expose fast
tier controls to app server
(majority of this PR is generated schema jsons - actual code is +69 /
-35 and +24 tests )
- add service tier fields to the app-server protocol surfaces used by
thread lifecycle, turn start, config, and session configured events
- thread service tier through the app-server message processor and core
thread config snapshots
- allow runtime config overrides to carry service tier for app-server
callers
cleanup:
- Removing useless "legacy" code supporting "standard" - we moved to
None | "fast", so "standard" is not needed.
- 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
- 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
- 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>
## 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.
## Summary
- skip online model refresh for subagent sessions
- avoid rollout flushes during subagent startup
- keep /models refresh for non-subagent sessions
## Testing
- cargo test -p codex-core --test all
suite::models_etag_responses::refresh_models_on_models_etag_mismatch_and_avoid_duplicate_models_fetch
- cargo test -p codex-core --test all
suite::remote_models::remote_models_long_model_slug_is_sent_with_high_reasoning
- cargo test -p codex-core --test all
suite::model_switching::model_switch_to_smaller_model_updates_token_context_window
- cargo test -p codex-core --test all
suite::compact::pre_sampling_compact_runs_on_switch_to_smaller_context_model
- cargo test -p codex-core --test all
suite::compact::pre_sampling_compact_runs_after_resume_and_switch_to_smaller_model
- cargo test -p codex-core --test all
suite::personality::remote_model_friendly_personality_instructions_with_feature
---------
Co-authored-by: Codex <noreply@openai.com>
## 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
The `notify` hook payload did not identify which Codex client started
the turn. That meant downstream notification hooks could not distinguish
between completions coming from the TUI and completions coming from
app-server clients such as VS Code or Xcode. Now that the Codex App
provides its own desktop notifications, it would be nice to be able to
filter those out.
This change adds that context without changing the existing payload
shape for callers that do not know the client name, and keeps the new
end-to-end test cross-platform.
## What changed
- added an optional top-level `client` field to the legacy `notify` JSON
payload
- threaded that value through `core` and `hooks`; the internal session
and turn state now carries it as `app_server_client_name`
- set the field to `codex-tui` for TUI turns
- captured `initialize.clientInfo.name` in the app server and applied it
to subsequent turns before dispatching hooks
- replaced the notify integration test hook with a `python3` script so
the test does not rely on Unix shell permissions or `bash`
- documented the new field in `docs/config.md`
## Testing
- `cargo test -p codex-hooks`
- `cargo test -p codex-tui`
- `cargo test -p codex-app-server
suite::v2::initialize::turn_start_notify_payload_includes_initialize_client_name
-- --exact --nocapture`
- `cargo test -p codex-core` (`src/lib.rs` passed; `core/tests/all.rs`
still has unrelated existing failures in this environment)
## Docs
The public config reference on `developers.openai.com/codex` should
mention that the legacy `notify` payload may include a top-level
`client` field. The TUI reports `codex-tui`, and the app server reports
`initialize.clientInfo.name` when it is available.
## Summary
This PR includes the session's local date and timezone in the
model-visible environment context and persists that data in
`TurnContextItem`.
## What changed
- captures the current local date and IANA timezone when building a turn
context, with a UTC fallback if the timezone lookup fails
- includes current_date and timezone in the serialized
<environment_context> payload
- stores those fields on TurnContextItem so they survive rollout/history
handling, subagent review threads, and resume flows
- treats date/timezone changes as environment updates, so prompt caching
and context refresh logic do not silently reuse stale time context
- updates tests to validate the new environment fields without depending
on a single hardcoded environment-context string
## test
built a local build and saw it in the rollout file:
```
{"timestamp":"2026-02-26T21:39:50.737Z","type":"response_item","payload":{"type":"message","role":"user","content":[{"type":"input_text","text":"<environment_context>\n <shell>zsh</shell>\n <current_date>2026-02-26</current_date>\n <timezone>America/Los_Angeles</timezone>\n</environment_context>"}]}}
```
Summary is a required parameter on UserTurn. Ideally we'd like the core
to decide the appropriate summary level.
Make the summary optional and don't send it when not needed.
