## Summary
This PR fully reverts the previously merged Agent Identity runtime
integration from the old stack:
https://github.com/openai/codex/pull/17387/changes
It removes the Codex-side task lifecycle wiring, rollout/session
persistence, feature flag plumbing, lazy `auth.json` mutation,
background task auth paths, and request callsite changes introduced by
that stack.
This leaves the repo in a clean pre-AgentIdentity integration state so
the follow-up PRs can reintroduce the pieces in smaller reviewable
layers.
## Stack
1. This PR: full revert
2. https://github.com/openai/codex/pull/18871: move Agent Identity
business logic into a crate
3. https://github.com/openai/codex/pull/18785: add explicit
AgentIdentity auth mode and startup task allocation
4. https://github.com/openai/codex/pull/18811: migrate auth callsites
through AuthProvider
## Testing
Tests: targeted Rust checks, cargo-shear, Bazel lock check, and CI.
Builds on top of #17659
Move the filesystem + sqlite thread listing-related operations inside of
a local ThreadStore implementation and call ThreadStore from the places
that used to perform these filesystem/sqlite operations.
This is the first of a series of PRs that will implement the rest of the
local ThreadStore.
Testing:
- added unit tests for the thread store implementation
- adjusted some unit tests in the realtime + personality packages whose
callsites changed. Specifically I'm trying to hide ThreadMetadata inside
of the local implementation and make ThreadMetadata a sqlite
implementation detail concern rather than a public interface, preferring
the more generate StoredThread interface instead
- added a corner case test for the personality migration package that
wasn't covered by the existing test suite
- adjust the behavior of searched thread listing to run the existing
local rollout repair/backfill pass _before_ querying SQLite results, so
callers using ThreadStore::list_threads do not miss matches after a
partial metadata warm-up
## Summary
Stack PR 2 of 4 for feature-gated agent identity support.
This PR adds agent identity registration behind
`features.use_agent_identity`. It keeps the app-server protocol
unchanged and starts registration after ChatGPT auth exists rather than
requiring a client restart.
## Stack
- PR1: https://github.com/openai/codex/pull/17385 - add
`features.use_agent_identity`
- PR2: https://github.com/openai/codex/pull/17386 - this PR
- PR3: https://github.com/openai/codex/pull/17387 - register agent tasks
when enabled
- PR4: https://github.com/openai/codex/pull/17388 - use `AgentAssertion`
downstream when enabled
## Validation
Covered as part of the local stack validation pass:
- `just fmt`
- `cargo test -p codex-core --lib agent_identity`
- `cargo test -p codex-core --lib agent_assertion`
- `cargo test -p codex-core --lib websocket_agent_task`
- `cargo test -p codex-api api_bridge`
- `cargo build -p codex-cli --bin codex`
## Notes
The full local app-server E2E path is still being debugged after PR
creation. The current branch stack is directionally ready for review
while that follow-up continues.
## Description
This PR introduces `review_id` as the stable identifier for guardian
reviews and exposes it in app-server `item/autoApprovalReview/started`
and `item/autoApprovalReview/completed` events.
Internally, guardian rejection state is now keyed by `review_id` instead
of the reviewed tool item ID. `target_item_id` is still included when a
review maps to a concrete thread item, but it is no longer overloaded as
the review lifecycle identifier.
## Motivation
We'd like to give users the ability to preempt a guardian review while
it's running (approve or decline).
However, we can't implement the API that allows the user to override a
running guardian review because we didn't have a unique `review_id` per
guardian review. Using `target_item_id` is not correct since:
- with execve reviews, there can be multiple execve calls (and therefore
guardian reviews) per shell command
- with network policy reviews, there is no target item ID
The PR that actually implements user overrides will use `review_id` as
the stable identifier.
## Summary
- reduce public module visibility across Rust crates, preferring private
or crate-private modules with explicit crate-root public exports
- update external call sites and tests to use the intended public crate
APIs instead of reaching through module trees
- add the module visibility guideline to AGENTS.md
## Validation
- `cargo check --workspace --all-targets --message-format=short` passed
before the final fix/format pass
- `just fix` completed successfully
- `just fmt` completed successfully
- `git diff --check` passed
## Summary
- make `CODEX_EXEC_SERVER_URL=none` map to an explicit disabled
environment mode instead of inferring from a missing URL
- expose environment capabilities (`exec_enabled`, `filesystem_enabled`)
so tool building can gate behavior explicitly and future
multi-environment work has a clearer seam
- suppress env-backed tools when the relevant capability is unavailable,
including exec tools, `js_repl`, `apply_patch`, `list_dir`, and
`view_image`
- keep handler/runtime backstops so disabled environments still reject
execution if a tool path somehow bypasses registration
## Testing
- `just fmt`
- `cargo test -p codex-exec-server`
- `cargo test -p codex-tools
disabled_environment_omits_environment_backed_tools`
- `cargo test -p codex-tools
environment_capabilities_gate_exec_and_filesystem_tools_independently`
- remote devbox Bazel build via `codex-applied-devbox`:
`//codex-rs/cli:cli`
Stacked on #16508.
This removes the temporary `codex-core` / `codex-login` re-export shims
from the ownership split and rewrites callsites to import directly from
`codex-model-provider-info`, `codex-models-manager`, `codex-api`,
`codex-protocol`, `codex-feedback`, and `codex-response-debug-context`.
No behavior change intended; this is the mechanical import cleanup layer
split out from the ownership move.
---------
Co-authored-by: Codex <noreply@openai.com>
## Why
`codex-core` was re-exporting APIs owned by sibling `codex-*` crates,
which made downstream crates depend on `codex-core` as a proxy module
instead of the actual owner crate.
Removing those forwards makes crate boundaries explicit and lets leaf
crates drop unnecessary `codex-core` dependencies. In this PR, this
reduces the dependency on `codex-core` to `codex-login` in the following
files:
```
codex-rs/backend-client/Cargo.toml
codex-rs/mcp-server/tests/common/Cargo.toml
```
## What
- Remove `codex-rs/core/src/lib.rs` re-exports for symbols owned by
`codex-login`, `codex-mcp`, `codex-rollout`, `codex-analytics`,
`codex-protocol`, `codex-shell-command`, `codex-sandboxing`,
`codex-tools`, and `codex-utils-path`.
- Delete the `default_client` forwarding shim in `codex-rs/core`.
- Update in-crate and downstream callsites to import directly from the
owning `codex-*` crate.
- Add direct Cargo dependencies where callsites now target the owner
crate, and remove `codex-core` from `codex-rs/backend-client`.
## Summary
- move skill loading and management into codex-core-skills
- leave codex-core with the thin integration layer and shared wiring
## Testing
- CI
---------
Co-authored-by: Codex <noreply@openai.com>
## Summary
- move the analytics events client into codex-analytics
- update codex-core and app-server callsites to use the new crate
## Testing
- CI
---------
Co-authored-by: Codex <noreply@openai.com>
### Summary
Make `FileWatcher` a reusable core component which can be built upon.
Extract skills-related logic into a separate `SkillWatcher`.
Introduce a composable `ThrottledWatchReceiver` to throttle filesystem
events, coalescing affected paths among them.
### Testing
Updated existing unit tests.
The idea is that codex-exec exposes an Environment struct with services
on it. Each of those is a trait.
Depending on construction parameters passed to Environment they are
either backed by local or remote server but core doesn't see these
differences.
## Summary
If a subagent requests approval, and the user persists that approval to
the execpolicy, it should (by default) propagate. We'll need to rethink
this a bit in light of coming Permissions changes, though I think this
is closer to the end state that we'd want, which is that execpolicy
changes to one permissions profile should be synced across threads.
## Testing
- [x] Added integration test
---------
Co-authored-by: Codex <noreply@openai.com>
Adds an environment crate and environment + file system abstraction.
Environment is a combination of attributes and services specific to
environment the agent is connected to:
File system, process management, OS, default shell.
The goal is to move most of agent logic that assumes environment to work
through the environment abstraction.
## Summary
- persist the code mode runner process in the session-scoped code mode
store
- switch the runner protocol from `init` to `start` with explicit
session ids
- handle runner-side session processing without the init waiter queue
## Validation
- just fmt
- cargo check -p codex-core
- node --check codex-rs/core/src/tools/code_mode_runner.cjs
## 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`
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.
Previous to this change, `determine_action()` would
1. check if `program` is associated with a skill
2. if so, check if `program` is in `execve_session_approvals` to see
whether the user needs to be prompted
This PR flips the order of these checks to try to set us up so that
"session approvals" are always consulted first (which should soon extend
to include session approvals derived from `prefix_rule()`s, as well).
Though to make the new ordering work, we need to record any relevant
metadata to associate with the approval, which in the case of a
skill-based approval is the `SkillMetadata` so that we can derive the
`PermissionProfile` to include with the escalation. (Though as noted by
the `TODO`, this `PermissionProfile` is not honored yet.)
The new `ExecveSessionApproval` struct is used to retain the necessary
metadata.
## What Changed
- Replace the `execve_session_approvals` `HashSet` with a map that
stores an `ExecveSessionApproval` alongside each approved `program`.
- When a user chooses `ApprovedForSession` for a skill script, capture
the matched `SkillMetadata` in the session approval entry.
- Consult that cache before re-running `find_skill()`, and reuse the
originally approved skill metadata and permission profile when allowing
later execve callbacks in the same session.
## Why
`unix_escalation.rs` checks a session-scoped approval cache before
prompting again for an execve-intercepted skill script. Without also
recording `ReviewDecision::ApprovedForSession`, that cache never gets
populated, so the same skill script can still trigger repeated approval
prompts within one session.
## What Changed
- Add `execve_session_approvals` to `SessionServices` so the session can
track approved skill script paths.
- Record the script path when a skill-script prompt returns
`ReviewDecision::ApprovedForSession`, but only for the skill-script path
rather than broader prefix-rule approvals.
- Reuse the cached approval on later execve callbacks by treating an
already-approved skill script as `Decision::Allow`.
---
[//]: # (BEGIN SAPLING FOOTER)
Stack created with [Sapling](https://sapling-scm.com). Best reviewed
with [ReviewStack](https://reviewstack.dev/openai/codex/pull/12756).
* #12758
* __->__ #12756
## Why
`codex-rs/core/src/tools/runtimes/shell/unix_escalation.rs` previously
located `codex-execve-wrapper` by scanning `PATH` and sibling
directories. That lookup is brittle and can select the wrong binary when
the runtime environment differs from startup assumptions.
We already pass `codex-linux-sandbox` from `codex-arg0`;
`codex-execve-wrapper` should use the same startup-driven path plumbing.
## What changed
- Introduced `Arg0DispatchPaths` in `codex-arg0` to carry both helper
executable paths:
- `codex_linux_sandbox_exe`
- `main_execve_wrapper_exe`
- Updated `arg0_dispatch_or_else()` to pass `Arg0DispatchPaths` to
top-level binaries and preserve helper paths created in
`prepend_path_entry_for_codex_aliases()`.
- Threaded `Arg0DispatchPaths` through entrypoints in `cli`, `exec`,
`tui`, `app-server`, and `mcp-server`.
- Added `main_execve_wrapper_exe` to core configuration plumbing
(`Config`, `ConfigOverrides`, and `SessionServices`).
- Updated zsh-fork shell escalation to consume the configured
`main_execve_wrapper_exe` and removed path-sniffing fallback logic.
- Updated app-server config reload paths so reloaded configs keep the
same startup-provided helper executable paths.
## References
- [`Arg0DispatchPaths`
definition](https://github.com/openai/codex/blob/e355b43d5c2a771f045296a6deae10d7c9c36ec6/codex-rs/arg0/src/lib.rs#L20-L24)
- [`arg0_dispatch_or_else()` forwarding both
paths](https://github.com/openai/codex/blob/e355b43d5c2a771f045296a6deae10d7c9c36ec6/codex-rs/arg0/src/lib.rs#L145-L176)
- [zsh-fork escalation using configured wrapper
path](https://github.com/openai/codex/blob/e355b43d5c2a771f045296a6deae10d7c9c36ec6/codex-rs/core/src/tools/runtimes/shell/unix_escalation.rs#L109-L150)
## Testing
- `cargo check -p codex-arg0 -p codex-core -p codex-exec -p codex-tui -p
codex-mcp-server -p codex-app-server`
- `cargo test -p codex-arg0`
- `cargo test -p codex-core tools::runtimes::shell::unix_escalation:: --
--nocapture`
## Why
This PR switches the `shell_command` zsh-fork path over to
`codex-shell-escalation` so the new shell tool can use the shared
exec-wrapper/escalation protocol instead of the `zsh_exec_bridge`
implementation that was introduced in
https://github.com/openai/codex/pull/12052. `zsh_exec_bridge` relied on
UNIX domain sockets, which is not as tamper-proof as the FD-based
approach in `codex-shell-escalation`.
## What Changed
- Added a Unix zsh-fork runtime adapter in `core`
(`core/src/tools/runtimes/shell/unix_escalation.rs`) that:
- runs zsh-fork commands through
`codex_shell_escalation::run_escalate_server`
- bridges exec-policy / approval decisions into `ShellActionProvider`
- executes escalated commands via a `ShellCommandExecutor` that calls
`process_exec_tool_call`
- Updated `ShellRuntime` / `ShellCommandHandler` / tool spec wiring to
select a `shell_command` backend (`classic` vs `zsh-fork`) while leaving
the generic `shell` tool path unchanged.
- Removed the `zsh_exec_bridge`-based session service and deleted
`core/src/zsh_exec_bridge/mod.rs`.
- Moved exec-wrapper entrypoint dispatch to `arg0` by handling the
`codex-execve-wrapper` arg0 alias there, and removed the old
`codex_core::maybe_run_zsh_exec_wrapper_mode()` hooks from `cli` and
`app-server` mains.
- Added the needed `codex-shell-escalation` dependencies for `core` and
`arg0`.
## Tests
- `cargo test -p codex-core
shell_zsh_fork_prefers_shell_command_over_unified_exec`
- `cargo test -p codex-app-server turn_start_shell_zsh_fork --
--nocapture`
- verifies zsh-fork command execution and approval flows through the new
backend
- includes subcommand approve/decline coverage using the shared zsh
DotSlash fixture in `app-server/tests/suite/zsh`
- To test manually, I added the following to `~/.codex/config.toml`:
```toml
zsh_path = "/Users/mbolin/code/codex3/codex-rs/app-server/tests/suite/zsh"
[features]
shell_zsh_fork = true
```
Then I ran `just c` to run the dev build of Codex with these changes and
sent it the message:
```
run `echo $0`
```
And it replied with:
```
echo $0 printed:
/Users/mbolin/code/codex3/codex-rs/app-server/tests/suite/zsh
In this tool context, $0 reflects the script path used to invoke the shell, not just zsh.
```
so the tool appears to be wired up correctly.
## Notes
- The zsh subcommand-decline integration test now uses `rm` under a
`WorkspaceWrite` sandbox. The previous `/usr/bin/true` scenario is
auto-allowed by the new `shell-escalation` policy path, which no longer
produces subcommand approval prompts.
zsh fork PR stack:
- https://github.com/openai/codex/pull/12051
- https://github.com/openai/codex/pull/12052👈
### Summary
This PR introduces a feature-gated native shell runtime path that routes
shell execution through a patched zsh exec bridge, removing MCP-specific
behavior from the shell hot path while preserving existing
CommandExecution lifecycle semantics.
When shell_zsh_fork is enabled, shell commands run via patched zsh with
per-`execve` interception through EXEC_WRAPPER. Core receives wrapper
IPC requests over a Unix socket, applies existing approval policy, and
returns allow/deny before the subcommand executes.
### What’s included
**1) New zsh exec bridge runtime in core**
- Wrapper-mode entrypoint (maybe_run_zsh_exec_wrapper_mode) for
EXEC_WRAPPER invocations.
- Per-execution Unix-socket IPC handling for wrapper requests/responses.
- Approval callback integration using existing core approval
orchestration.
- Streaming stdout/stderr deltas to existing command output event
pipeline.
- Error handling for malformed IPC, denial/abort, and execution
failures.
**2) Session lifecycle integration**
SessionServices now owns a `ZshExecBridge`.
Session startup initializes bridge state; shutdown tears it down
cleanly.
**3) Shell runtime routing (feature-gated)**
When `shell_zsh_fork` is enabled:
- Build execution env/spec as usual.
- Add wrapper socket env wiring.
- Execute via `zsh_exec_bridge.execute_shell_request(...)` instead of
the regular shell path.
- Non-zsh-fork behavior remains unchanged.
**4) Config + feature wiring**
- Added `Feature::ShellZshFork` (under development).
- Added config support for `zsh_path` (optional absolute path to patched
zsh):
- `Config`, `ConfigToml`, `ConfigProfile`, overrides, and schema.
- Session startup validates that `zsh_path` exists/usable when zsh-fork
is enabled.
- Added startup test for missing `zsh_path` failure mode.
**5) Seatbelt/sandbox updates for wrapper IPC**
- Extended seatbelt policy generation to optionally allow outbound
connection to explicitly permitted Unix sockets.
- Wired sandboxing path to pass wrapper socket path through to seatbelt
policy generation.
- Added/updated seatbelt tests for explicit socket allow rule and
argument emission.
**6) Runtime entrypoint hooks**
- This allows the same binary to act as the zsh wrapper subprocess when
invoked via `EXEC_WRAPPER`.
**7) Tool selection behavior**
- ToolsConfig now prefers ShellCommand type when shell_zsh_fork is
enabled.
- Added test coverage for precedence with unified-exec enabled.
### 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>
Summary
- move `core/src/hooks` implementation into a new `codex-hooks` crate
with its own manifest
- update `codex-rs` workspace and `codex-core` crate to depend on the
extracted `hooks` crate and wire up the shared APIs
- ensure references, modules, and lockfile reflect the new crate layout
Testing
- Not run (not requested)
As of this PR, `SessionServices` retains a
`Option<StartedNetworkProxy>`, if appropriate.
Now the `network` field on `Config` is `Option<NetworkProxySpec>`
instead of `Option<NetworkProxy>`.
Over in `Session::new()`, we invoke `NetworkProxySpec::start_proxy()` to
create the `StartedNetworkProxy`, which is a new struct that retains the
`NetworkProxy` as well as the `NetworkProxyHandle`. (Note that `Drop` is
implemented for `NetworkProxyHandle` to ensure the proxies are shutdown
when it is dropped.)
The `NetworkProxy` from the `StartedNetworkProxy` is threaded through to
the appropriate places.
---
[//]: # (BEGIN SAPLING FOOTER)
Stack created with [Sapling](https://sapling-scm.com). Best reviewed
with [ReviewStack](https://reviewstack.dev/openai/codex/pull/11207).
* #11285
* __->__ #11207
This introduces a `Hooks` service. It registers hooks from config and
dispatches hook events at runtime.
N.B. The hook config is not wired up to this yet. But for legacy
reasons, we wire up `notify` from config and power it using hooks now.
Nothing about the `notify` interface has changed.
I'd start by reviewing `hooks/types.rs`
Some things to note:
- hook names subject to change
- no hook result yet
- stopping semantics yet to be introduced
- additional hooks yet to be introduced
Make ModelClient a session-scoped object.
Move state that is session level onto the client, and make state that is
per-turn explicit on corresponding methods.
Stop taking a huge Config object, instead only pass in values that are
actually needed.
---------
Co-authored-by: Josh McKinney <joshka@openai.com>
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>
Add a `.sqlite` database to be used to store rollout metatdata (and
later logs)
This PR is phase 1:
* Add the database and the required infrastructure
* Add a backfill of the database
* Persist the newly created rollout both in files and in the DB
* When we need to get metadata or a rollout, consider the `JSONL` as the
source of truth but compare the results with the DB and show any errors
### Summary
* Added `mcpServer/refresh` command to inform app servers and active
threads to refresh mcpServer on next turn event.
* Added `pending_mcp_server_refresh_config` to codex core so that if the
value is populated, we reinitialize the mcp server manager on the thread
level.
* The config is updated on `mcpServer/refresh` command which we iterate
through threads and provide with the latest config value after last
write.
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
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
# 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.
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.
1. Skills load once in core at session start; the cached outcome is
reused across core and surfaced to TUI via SessionConfigured.
2. TUI detects explicit skill selections, and core injects the matching
SKILL.md content into the turn when a selected skill is present.
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.
The goal of this change:
1. Unify user input and user turn implementation.
2. Have a single place where turn/session setting overrides are applied.
3. Have a single place where turn context is created.
4. Create TurnContext only for actual turn and have a separate structure
for current session settings (reuse ConfigureSession)
