Summary
- propagate approval policy from parent to spawned agents and drop the
Never override so sub-agents respect the caller’s request
- refresh the pending-approval list whenever events arrive or the active
thread changes and surface the list above the composer for inactive
threads
- add widgets, helpers, and tests covering the new pending-thread
approval UI state
![Uploading Screenshot 2026-02-25 at 11.02.18.png…]()
This PR replaces the old `additional_permissions.fs_read/fs_write` shape
with a shared `PermissionProfile`
model and wires it through the command approval, sandboxing, protocol,
and TUI layers. The schema is adopted from the
`SkillManifestPermissions`, which is also refactored to use this unified
struct. This helps us easily expose permission profiles in app
server/core as a follow-up.
## Summary
- Fix `js_repl` so `await codex.tool("view_image", { path })` actually
attaches the image to the active turn when called from inside the JS
REPL.
- Restore the behavior expected by the existing `js_repl`
image-attachment test.
- This is a follow-up to
[#12553](https://github.com/openai/codex/pull/12553), which changed
`view_image` to return structured image content.
## Root Cause
- [#12553](https://github.com/openai/codex/pull/12553) changed
`view_image` from directly injecting a pending user image message to
returning structured `function_call_output` content items.
- The nested tool-call bridge inside `js_repl` serialized that tool
response back to the JS runtime, but it did not mirror returned image
content into the active turn.
- As a result, `view_image` appeared to succeed inside `js_repl`, but no
`input_image` was actually attached for the outer turn.
## What Changed
- Updated the nested tool-call path in `js_repl` to inspect function
tool responses for structured content items.
- When a nested tool response includes `input_image` content, `js_repl`
now injects a corresponding user `Message` into the active turn before
returning the raw tool result back to the JS runtime.
- Kept the normal JSON result flow intact, so `codex.tool(...)` still
returns the original tool output object to JavaScript.
## Why
- `js_repl` documentation and tests already assume that `view_image` can
be used from inside the REPL to attach generated images to the model.
- Without this fix, the nested call path silently dropped that
attachment behavior.
Summary
- detect skill-invoking shell commands based on the original command
string, request approvals when needed, and cache positive decisions per
session
- keep implicit skill invocation emitted after approval and keep skill
approval decline messaging centralized to the shell handler
- expand and adjust skill approval tests to cover shell-based skill
scripts while matching the new detection expectations
Testing
- Not run (not requested)
## 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.
## 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
- use `skills_for_cwd` lookup to scope allowed skills and build
invocation context for downstream processing
- add detection in `stream_events_utils` to classify tool calls as
implicit skill invocations per the proposal (script runners, extensions,
`scripts` dirs, and SKILL.md reads)
- deduplicate invocations per turn and emit analytics/OTEL events on the
same background queue as explicit invokes
## Why
Tool handlers and runtimes needed to pass the same turn/session context
for shell and non-shell workflows without duplicative ownership churn.
Using shared pointers avoids temporary lifetimes and keeps existing
behavior unchanged while simplifying call sites.
## What changed
- Converted `ToolCtx` to store shared context handles (`Arc`-based),
including updates across shell, apply-patch, and unified-exec paths.
- Updated orchestrator/runtime call sites to consume the shared context
consistently and remove brittle move/borrow patterns.
- Kept behavior unchanged while preparing the type surface for the new
shell escalation integration in the next stack commit.
## Verification
- Validated this commit stack point with `just clippy` and confirmed
workspace compiles cleanly in this stack state.
[//]: # (BEGIN SAPLING FOOTER)
Stack created with [Sapling](https://sapling-scm.com). Best reviewed
with [ReviewStack](https://reviewstack.dev/openai/codex/pull/12583).
* #12584
* __->__ #12583
* #12556
## Summary
Simplify network approvals by removing per-attempt proxy correlation and
moving to session-level approval dedupe keyed by (host, protocol, port).
Instead of encoding attempt IDs into proxy credentials/URLs, we now
treat approvals as a destination policy decision.
- Concurrent calls to the same destination share one approval prompt.
- Different destinations (or same host on different ports) get separate
prompts.
- Allow once approves the current queued request group only.
- Allow for session caches that (host, protocol, port) and auto-allows
future matching requests.
- Never policy continues to deny without prompting.
Example:
- 3 calls:
- a.com (line 443)
- b.com (line 443)
- a.com (line 443)
=> 2 prompts total (a, b), second a waits on the first decision.
- a.com:80 is treated separately from a.com line 443
## Testing
- `just fmt` (in `codex-rs`)
- `cargo test -p codex-core tools::network_approval::tests`
- `cargo test -p codex-core` (unit tests pass; existing
integration-suite failures remain in this environment)
Summary
- expose `agents.max_depth` in config schema and toml parsing, with
defaults and validation
- thread-spawn depth guards and multi-agent handler now respect the
configured limit instead of a hardcoded value
- ensure documentation and helpers account for agent depth limits
## Summary
This feature is now reasonably stable, let's remove it so we can
simplify our upcoming iterations here.
## Testing
- [x] Existing tests pass
Summary
- rename the `collab` handlers and UI files to `multi_agents` to match
the new naming
- update module references and specs so the handlers and TUI widgets
consistently use the renamed files
- keep the existing functionality while aligning file and module names
with the multi-agent terminology
The idea is to have 2 family of agents.
1. Built-in that we packaged directly with Codex
2. User defined that are defined using the `agents_config.toml` file. It
can reference config files that will override the agent config. This
looks like this:
```
version = 1
[agents.explorer]
description = """Use `explorer` for all codebase questions.
Explorers are fast and authoritative.
Always prefer them over manual search or file reading.
Rules:
- Ask explorers first and precisely.
- Do not re-read or re-search code they cover.
- Trust explorer results without verification.
- Run explorers in parallel when useful.
- Reuse existing explorers for related questions."""
config_file = "explorer.toml"
```
### What changed
1. Removed per-turn MCP selection reset in `core/src/tasks/mod.rs`.
2. Added `SessionState::set_mcp_tool_selection(Vec<String>)` in
`core/src/state/session.rs` for authoritative restore behavior (deduped,
order-preserving, empty clears).
3. Added rollout parsing in `core/src/codex.rs` to recover
`active_selected_tools` from prior `search_tool_bm25` outputs:
- tracks matching `call_id`s
- parses function output text JSON
- extracts `active_selected_tools`
- latest valid payload wins
- malformed/non-matching payloads are ignored
4. Applied restore logic to resumed and forked startup paths in
`core/src/codex.rs`.
5. Updated instruction text to session/thread scope in
`core/templates/search_tool/tool_description.md`.
6. Expanded tests in `core/tests/suite/search_tool.rs`, plus unit
coverage in:
- `core/src/codex.rs`
- `core/src/state/session.rs`
### Behavior after change
1. Search activates matched tools.
2. Additional searches union into active selection.
3. Selection survives new turns in the same thread.
4. Resume/fork restores selection from rollout history.
5. Separate threads do not inherit selection unless forked.
### 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
- Limit `search_tool_bm25` indexing to `codex_apps` tools only, so
non-Apps MCP servers are no longer discoverable through this search
path.
- Move search-tool discovery guidance into the `search_tool_bm25` tool
description (via template include) instead of injecting it as a separate
developer message.
- Update Apps discovery guidance wording to clarify when to use
`search_tool_bm25` for Apps-backed systems (for example Slack, Google
Drive, Jira, Notion) and when to call tools directly.
- Remove dead `core` helper code (`filter_codex_apps_mcp_tools` and
`codex_apps_connector_id`) that is no longer used after the
tool-selection refactor.
- Update `core` search-tool tests to assert codex-apps-only behavior and
to validate guidance from the tool description.
## Validation
- ✅ `just fmt`
- ✅ `cargo test -p codex-core search_tool`
- ⚠️ `cargo test -p codex-core` was attempted, but the run repeatedly
stalled on
`tools::js_repl::tests::js_repl_can_attach_image_via_view_image_tool`.
## Tickets
- None
## Why
We currently carry multiple permission-related concepts directly on
`Config` for shell/unified-exec behavior (`approval_policy`,
`sandbox_policy`, `network`, `shell_environment_policy`,
`windows_sandbox_mode`).
Consolidating these into one in-memory struct makes permission handling
easier to reason about and sets up the next step: supporting named
permission profiles (`[permissions.PROFILE_NAME]`) without changing
behavior now.
This change is mostly mechanical: it updates existing callsites to go
through `config.permissions`, but it does not yet refactor those
callsites to take a single `Permissions` value in places where multiple
permission fields are still threaded separately.
This PR intentionally **does not** change the on-disk `config.toml`
format yet and keeps compatibility with legacy config keys.
## What Changed
- Introduced `Permissions` in `core/src/config/mod.rs`.
- Added `Config::permissions` and moved effective runtime permission
fields under it:
- `approval_policy`
- `sandbox_policy`
- `network`
- `shell_environment_policy`
- `windows_sandbox_mode`
- Updated config loading/building so these effective values are still
derived from the same existing config inputs and constraints.
- Updated Windows sandbox helpers/resolution to read/write via
`permissions`.
- Threaded the new field through all permission consumers across core
runtime, app-server, CLI/exec, TUI, and sandbox summary code.
- Updated affected tests to reference `config.permissions.*`.
- Renamed the struct/field from
`EffectivePermissions`/`effective_permissions` to
`Permissions`/`permissions` and aligned variable naming accordingly.
## Verification
- `just fix -p codex-core -p codex-tui -p codex-cli -p codex-app-server
-p codex-exec -p codex-utils-sandbox-summary`
- `cargo build -p codex-core -p codex-tui -p codex-cli -p
codex-app-server -p codex-exec -p codex-utils-sandbox-summary`
## Summary
This PR adds host-integrated helper APIs for `js_repl` and updates model
guidance so the agent can use them reliably.
### What’s included
- Add `codex.tool(name, args?)` in the JS kernel so `js_repl` can call
normal Codex tools.
- Keep persistent JS state and scratch-path helpers available:
- `codex.state`
- `codex.tmpDir`
- Wire `js_repl` tool calls through the standard tool router path.
- Add/align `js_repl` execution completion/end event behavior with
existing tool logging patterns.
- Update dynamic prompt injection (`project_doc`) to document:
- how to call `codex.tool(...)`
- raw output behavior
- image flow via `view_image` (`codex.tmpDir` +
`codex.tool("view_image", ...)`)
- stdio safety guidance (`console.log` / `codex.tool`, avoid direct
`process.std*`)
## Why
- Standardize JS-side tool usage on `codex.tool(...)`
- Make `js_repl` behavior more consistent with existing tool execution
and event/logging patterns.
- Give the model enough runtime guidance to use `js_repl` safely and
effectively.
## Testing
- Added/updated unit and runtime tests for:
- `codex.tool` calls from `js_repl` (including shell/MCP paths)
- image handoff flow via `view_image`
- prompt-injection text for `js_repl` guidance
- execution/end event behavior and related regression coverage
#### [git stack](https://github.com/magus/git-stack-cli)
- ✅ `1` https://github.com/openai/codex/pull/10674
- 👉 `2` https://github.com/openai/codex/pull/10672
- ⏳ `3` https://github.com/openai/codex/pull/10671
- ⏳ `4` https://github.com/openai/codex/pull/10673
- ⏳ `5` https://github.com/openai/codex/pull/10670
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.
## Why
`codex-core` was being built in multiple feature-resolved permutations
because test-only behavior was modeled as crate features. For a large
crate, those permutations increase compile cost and reduce cache reuse.
## Net Change
- Removed the `test-support` crate feature and related feature wiring so
`codex-core` no longer needs separate feature shapes for test consumers.
- Standardized cross-crate test-only access behind
`codex_core::test_support`.
- External test code now imports helpers from
`codex_core::test_support`.
- Underlying implementation hooks are kept internal (`pub(crate)`)
instead of broadly public.
## Outcome
- Fewer `codex-core` build permutations.
- Better incremental cache reuse across test targets.
- No intended production behavior change.
- Keep `view_image` in the advertised tool list for all models.
- Return a clear error when the current model does not support image
inputs, and cover it with a unit test.
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
**Why We Did This**
- The goal is to reduce MCP tool context pollution by not exposing the
full MCP tool list up front
- It forces an explicit discovery step (`search_tool_bm25`) so the model
narrows tool scope before making MCP calls, which helps relevance and
lowers prompt/tool clutter.
**What It Changed**
- Added a new experimental feature flag `search_tool` in
`core/src/features.rs:90` and `core/src/features.rs:430`.
- Added config/schema support for that flag in
`core/config.schema.json:214` and `core/config.schema.json:1235`.
- Added BM25 dependency (`bm25`) in `Cargo.toml:129` and
`core/Cargo.toml:23`.
- Added new tool handler `search_tool_bm25` in
`core/src/tools/handlers/search_tool_bm25.rs:18`.
- Registered the handler and tool spec in
`core/src/tools/handlers/mod.rs:11` and `core/src/tools/spec.rs:780` and
`core/src/tools/spec.rs:1344`.
- Extended `ToolsConfig` to carry `search_tool` enablement in
`core/src/tools/spec.rs:32` and `core/src/tools/spec.rs:56`.
- Injected dedicated developer instructions for tool-discovery workflow
in `core/src/codex.rs:483` and `core/src/codex.rs:1976`, using
`core/templates/search_tool/developer_instructions.md:1`.
- Added session state to store one-shot selected MCP tools in
`core/src/state/session.rs:27` and `core/src/state/session.rs:131`.
- Added filtering so when feature is enabled, only selected MCP tools
are exposed on the next request (then consumed) in
`core/src/codex.rs:3800` and `core/src/codex.rs:3843`.
- Added E2E suite coverage for
enablement/instructions/hide-until-search/one-turn-selection in
`core/tests/suite/search_tool.rs:72`,
`core/tests/suite/search_tool.rs:109`,
`core/tests/suite/search_tool.rs:147`, and
`core/tests/suite/search_tool.rs:218`.
- Refactored test helper utilities to support config-driven tool
collection in `core/tests/suite/tools.rs:281`.
**Net Behavioral Effect**
- With `search_tool` **off**: existing MCP behavior (tools exposed
normally).
- With `search_tool` **on**: MCP tools start hidden, model must call
`search_tool_bm25`, and only returned `selected_tools` are available for
the next model call.
jif-oai