## 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>
## Summary
- align the guardian permission test with the actual sandbox policy it
widens and use a slightly larger Windows-only timeout budget
- expose the additional-permissions normalization helper to the guardian
test module
- replace the guardian popup snapshot assertion with targeted string
assertions
## Why this fixes the flake
This group was carrying two separate sources of drift. The guardian core
test widened derived sandbox policies without updating the source
sandbox policy, and it used a Windows command/timeout combination that
was too tight on slower runners. Separately, the TUI test was
snapshotting the full popup even though unrelated feature text changes
were the only thing moving. The new assertions keep coverage on the
guardian entry itself while removing unrelated snapshot churn.
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.
## Why
`PermissionProfile` should describe filesystem roots as absolute paths
at the type level. Using `PathBuf` in `FileSystemPermissions` made the
shared type too permissive and blurred together three different
deserialization cases:
- skill metadata in `agents/openai.yaml`, where relative paths should
resolve against the skill directory
- app-server API payloads, where callers should have to send absolute
paths
- local tool-call payloads for commands like `shell_command` and
`exec_command`, where `additional_permissions.file_system` may
legitimately be relative to the command `workdir`
This change tightens the shared model without regressing the existing
local command flow.
## What Changed
- changed `protocol::models::FileSystemPermissions` and the app-server
`AdditionalFileSystemPermissions` mirror to use `AbsolutePathBuf`
- wrapped skill metadata deserialization in `AbsolutePathBufGuard`, so
relative permission roots in `agents/openai.yaml` resolve against the
containing skill directory
- kept app-server/API deserialization strict, so relative
`additionalPermissions.fileSystem.*` paths are rejected at the boundary
- restored cwd/workdir-relative deserialization for local tool-call
payloads by parsing `shell`, `shell_command`, and `exec_command`
arguments under an `AbsolutePathBufGuard` rooted at the resolved command
working directory
- simplified runtime additional-permission normalization so it only
canonicalizes and deduplicates absolute roots instead of trying to
recover relative ones later
- updated the app-server schema fixtures, `app-server/README.md`, and
the affected transport/TUI tests to match the final behavior
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
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
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
### 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.
**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.
## Summary
This PR updates `request_user_input` behavior and Default-mode guidance
to match current collaboration-mode semantics and reduce model
confusion.
## Why
- `request_user_input` should be explicitly documented as **Plan-only**.
- Tool description and runtime availability checks should be driven by
the **same centralized mode policy**.
- Default mode prompt needed stronger execution guidance and explicit
instruction that `request_user_input` is unavailable.
- Error messages should report the **actual mode name** (not aliases
that can read as misleading).
## What changed
- Centralized `request_user_input` mode policy in `core` handler logic:
- Added a single allowed-modes config (`Plan` only).
- Reused that policy for:
- runtime rejection messaging
- tool description text
- Updated tool description to include availability constraint:
- `"This tool is only available in Plan mode."`
- Updated runtime rejection behavior:
- `Default` -> `"request_user_input is unavailable in Default mode"`
- `Execute` -> `"request_user_input is unavailable in Execute mode"`
- `PairProgramming` -> `"request_user_input is unavailable in Pair
Programming mode"`
- Strengthened Default collaboration prompt:
- Added explicit execution-first behavior
- Added assumptions-first guidance
- Added explicit `request_user_input` unavailability instruction
- Added concise progress-reporting expectations
- Simplified formatting implementation:
- Inlined allowed-mode name collection into `format_allowed_modes()`
- Kept `format_allowed_modes()` output for 3+ modes as CSV style
(`modes: a,b,c`)
## 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
This adds support for a new variant of the shell tool behind a flag. To
test, run `codex` with `--enable shell_command_tool`, which will
register the tool with Codex under the name `shell_command` that accepts
the following shape:
```python
{
command: str
workdir: str | None,
timeout_ms: int | None,
with_escalated_permissions: bool | None,
justification: str | None,
}
```
This is comparable to the existing tool registered under
`shell`/`container.exec`. The primary difference is that it accepts
`command` as a `str` instead of a `str[]`. The `shell_command` tool
executes by running `execvp(["bash", "-lc", command])`, though the exact
arguments to `execvp(3)` depend on the user's default shell.
The hypothesis is that this will simplify things for the model. For
example, on Windows, instead of generating:
```json
{"command": ["pwsh.exe", "-NoLogo", "-Command", "ls -Name"]}
```
The model could simply generate:
```json
{"command": "ls -Name"}
```
As part of this change, I extracted some logic out of `user_shell.rs` as
`Shell::derive_exec_args()` so that it can be reused in
`codex-rs/core/src/tools/handlers/shell.rs`. Note the original code
generated exec arg lists like:
```javascript
["bash", "-lc", command]
["zsh", "-lc", command]
["pwsh.exe", "-NoProfile", "-Command", command]
```
Using `-l` for Bash and Zsh, but then specifying `-NoProfile` for
PowerShell seemed inconsistent to me, so I changed this in the new
implementation while also adding a `use_login_shell: bool` option to
make this explicit. If we decide to add a `login: bool` to
`ShellCommandToolCallParams` like we have for unified exec:
https://github.com/openai/codex/blob/807e2c27f0a9f2e85c50e7e6df5533f0d9b853c7/codex-rs/core/src/tools/handlers/unified_exec.rs#L33-L34
Then this should make it straightforward to support.
# Tool System Refactor
- Centralizes tool definitions and execution in `core/src/tools/*`:
specs (`spec.rs`), handlers (`handlers/*`), router (`router.rs`),
registry/dispatch (`registry.rs`), and shared context (`context.rs`).
One registry now builds the model-visible tool list and binds handlers.
- Router converts model responses to tool calls; Registry dispatches
with consistent telemetry via `codex-rs/otel` and unified error
handling. Function, Local Shell, MCP, and experimental `unified_exec`
all flow through this path; legacy shell aliases still work.
- Rationale: reduce per‑tool boilerplate, keep spec/handler in sync, and
make adding tools predictable and testable.
Example: `read_file`
- Spec: `core/src/tools/spec.rs` (see `create_read_file_tool`,
registered by `build_specs`).
- Handler: `core/src/tools/handlers/read_file.rs` (absolute `file_path`,
1‑indexed `offset`, `limit`, `L#: ` prefixes, safe truncation).
- E2E test: `core/tests/suite/read_file.rs` validates the tool returns
the requested lines.
## Next steps:
- Decompose `handle_container_exec_with_params`
- Add parallel tool calls
