## Disclaimer
Do not use for now
## Why
Extensions can already contribute prompt fragments and request same-turn
item injection, but there was no host-owned hook for contributing
structured `ResponseItem`s while Codex is assembling a new turn's
initial model input. This change adds that seam so extensions can attach
turn-local input that depends on the submitted user input and resolved
turn environments without routing through prompt text or late injection.
## What changed
- add `TurnInputContributor` to `codex_extension_api` and export the new
`TurnInputContext` / `TurnInputEnvironment` types it receives
- teach `ExtensionRegistry` to register and expose turn-input
contributors alongside the existing extension hooks
- call registered turn-input contributors from
`core/src/session/turn.rs` while building the initial injected input for
a turn, then append their returned `ResponseItem`s after the skill and
plugin injections
Summary
- Add TurnErrorInput and TurnLifecycleContributor::on_turn_error to the
extension API.
- Emit the turn-error lifecycle from core turn error paths, including
usage limit failures.
- Add direct lifecycle coverage for the emitted error facts and stores.
Tests
- just fmt
- git diff --check
- Not run: full tests or clippy (per instructions)
Summary: add session source and persistent-state availability to
ThreadStartInput; populate them from session init; update existing goal
test harness constructors. Tests: just fmt; git diff --check. No full
tests or clippy run per request.
## Why
Extensions can currently observe thread start, resume, and stop, but
they do not have a lifecycle point for the host to say that immediately
pending thread work has drained. That makes idle follow-up behavior
harder to express as extension-owned logic instead of host-specific
plumbing.
This adds an explicit idle lifecycle hook so an extension can react when
a thread becomes idle while the host keeps ownership of whether any
submitted follow-up input starts a turn, is queued, or is ignored.
## What changed
- Added `ThreadIdleInput` with access to the session-scoped and
thread-scoped extension stores.
- Added a default `on_thread_idle` method to
`ThreadLifecycleContributor`.
- Re-exported `ThreadIdleInput` from the extension API surface.
## Testing
Not run; this only extends the extension API trait surface with a
default hook and exported input type.
## Why
The goal extension needs more context when a turn starts than
`turn_store` alone provides.
In particular, goal accounting needs the stable turn id, the effective
collaboration mode, and the cumulative token-usage baseline captured at
turn start so it can:
- suppress goal accounting for plan-mode turns
- compute exact per-turn deltas from cumulative `total_token_usage`
snapshots instead of relying on the most recent usage event alone
- keep the extension-owned accounting path aligned with the host turn
lifecycle
## What
- extend `codex_extension_api::TurnStartInput` to expose `turn_id`,
`collaboration_mode`, and `token_usage_at_turn_start`
- pass the full `TurnContext` plus the captured token-usage baseline
through the turn-start lifecycle emission path
- initialize goal turn accounting from the turn-start baseline and
collaboration mode
- switch goal token accounting to compute deltas from cumulative
`total_token_usage` snapshots
- add coverage for the new turn-start lifecycle fields and for
goal-accounting baseline behavior
## Testing
- added `turn_start_lifecycle_exposes_turn_metadata_and_token_baseline`
in `codex-rs/core/src/session/tests.rs`
- added `ext/goal/tests/accounting.rs` coverage for baseline-aware goal
accounting and plan-mode suppression
## Why
Extensions that need to track runtime progress currently have no typed
host signal for tool execution. The goal extension in particular needs
to observe tool attempts without inspecting tool payloads, owning tool
implementations, or staying coupled to core-only runtime plumbing.
This adds a narrow lifecycle contributor API for host-owned tool
execution: extensions can observe when an accepted tool call starts and
how it finishes, while policy hooks and tool handlers continue to own
payload rewriting, blocking, and execution.
Relevant code:
-
[`ToolLifecycleContributor`](https://github.com/openai/codex/blob/3ad2850ffc7d8a1da19c65a92425637a59098f1b/codex-rs/ext/extension-api/src/contributors.rs#L119)
defines the extension-facing observer contract.
-
[`tool_lifecycle.rs`](https://github.com/openai/codex/blob/3ad2850ffc7d8a1da19c65a92425637a59098f1b/codex-rs/ext/extension-api/src/contributors/tool_lifecycle.rs)
defines the typed start/finish inputs, source, and outcome enums.
- [`notify_tool_start` /
`notify_tool_finish`](https://github.com/openai/codex/blob/3ad2850ffc7d8a1da19c65a92425637a59098f1b/codex-rs/core/src/tools/lifecycle.rs)
bridges core tool dispatch into the extension registry.
## What Changed
- Added `ToolLifecycleContributor` to `codex-extension-api`, including:
- `ToolStartInput`
- `ToolFinishInput`
- `ToolCallSource`
- `ToolCallOutcome`
- Added registration and lookup support on `ExtensionRegistryBuilder` /
`ExtensionRegistry`.
- Wired core tool dispatch to notify lifecycle contributors for:
- accepted tool starts
- completed tool calls, including the tool output success marker
- pre-tool-use blocks
- failures before or after the handler runs
- cancellation/abort in the parallel tool path
- Registered the goal extension as a lifecycle contributor and added the
outcome filter it will use for goal progress accounting.
## Test Coverage
- Added `dispatch_notifies_tool_lifecycle_contributors` to cover
lifecycle notification ordering and outcomes for successful and
handler-failed tool calls.
## Why
The tool runtime path still had a typed output associated type on
`ToolExecutor`, plus a core-only `RegisteredTool` adapter and
extension-only executor aliases. That made every new shared tool runtime
carry extra adapter plumbing before it could participate in core
dispatch, extension tools, hook payloads, telemetry, and model-visible
spec generation.
This PR moves output erasure to the shared executor boundary so core and
extension tools can use the same execution contract directly.
## What Changed
- Changed `codex_tools::ToolExecutor` to return `Box<dyn ToolOutput>`
instead of an associated `Output` type.
- Removed the extension-specific `ExtensionToolExecutor` /
`ExtensionToolOutput` aliases and exposed `ToolExecutor<ToolCall>` plus
`ToolOutput` through `codex-extension-api`.
- Reworked core tool registration around `CoreToolRuntime` and
`ToolRegistry::from_tools`, removing the extra `RegisteredTool` /
`ToolRegistryBuilder` layer.
- Consolidated model-visible spec planning and registry construction in
`core/src/tools/spec_plan.rs`, including deferred tool search and
code-mode-only filtering.
- Added `ToolOutput` helpers for post-tool-use hook ids and inputs so
MCP, unified exec, extension, and other boxed outputs preserve the same
hook payload behavior.
- Updated core handlers, memories tools, and the related
registry/spec/router tests to use the simplified contract.
## Test Coverage
- Updated coverage for tool spec planning, registry lookup, deferred
tool search registration, extension tool routing, post-tool-use hook
payloads, dispatch tracing, guardian output extraction, and memories
extension tool execution.
## Why
`codex_tools::ToolExecutor` keeps a tool spec attached to its runtime
handler, but extension tools still carried a parallel
`ExtensionToolFuture` / `ExtensionToolExecutor` shape. That made
extension-owned tools look different from host tools even though
routing, registration, and execution need the same abstraction.
This PR makes the shared executor contract directly async and lets
extension tools implement it too, so host tools and extension tools can
move through the same registration path.
## What changed
- Changed `ToolExecutor::handle` to an `async fn` using `async-trait`,
and updated built-in tool handlers to implement the async trait
directly.
- Replaced the bespoke `ExtensionToolFuture` contract with a marker
`ExtensionToolExecutor` over `ToolExecutor<ToolCall, Output =
JsonToolOutput>`, re-exporting `ToolExecutor` from
`codex-extension-api`.
- Updated the memories extension tools to implement the shared executor
trait.
- Split tool-router construction into collected executors plus hosted
model specs, keeping hosted tools like web search and image generation
separate from executable handlers.
- Updated spec/router tests and extension-tool stubs for the new
executor shape.
## Verification
- Not run locally.
## Summary
- add a scoped level_id to ExtensionData and expose it through
level_id()
- remove thread_id/turn_id parameters from extension contributor inputs
where the scoped ExtensionData already carries that identity
- move turn-scoped extension data onto TurnContext so token usage and
lifecycle contributors can share the same turn store
## Testing
- cargo check -p codex-extension-api -p codex-core --tests
- cargo test -p codex-extension-api
- cargo test -p codex-guardian
- cargo test -p codex-core --lib
record_token_usage_info_notifies_extension_contributors
- cargo test -p codex-core --lib
submission_loop_channel_close_emits_thread_stop_lifecycle
- cargo test -p codex-core --lib
submission_loop_channel_close_aborts_active_turn_before_thread_stop_lifecycle
- just fix -p codex-extension-api
- just fix -p codex-guardian
- just fix -p codex-core
- just fmt
## Note
- Attempted cargo test -p codex-core; it aborted in
agent::control::tests::spawn_agent_fork_last_n_turns_keeps_only_recent_turns
with the existing stack overflow before the full suite completed.
## Why
Extensions can already contribute prompt, tool, turn-item, and
thread-lifecycle behavior, but there was no explicit host-owned hook for
per-turn setup and cleanup. That makes extension-private turn state
awkward: an extension either has to stash it outside the turn lifecycle
or depend on core runtime objects.
This adds a small turn lifecycle boundary. Extensions receive stable
identifiers plus the existing session, thread, and turn `ExtensionData`
stores, while core keeps owning task scheduling, cancellation, and turn
teardown.
## What Changed
- Added `TurnLifecycleContributor` with `on_turn_start`, `on_turn_stop`,
and `on_turn_abort` callbacks in `codex-rs/ext/extension-api`.
- Added typed `TurnStartInput`, `TurnStopInput`, and `TurnAbortInput`
payloads that expose `thread_id`, `turn_id`, `session_store`,
`thread_store`, and `turn_store`.
- Registered and re-exported turn lifecycle contributors through
`ExtensionRegistry` and `ExtensionRegistryBuilder`.
- Wired `Session` to emit turn start, stop, and abort callbacks from the
existing turn/task lifecycle paths.
- Carried the turn-scoped `ExtensionData` through `RunningTask` and
`RemovedTask` so stop/abort callbacks receive the same turn store
created at turn start.
## Verification
- Not run locally.
## Why
Extensions that need thread-scoped state currently only get a start-time
callback. That is enough for seeding stores, but it leaves the host
without a shared extension seam for later thread rehydrate and flush
work as thread ownership evolves. This PR turns that start-only seam
into a host-owned thread lifecycle contributor contract so
extension-private state can stay behind the extension API instead of
leaking extra orchestration through core.
## What changed
- Replaced `ThreadStartContributor` with `ThreadLifecycleContributor`
and added typed lifecycle inputs for thread start, resume, and stop. The
contract lives in
[`contributors/thread_lifecycle.rs`](https://github.com/openai/codex/blob/d0e9211f70e58d6b07ef07e84f359d1b9aa25955/codex-rs/ext/extension-api/src/contributors/thread_lifecycle.rs#L1-L64).
- Kept the existing start-time behavior intact by routing session
construction through `on_thread_start`.
- Invoked `on_thread_stop` during session shutdown before thread-scoped
extension state is dropped, while isolating contributor failures behind
warning logs.
- Migrated `git-attribution` and `guardian` onto the lifecycle
registration path.
- Renamed the extension registry plumbing from start-specific
contributors to lifecycle-specific contributors.
## Notes
`on_thread_resume` is introduced at the API boundary here so extensions
can target the final lifecycle shape; host resume dispatch can be wired
where that runtime path is finalized.
## Why
Extension tools were split across two public runtime contracts:
`codex-tool-api` exposed `ToolBundle` plus its own call/spec/error
types, while core native tools used `codex_tools::ToolExecutor`. That
made contributed tool specs and execution behavior easy to drift apart
and added another crate boundary for what should be one executable-tool
seam.
This PR makes `ToolExecutor` the single runtime contract and keeps
extension-specific pinning in `codex-extension-api`.
## Remaining todo
https://github.com/openai/codex/pull/22369/changes#diff-b935ea8245c3ce568a30cff660175fa6390b66b872ae409e1e2e965738250741R5
Either generic `Invocation` or sub-extract the `ToolCall` and clean
`ToolInvocation`
## What changed
- Removed the `codex-tool-api` workspace crate and its dependencies from
core and `codex-extension-api`.
- Made `codex_tools::ToolExecutor` object-safe with `async_trait` so
extension contributors can return a dyn executor.
- Added the extension-facing aliases under
`ext/extension-api/src/contributors/tools.rs`, including
`ExtensionToolExecutor = dyn ToolExecutor<ToolCall, Output =
ExtensionToolOutput>`.
- Changed `ToolContributor::tools` to return extension executors
directly instead of `ToolBundle`s.
- Updated core’s extension tool handler/registry/router path to adapt
those extension executors into the existing native `ToolInvocation`
runtime path.
- Added focused coverage for extension tools being registered,
model-visible, dispatchable, and not replacing built-in tools.
## Verification
- `cargo test -p codex-tools`
- `cargo test -p codex-extension-api`
## Why
This is the next narrow step toward moving concrete tool families out of
core. After #22138 introduced `codex-tool-api`, we still needed a real
end-to-end seam that lets an extension own an executable tool definition
once and have core install it without the temporary `extension-api`
wrapper or a dependency on `codex-tools`.
`codex-tool-api` is the small extension-facing execution contract, while
`codex-tools` still has a different job: host-side shared tool metadata
and planning logic that is not “run this contributed tool”, like spec
shaping, namespaces, discovery, code-mode augmentation, and
MCP/dynamic-to-Responses API conversion
## What changed
- Moved the shared leaf tool-spec and JSON Schema types into
`codex-tool-api`, so the executable contract now lives with
[`ToolBundle`](https://github.com/openai/codex/blob/c538758095337d4fe0a52a172363ccede4066bda/codex-rs/tool-api/src/bundle.rs#L19-L70).
- Replaced the temporary extension-side tool wrapper with direct
`ToolBundle` use in `codex-extension-api`.
- Taught core to collect contributed bundles, include them in spec
planning, register them through
[`ToolRegistryBuilder::register_tool_bundle`](https://github.com/openai/codex/blob/c538758095337d4fe0a52a172363ccede4066bda/codex-rs/core/src/tools/registry.rs#L653-L667),
and dispatch them through the existing router/runtime path.
- Added focused coverage for contributed tools becoming model-visible
and dispatchable, plus spec-planning coverage for contributed function
and freeform tools.
## Verification
- Added `extension_tool_bundles_are_model_visible_and_dispatchable` in
`core/src/tools/router_tests.rs`.
- Added spec-plan coverage in `core/src/tools/spec_plan_tests.rs` for
contributed extension bundles.
## Related
- Follow-up to #22138
## Why
`codex-core` still owns a growing amount of product-specific behavior.
This PR starts the extraction path by introducing a small, typed
first-party extension seam: features can install the contribution
families they actually own, while the host keeps lifecycle and state
ownership instead of pushing a broad service locator into the API.
See the `examples/` for illustration
## Known limitations
* Tool contract definition will be shared with core
* Fragments must be extracted
* Missing some contributors
jif ·