## 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
Codex still models model-visible tools and executable behavior largely
inside `codex-core`, which makes it harder to evolve the tool system
toward a single reusable abstraction for built-ins, MCP-backed tools,
dynamic tools, and later tools injected from outside core.
This PR takes the next incremental step in that direction by moving the
common execution-facing pieces out of core and separating them from
core-only orchestration. The intent is to let shared tool abstractions
improve in one place, while `codex-core` keeps the parts that are still
inherently host-specific today, such as `ToolInvocation`, dispatch
wiring, and hook integration.
This PR is mostly moving things around. The only interesting piece is
this abstraction:
https://github.com/openai/codex/pull/22359/changes#diff-81af519002548ba51ed102bdaaf77e081d40a1e73a6e5f9b104bbbc96a6f1b3dR13
## What changed
- Added `codex_tools::ToolExecutor<Invocation>` as the shared execution
trait for model-visible tools.
- Moved the reusable execution support types from `codex-core` into
`codex-tools`:
- `FunctionCallError`
- `ToolPayload`
- `ToolOutput`
- Refactored core tool implementations so that execution behavior lives
on `ToolExecutor<ToolInvocation>`, while `ToolHandler` remains the
core-local extension point for hook payloads, telemetry tags, diff
consumers, and other orchestration concerns.
- Kept the registry and dispatch flow behaviorally unchanged while
making the shared/extracted boundary explicit across built-in, MCP,
dynamic, extension-backed, shell, and multi-agent tool handlers.
## Verification
- `cargo test -p codex-tools`
- `just fix -p codex-tools`
- `just fix -p codex-core`
- `cargo test -p codex-core` progressed through the updated tool
surfaces and then hit the existing unrelated multi-agent stack overflow
in
`tools::handlers::multi_agents::tests::tool_handlers_cascade_close_and_resume_and_keep_explicitly_closed_subtrees_closed`.
jif-oai