Commit Graph
6 Commits
Author SHA1 Message Date
jif 7b3eb8e4bc skills: expose remote skill resource tools (#27388)
## Why

PR #27387 makes backend plugin skills discoverable and invocable without
an executor, but resources referenced by those skills still sit behind
the generic MCP resource surface. The model needs a skills-owned API
that preserves the provider authority and package boundary instead of
treating remote resources like local files.

This is stacked on #27387.

## What

- Adds one `skills` namespace with bounded `list` and `read` tools for
remote skill providers.
- Revalidates `authority + package` against the live remote catalog on
every read, then routes the opaque resource ID back through that
provider.
- Allows the backend provider to read canonical child `skill://`
resources while rejecting cross-package, non-canonical, query, fragment,
and traversal-shaped URIs.
- Caps each serialized tool result at 8 KB. Lists are paginated; reads
return an opaque continuation cursor.
- Marks the JSON output as external context so memory generation can
apply its normal suppression policy.
- Deliberately does not add `skills.search`; that waits for a bounded
plugin-service search contract.

## Tool contract

Pseudo-Python matching the wire shape:

```python
from typing import Literal, NotRequired, TypedDict


class RemoteSkillAuthority(TypedDict):
    kind: Literal["remote"]
    id: str  # e.g. "codex_apps"


class RemoteSkill(TypedDict):
    authority: RemoteSkillAuthority
    package: str  # opaque provider-owned package ID
    name: str
    description: str
    main_resource: str  # opaque provider-owned SKILL.md ID


class SkillsListParams(TypedDict):
    cursor: NotRequired[str]


class SkillsListResult(TypedDict):
    skills: list[RemoteSkill]
    next_cursor: str | None
    warnings: list[str]
    truncated: bool


class SkillsReadParams(TypedDict):
    authority: RemoteSkillAuthority  # copied from skills.list
    package: str  # copied from skills.list
    resource: str  # provider-owned child resource ID
    cursor: NotRequired[str]  # copy next_cursor to continue


class SkillsReadResult(TypedDict):
    resource: str
    contents: str
    next_cursor: str | None
    truncated: bool


class Skills:
    def list(self, params: SkillsListParams) -> SkillsListResult: ...
    def read(self, params: SkillsReadParams) -> SkillsReadResult: ...
```

There is one namespace for all remote skills, not one tool or MCP server
per skill. No resource ID is converted into a filesystem path.

## Backend dependency

`/ps/mcp` must support direct reads of child resources such as
`skill://plugin_demo/deploy/references/deploy.md`. This PR implements
and tests the Codex side of that contract; production child reads remain
dependent on the corresponding plugin-service support. Search remains
out of scope until that service exposes a bounded search/resource API.

## Validation

- Added an app-server integration test covering `skills.list` followed
by `skills.read` with no executor.
- Ran `just fmt`.
- Ran `just bazel-lock-update` and `just bazel-lock-check`.
- Did not run Rust tests or Clippy locally, per request; CI will run
them.
2026-06-11 12:38:04 +02:00
rka-oai 26d9329833 [codex] Exclude external tool output from memories (#26821)
## Summary

- add contains_external_context() to tool output so other tools can be
opted out of influencing memory when disable_on_external_context=true
- Classify standalone web-search output as external context (to match
behavior as hosted web search)
- Verify with integration test
2026-06-08 16:53:04 +00:00
sayan-oai 34aad43684 add encryptedcontent to functioncalloutput (#23500)
add new `EncryptedContent` variant to `FunctionCallOutputContentItem`
ahead of standalone websearch.

we need to be able to receive and pass encrypted function call output
from the new web search endpoint back to responsesapi, as we cannot
expose direct search results.
2026-05-19 23:47:48 -07:00
jif-oai 6f1a01fbdd Simplify tool executor and registry plumbing (#22636)
## 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.
2026-05-15 11:47:54 +02:00
jif-oai 9c5dfa7b1a Refactor extension tools onto shared ToolExecutor (#22369)
## 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`
2026-05-13 12:12:06 +02:00
jif-oai 1824685a00 feat: extract shared tool executor interface (#22359)
## 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`.
2026-05-13 11:31:27 +02:00