## Summary
Some customer MCP tools expose large input schemas that exceed Codex's
compact schema budget even after description stripping. Today, the final
compaction pass collapses complex schemas starting at depth 2, which can
erase important shallow call structure such as small `anyOf` branches,
required fields, and help-mode entry points. In one reported case, this
degraded a tool schema into `query: any | any`, leaving the model
without enough structure to discover the required help call.
This change raises the deep-schema collapse boundary from depth 2 to
depth 3. That preserves one additional layer of the tool contract while
still collapsing deeper expensive subtrees to `{}` when a schema remains
over budget.
## What Changed
- Increased `MAX_COMPACT_TOOL_SCHEMA_DEPTH` from `2` to `3`.
- Updated the schema compaction traversal test to assert the new
collapse boundary.
- The resulting compacted shape keeps useful shallow structure, for
example:
- top-level argument names
- shallow `anyOf` branches
- required object fields
- nested property names one level deeper than before
## Validation
- Ran `just test -p codex-tools`: 81 tests passed.
- Ran a golden schema corpus comparison over 214 discovered tool input
schemas under `golden_schemas/*/mcp_tools/*/input_schema.json`.
- Depth 2 and depth 3 had identical percentile token counts across the
corpus.
- Both ended with `0 / 214` schemas over 1k tokens.
- Both ended with `0 / 214` schemas over the 4,000-byte compact JSON
budget.
- Only one golden schema changed, increasing from 49 to 56 tokens, so
this does not appear to introduce a meaningful corpus-wide regression.
Corpus percentile results:
| Percentile | Depth 2 | Depth 3 |
|---|---:|---:|
| p0 | 9 | 9 |
| p10 | 31 | 31 |
| p25 | 54 | 54 |
| p50 | 81 | 81 |
| p75 | 143 | 143 |
| p90 | 290 | 290 |
| p95 | 431 | 431 |
| p99 | 600 | 600 |
| max | 832 | 832 |
## Why
Some connector golden schemas use JSON Schema composition keywords
beyond `anyOf`, specifically top-level or nested `oneOf` and `allOf`.
Codex currently needs to preserve those shapes when parsing MCP tool
input schemas so connector tools do not lose valid schema structure
during normalization.
To prevent an increased Responses API error rate, this PR will be merged
after the Responses API supports top-level `oneOf`/`allOf`.
## What Changed
- Adds `oneOf` and `allOf` support to `JsonSchema`, matching the
existing `anyOf` handling.
- Traverses `oneOf` and `allOf` anywhere schema children are visited,
including sanitization, definition reachability, description stripping,
and deep schema compaction.
- Adds a final large-schema compaction pass that prunes schema objects
containing `anyOf`, `oneOf`, or `allOf` to `{}` if earlier compaction
passes still leave the schema over budget.
## Validation
Golden schema token validation over `2,025` schemas under
`golden_schemas`, all parsed successfully. Token count is `o200k_base`
over compact JSON from `parse_tool_input_schema`.
| Percentile | Before PR | After oneOf/allOf | After pruning |
|---|---:|---:|---:|
| p0 | 9 | 9 | 9 |
| p10 | 63 | 64 | 64 |
| p25 | 86 | 87 | 87 |
| p50 | 125 | 128 | 128 |
| p75 | 203 | 206 | 206 |
| p90 | 327 | 333 | 333 |
| p95 | 460 | 473 | 473 |
| p99 | 763 | 779 | 779 |
| max | 891 | 955 | 955 |
Totals:
| Parser state | Total tokens |
|---|---:|
| Before PR | 345,713 |
| After oneOf/allOf | 352,686 |
| After pruning | 352,686 |
The pruning column matches the oneOf/allOf column for this corpus
because no parsed compact golden schema remains over the `4,000`
compact-byte budget after the earlier compaction passes.
## Why
Users following the Amazon Bedrock API-key setup can export
`AWS_BEARER_TOKEN_BEDROCK` and `AWS_REGION`, but Codex's bearer-token
auth path only accepted `model_providers.amazon-bedrock.aws.region`.
That made the documented env-based setup fail with a missing-region
error even though the standard AWS region environment variable was
present.
## What Changed
- Updates Bedrock bearer-token region resolution to use
`model_providers.amazon-bedrock.aws.region` first, then fall back to
`AWS_REGION`, then `AWS_DEFAULT_REGION`.
- Updates the missing-region error to list all supported region sources.
- Adds focused coverage for config precedence, `AWS_REGION`,
`AWS_DEFAULT_REGION`, and the missing-region failure.
## Summary
Amazon Bedrock should expose GPT-5.5 alongside GPT-5.4, and the Bedrock
GPT entries should stay aligned with the canonical bundled OpenAI model
metadata instead of carrying a separate hand-written copy that can drift
over time. This change will be merged when the model is online.
This change:
- Adds the Bedrock Mantle model id for `openai.gpt-5.5`.
- Builds the Bedrock GPT-5.5 and GPT-5.4 catalog entries from the
bundled OpenAI model catalog, then overrides the Bedrock-facing slug,
explicit priority, and Bedrock-specific context windows.
- Hardcodes both `context_window` and `max_context_window` to `272000`
for Bedrock GPT-5.5 and GPT-5.4.
- Keeps `openai.gpt-5.5` as the default Bedrock model ahead of
`openai.gpt-5.4` and the Bedrock OSS models.
Client-side namespace tools are now supported by bedrock. Enable
`namespace_tools` for the Amazon Bedrock provider while continuing to
disable unsupported hosted tools such as image generation and web
search.
This reverts commit 5381240f57. Gov cloud
should not be supported
# External (non-OpenAI) Pull Request Requirements
External code contributions are by invitation only. Please read the
dedicated "Contributing" markdown file for details:
https://github.com/openai/codex/blob/main/docs/contributing.md
If your PR conforms to our contribution guidelines, replace this text
with a detailed and high quality description of your changes.
Include a link to a bug report or enhancement request.
## Why
Before changing the Codex Bridge JSON schema policy, add integration
coverage around real connector-like MCP tool schemas. The existing unit
tests cover individual sanitizer behaviors, but they do not make it easy
to see whether full fixture schemas keep model-visible guidance, prune
only unreachable definitions, drop unsupported JSON Schema fields, and
stay within the Responses API schema budget.
## What Changed
- Added `tools/tests/json_schema_policy_fixtures.rs`, which converts MCP
tool fixtures through `mcp_tool_to_responses_api_tool` and validates the
resulting Responses tool parameters.
- Added connector-style fixtures for Slack, Google Calendar, Google
Drive, Notion, and Microsoft Outlook Email under
`tools/tests/fixtures/json_schema_policy/`.
- Added fixture assertions for preserved guidance, pruned definitions,
expected field drops after `JsonSchema` conversion, marker count
baselines, and dangling local `$ref` prevention.
- Added a real oversized golden Notion `create_page` input schema
fixture to exercise the compaction path that strips descriptions, drops
root `$defs`, rewrites local refs, and fits the compacted schema under
the budget.
## Why
The `dev/cc/ref-def` branch preserves richer JSON Schema detail for
connector tools, including `$defs` and nested shapes. That improves
fidelity, but it pushes the largest connector schemas well past the
intended tool-schema budget. This PR adds a best-effort compaction pass
for unusually large tool input schemas so the p99 and max tails stay
small while ordinary schemas are left alone.
## What Changed
- Added best-effort large-schema compaction in
`codex-rs/tools/src/json_schema.rs` after schema sanitization and
definition pruning.
- Compaction runs as a waterfall only while the compact JSON budget
proxy is exceeded:
1. Strip schema `description` metadata.
2. Drop root `$defs` / `definitions`.
3. Collapse deep nested complex schema objects to `{}`.
- Kept top-level argument names and immediate schema shape where
possible.
## Corpus Results
Scope: 2,025 schemas under `golden_schemas`, all parsed successfully.
Token count is `o200k_base` over compact JSON from
`parse_tool_input_schema`.
| Percentile | Before `origin/main` `4dbca61e20` | After branch
`dev/cc/ref-def` `f9bf071758` | After this PR |
|---|---:|---:|---:|
| p0 | 9 | 9 | 9 |
| p10 | 59 | 63 | 63 |
| p25 | 81 | 86 | 86 |
| p50 | 114 | 127 | 125 |
| p75 | 174 | 205 | 202 |
| p90 | 295 | 335 | 322 |
| p95 | 391 | 526 | 422 |
| p99 | 794 | 1,303 | 689 |
| max | 2,836 | 3,337 | 887 |
After this PR, `0 / 2,025` schemas are over 1k tokens.
### Compaction Savings
These are cumulative waterfall stages over the same corpus. Later passes
only run for schemas that are still over the compact JSON budget proxy.
| Stage | Total tokens | Step savings | Schemas changed by step |
|---|---:|---:|---:|
| No compaction | 391,862 | - | - |
| Strip schema `description` metadata | 350,961 | 40,901 | 66 |
| Drop root `$defs` / `definitions` | 340,683 | 10,278 | 13 |
| Collapse deep complex schemas to `{}` | 335,875 | 4,808 | 6 |
# Why
Some connector tool input schemas use local JSON Schema references and
definition tables to avoid duplicating large nested shapes. Codex
previously lowered these schemas into the supported subset in a way that
could discard `$ref`-only schema objects and lose the corresponding
definitions, which made non-strict tool registration less faithful than
the original connector schema.
This keeps the existing minimal-lowering policy: Codex still does not
raw-pass through arbitrary JSON Schema, but it now preserves local
reference structure that fits the Responses-compatible subset and prunes
definition entries that cannot be reached by following `$ref`s from the
root schema after sanitization, including refs found transitively inside
other reachable definitions. The pruning matters because Responses
parses definition tables even when entries are unused, so keeping dead
definitions wastes prompt tokens.
# What changed
- Added `$ref`, `$defs`, and legacy `definitions` fields to the tool
`JsonSchema` representation.
- Updated `parse_tool_input_schema` lowering so `$ref`-only schema
objects survive sanitization instead of becoming `{}`.
- Sanitized definition tables recursively and dropped malformed
definition tables so non-strict registration degrades gracefully.
- Added reachability pruning for root definition tables by starting from
refs outside definition tables, then following refs inside reachable
definitions.
- Added JSON Pointer decoding for local definition refs such as
`#/$defs/Foo~1Bar`.
# Verification
ran local golden-schema probes against representative connector schemas
to validate behavior on real generated schemas:
| Golden schema | Before bytes | After bytes | `$defs` before -> after |
`$ref` before -> after | Result |
|---|---:|---:|---:|---:|---|
| `google_calendar/create_space` | 7111 | 4526 | 7 -> 7 | 7 -> 7 | all
definitions preserved because all are reachable |
| `figma/apply_file_variable_changes` | 4609 | 999 | 8 -> 5 | 8 -> 5 |
unused defs pruned after unsupported `oneOf` shapes lower away |
| `snowflake/list_catalog_integrations` | 1380 | 404 | 3 -> 0 | 0 -> 0 |
all defs pruned because none are referenced |
| `dropbox/create_shared_link` | 8894 | 1836 | 14 -> 4 | 9 -> 4 | only
defs reachable from the root schema after sanitization are retained,
including transitively through other retained defs |
Token increase across golden schema due to this change:
<img width="817" height="366" alt="Screenshot 2026-05-19 at 1 47 04 PM"
src="https://github.com/user-attachments/assets/d5c80fe9-da85-41e6-8ac7-a01d1e0b0f71"
/>
## Why
Some tool providers, especially MCP servers and dynamic tool sources,
can supply schema nodes that omit `type` and have no recognized JSON
Schema shape hints. Previously, `sanitize_json_schema` filled those
unknown nodes in as `string`, which made the schema parseable but
invented a scalar constraint that the provider did not specify. For
description-only fields, that could incorrectly steer tool arguments
away from the provider's actual accepted shape.
The Responses API accepts permissive empty schemas such as `{}` at
nested property positions, so Codex should preserve that permissive
meaning instead of coercing unknown schema nodes into a misleading
scalar type.
## What Changed
- Changed the no-hints fallback in `codex-rs/tools/src/json_schema.rs`
to clear unrecognized object schema nodes to `{}`.
- Empty schemas now remain `{}` rather than becoming `type: "string"`.
- Description-only or otherwise metadata-only nested property schemas
now become `{}` while surrounding object/array/string/number inference
still applies when recognized hints are present.
- Updated `codex-tools` and `codex-core` tests to cover top-level empty
schemas, nested empty schemas, metadata-only malformed schemas, dynamic
tools, and MCP tool specs.
## Verification
- `cargo test -p codex-tools`
- `cargo test -p codex-core
test_mcp_tool_property_missing_type_defaults_to_empty_schema`
- Manually verified the real Responses API behavior for both
empty-schema positions:
- Top-level function `parameters: {}` is accepted and echoed back as
`{"type":"object","properties":{}}`; when forced to call the tool,
Responses emitted empty object arguments: `"arguments": "{}"`.
- Nested property schema `{}` is accepted and preserved as `{}`; when
forced to call a tool with `metadata.extra`, Responses emitted
`"arguments": "{\"metadata\":{\"extra\":\"codex schema sanitizer
behavior\"}}"`.
## Why
Guardian review selection was hard-coded in `core`, which worked for the
default OpenAI path but did not give provider implementations a way to
choose backend-specific reviewer model IDs. That matters for Amazon
Bedrock: guardian review should run through the Bedrock/Mantle provider
using Bedrock's `openai.gpt-5.4` model ID, instead of accidentally
selecting a reviewer model that implies the OpenAI backend.
## What Changed
- Added provider-owned approval review model selection via
`ModelProvider::approval_review_model_selection`.
- Moved the existing default selection policy into the provider
abstraction: prefer the requested reviewer model when it is available,
otherwise fall back to the active turn model, preferring `Low` reasoning
when supported.
- Added an Amazon Bedrock override that pins guardian review to
`openai.gpt-5.4` with `Low` reasoning.
## Why
Amazon Bedrock Mantle needs a stable client-agent header so requests
from the built-in Bedrock provider can be identified as coming from
Codex for safety stack.
## What changed
- Added `x-amzn-mantle-client-agent: codex` to the built-in Amazon
Bedrock provider default HTTP headers.
## Summary
Codex's Amazon Bedrock provider signs Mantle requests with SigV4 using
credentials resolved by the AWS SDK. That worked for standard AWS
profiles and environment credentials, but AWS CLI console-login profiles
created by `aws login` require the SDK's `credentials-login` feature to
resolve `login_session` credentials.
This change enables that credential provider so Bedrock can use AWS
console-login credentials through the existing provider-owned AWS auth
path.
While testing the console-login path, we also hit a Mantle-specific
SigV4 regression from the new split between `session_id` and
`thread_id`. Mantle does not preserve legacy OpenAI compatibility
headers that use `snake_case` before SigV4 verification, so signing
those headers can make the server reconstruct a different canonical
request. The Bedrock auth path now removes that header class before
signing, keeping preserved hyphenated Codex/AWS headers such as
`x-codex-turn-metadata` signed normally.
## Changes
- Enable `aws-config`'s `credentials-login` feature in
`codex-rs/aws-auth`.
- Add a compile-time regression test for
`aws_config::login::LoginCredentialsProvider`.
- Strip `snake_case` compatibility headers from Bedrock Mantle SigV4
requests before signing.
- Expand the Bedrock auth regression test to cover `session_id`,
`thread_id`, and future headers of the same shape.
- Refresh Cargo and Bazel lockfiles for the added `aws-sdk-signin`
dependency.
## Tests
- tested with `aws login` locally and verified that it works as
intended.
## Why
`/status` was showing the configured `ModelProviderInfo.base_url` for
Amazon Bedrock, which can be stale or misleading because the actual
Bedrock Mantle endpoint is derived at runtime from the resolved AWS
region. This made sessions report the wrong provider endpoint even
though requests used the correct runtime URL.
## What changed
- Added `ModelProvider::runtime_base_url()` so provider implementations
can expose the request-time base URL through the shared runtime provider
abstraction.
- Moved Bedrock region-to-Mantle URL resolution into
`amazon_bedrock::mantle::runtime_base_url()`, keeping region resolution
private to the Mantle module.
- Overrode `runtime_base_url()` for Amazon Bedrock so it returns the
resolved Mantle endpoint instead of the configured default.
- Resolved and cached the runtime provider base URL during TUI startup,
then used that cached value when rendering `/status`.
- Added status coverage that verifies Bedrock displays the runtime URL
and ignores the configured Bedrock `base_url` when they differ.
## Verification
model provider is resolved correctly in local build:
<img width="696" height="245" alt="Screenshot 2026-04-29 at 5 01 36 PM"
src="https://github.com/user-attachments/assets/a13c10a5-3720-41ab-8ace-3c4bc573f971"
/>
## Summary
Amazon Bedrock Mantle's OpenAI-compatible endpoint now lives under
`/openai/v1`, and the GPT-5.4 Mantle model ID no longer uses the `-cmb`
suffix. This updates Codex's built-in Bedrock provider configuration so
generated providers and the static Bedrock catalog use the current
endpoint and model ID.
## Changes
- Update the Bedrock Mantle base URL from
`https://bedrock-mantle.{region}.api.aws/v1` to
`https://bedrock-mantle.{region}.api.aws/openai/v1`.
- Update the Amazon Bedrock default base URL in
`codex-model-provider-info`.
- Change the Bedrock GPT-5.4 catalog slug from `openai.gpt-5.4-cmb` to
`openai.gpt-5.4`.
- Align provider and catalog tests with the new URL and model ID.
## Test Plan
- Manual smoke test:
```shell
target/debug/codex \
-m openai.gpt-5.4 \
-c 'model_provider="amazon-bedrock"' \
-c 'model_providers.amazon-bedrock.aws.region="us-west-2"'
```
follow up of #19442. The app server now exposes provider-derived bounds
through a new v2 `modelProvider/read` method. The response reports the
configured provider map key as `modelProvider` and returns the effective
capability booleans so clients can align their UI with the same
provider-owned limits used by core.
## Why
Unsupported features must fail closed and Codex must not expose
OpenAI-hosted fallback paths when the active provider cannot support
them. In practice, Bedrock should not surface app connectors, MCP
servers, tool search/suggestions, image generation, web search, or JS
REPL until those paths are explicitly supported for that provider.
This PR moves that decision into provider-owned capability metadata
instead of scattering Bedrock-specific checks across callers.
## What changed
- Adds `ProviderCapabilities` to `codex-model-provider`, with default
support for existing providers and a Bedrock override that disables
unsupported launch surfaces.
- Adds `ToolCapabilityBounds` to `codex-tools` so provider capability
limits can clamp otherwise-enabled tool config.
- Applies capability bounds when building session and review-thread tool
config.
- Routes MCP/app connector configuration through
`McpManager::mcp_config`, which filters configured MCP servers and app
connectors based on the active provider.
- Updates app-server MCP list/read paths to use the filtered MCP config.
- Adds coverage for default provider capabilities, Bedrock disabled
capabilities, and optional tool-surface clamping.
## Testing
built locally and verified that bedrock responses api now return without
errors calling unsupported tools.
## Why
When using the Amazon Bedrock provider with `openai.gpt-5.4-cmb`, the
model picker allowed `xhigh` because the CMB catalog entry was derived
from the bundled `gpt-5.4` reasoning metadata. Bedrock rejects that
effort level, causing the request to fail before the turn can run:
```text
{"error":{"code":"validation_error","message":"Failed to deserialize the JSON body into the target type: Invalid 'reasoning': Invalid 'effort': unknown variant `xhigh`, expected one of `high`, `low`, `medium`, `minimal` at line 1 column 77239","param":null,"type":"invalid_request_error"}}
```
## What Changed
- Replace the runtime lookup of bundled `gpt-5.4` metadata for
`openai.gpt-5.4-cmb` with an explicit Bedrock CMB `ModelInfo` entry.
- Advertise only the Bedrock-supported CMB reasoning levels: `minimal`,
`low`, `medium`, and `high`.
- Keep the existing GPT OSS Bedrock model metadata and reasoning levels
unchanged.
- Add catalog coverage for the hardcoded CMB metadata and
Bedrock-compatible reasoning level list.
## Why
`openai.gpt-5.4-cmb` is served through the Amazon Bedrock provider,
whose request validator currently accepts `function` and `mcp` tool
specs but rejects Responses `custom` tools. The CMB catalog entry reuses
the bundled `gpt-5.4` metadata, which marks `apply_patch_tool_type` as
`freeform`. That causes Codex to include an `apply_patch` tool with
`type: "custom"`, so even heavily disabled sessions can fail before the
model runs with:
```text
Invalid tools: unknown variant `custom`, expected `function` or `mcp`
```
This is provider-specific: the model should still expose `apply_patch`,
but for Bedrock it needs to use the JSON/function tool shape instead of
the freeform/custom shape.
## What Changed
- Override the `openai.gpt-5.4-cmb` static catalog entry to set
`apply_patch_tool_type` to `function` after inheriting the rest of the
`gpt-5.4` model metadata.
- Update the catalog test expectation so the CMB entry continues to
track `gpt-5.4` metadata except for this Bedrock-specific tool shape
override.
## Verification
- `cargo test -p codex-model-provider`
- `just fix -p codex-model-provider`
## Why
`codex-models-manager` had grown to own provider-specific concerns:
constructing OpenAI-compatible `/models` requests, resolving provider
auth, emitting request telemetry, and deciding how provider catalogs
should be sourced. That made the manager harder to reuse for providers
whose model catalog is not fetched from the OpenAI `/models` endpoint,
such as Amazon Bedrock.
This change moves provider-specific model discovery behind
provider-owned implementations, so the models manager can focus on
refresh policy, cache behavior, picker ordering, and model metadata
merging.
## What Changed
- Introduced a `ModelsManager` trait with separate `OpenAiModelsManager`
and `StaticModelsManager` implementations.
- Added `ModelsEndpointClient` so OpenAI-compatible HTTP fetching lives
outside `codex-models-manager`.
- Moved `/models` request construction, provider auth resolution,
timeout handling, and request telemetry into `codex-model-provider` via
`OpenAiModelsEndpoint`.
- Added provider-owned `models_manager(...)` construction so configured
OpenAI-compatible providers use `OpenAiModelsManager`, while
static/catalog-backed providers can return `StaticModelsManager`.
- Added an Amazon Bedrock static model catalog for the GPT OSS Bedrock
model IDs.
- Updated core/session/thread manager code and tests to depend on
`Arc<dyn ModelsManager>`.
- Moved offline model test helpers into
`codex_models_manager::test_support`.
## Metadata References
The Bedrock catalog metadata is based on the official Amazon Bedrock
OpenAI model documentation:
- [Amazon Bedrock OpenAI
models](https://docs.aws.amazon.com/bedrock/latest/userguide/model-parameters-openai.html)
lists the Bedrock model IDs, text input/output modalities, and `128,000`
token context window for `gpt-oss-20b` and `gpt-oss-120b`.
- [Amazon Bedrock `gpt-oss-120b` model
card](https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-openai-gpt-oss-120b.html)
lists the `bedrock-runtime` model ID `openai.gpt-oss-120b-1:0`, the
`bedrock-mantle` model ID `openai.gpt-oss-120b`, text-only modalities,
and `128K` context window.
- [OpenAI `gpt-oss-120b` model
docs](https://developers.openai.com/api/docs/models/gpt-oss-120b)
document configurable reasoning effort with `low`, `medium`, and `high`,
plus text input/output modality.
The display names, default reasoning effort, and priority ordering are
Codex-local catalog choices.
## Test Plan
- Manually verified app-server model listing with an AWS profile:
```shell
CODEX_HOME="$(mktemp -d)" cargo run -p codex-app-server-test-client -- \
--codex-bin ./target/debug/codex \
-c 'model_provider="amazon-bedrock"' \
-c 'model_providers.amazon-bedrock.aws.profile="codex-bedrock"' \
-c 'model_providers.amazon-bedrock.aws.region="us-west-2"' \
model-list
```
The response returned the Bedrock catalog with `openai.gpt-oss-120b-1:0`
as the default model and `openai.gpt-oss-20b-1:0` as the second listed
model, both text-only and supporting low/medium/high reasoning effort.
## Why
AWS/Bedrock mode currently reports `account: null` with
`requiresOpenaiAuth: false` from `account/read`. That suppresses the
OpenAI-auth requirement, but it does not let app clients distinguish AWS
auth from any other non-OpenAI custom provider. For the prototype AWS
provider UX, clients need a simple provider-derived signal so they can
suppress ChatGPT/API-key login and token-refresh paths without
hardcoding Bedrock checks.
## What changed
- Adds an `aws` variant to the v2 `Account` protocol union.
- Adds `ProviderAccountKind` to `codex-model-provider` so the runtime
provider owns the app-visible account classification.
- Makes Amazon Bedrock return `ProviderAccountKind::Aws` from the
model-provider layer.
- Updates app-server `account/read` to map `ProviderAccountKind` to the
existing `GetAccountResponse` wire shape.
- Preserves the existing `account: null, requiresOpenaiAuth: false`
behavior for other non-OpenAI providers.
- Regenerates the app-server protocol schema fixtures.
- Adds coverage for provider account classification and for the Amazon
Bedrock `account/read` response.
## Testing
- `cargo test -p codex-model-provider`
- `cargo test -p codex-app-server-protocol`
- `cargo test -p codex-app-server get_account_with_aws_provider`
## Notes
I attempted `just bazel-lock-update` and `just bazel-lock-check`, but
both are blocked in my local environment because `bazel` is not
installed.
## Summary
The Bedrock Mantle SigV4 auth provider currently looks like it can
lazily load `AwsAuthContext`, but the provider is only constructed after
`resolve_auth_method` has already loaded that context. Because
`with_context` always pre-populates the `OnceCell`, the
`get_or_try_init` fallback is unused in normal operation and makes the
provider lifecycle harder to reason about.
This change removes that dead lazy-loading path and makes the actual
behavior explicit:
- `BedrockAuthMethod::AwsSdkAuth` carries only the resolved
`AwsAuthContext`.
- `BedrockMantleSigV4AuthProvider` stores the resolved context directly.
- request signing uses the stored context without going through
`OnceCell`.
The existing eager AWS auth resolution behavior is unchanged; this is a
simplification of the provider state, not a behavior change.
## Testing
- `cargo shear`
- `cargo test -p codex-model-provider`
- `just bazel-lock-check`
## Summary
Add first-class Amazon Bedrock Mantle provider support so Codex can keep
using its existing Responses API transport with OpenAI-compatible
AWS-hosted endpoints such as AOA/Mantle.
This is needed for the AWS launch path, where provider traffic should
authenticate with AWS credentials instead of OpenAI bearer credentials.
Requests are authenticated immediately before transport send, so SigV4
signs the final method, URL, headers, and body bytes that `reqwest` will
send.
## What Changed
- Added a new `codex-aws-auth` crate for loading AWS SDK config,
resolving credentials, and signing finalized HTTP requests with AWS
SigV4.
- Added a built-in `amazon-bedrock` provider that targets Bedrock Mantle
Responses endpoints, defaults to `us-east-1`, supports region/profile
overrides, disables WebSockets, and does not require OpenAI auth.
- Added Amazon Bedrock auth resolution in `codex-model-provider`: prefer
`AWS_BEARER_TOKEN_BEDROCK` when set, otherwise use AWS SDK credentials
and SigV4 signing.
- Added `AuthProvider::apply_auth` and `Request::prepare_body_for_send`
so request-signing providers can sign the exact outbound request after
JSON serialization/compression.
- Determine the region by taking the `aws.region` config first (required
for bearer token codepath), and fallback to SDK default region.
## Testing
Amazon Bedrock Mantle Responses paths:
- Built the local Codex binary with `cargo build`.
- Verified the custom proxy-backed `aws` provider using `env_key =
"AWS_BEARER_TOKEN_BEDROCK"` streamed raw `responses` output with
`response.output_text.delta`, `response.completed`, and `mantle-env-ok`.
- Verified a full `codex exec --profile aws` turn returned
`mantle-env-ok`.
- Confirmed the custom provider used the bearer env var, not AWS profile
auth: bogus `AWS_PROFILE` still passed, empty env var failed locally,
and malformed env var reached Mantle and failed with `401
invalid_api_key`.
- Verified built-in `amazon-bedrock` with `AWS_BEARER_TOKEN_BEDROCK` set
passed despite bogus AWS profiles, returning `amazon-bedrock-env-ok`.
- Verified built-in `amazon-bedrock` SDK/SigV4 auth passed with
`AWS_BEARER_TOKEN_BEDROCK` unset and temporary AWS session env
credentials, returning `amazon-bedrock-sdk-env-ok`.
## Why
Codex needs a first-class `amazon-bedrock` model provider so users can
select Bedrock without copying a full provider definition into
`config.toml`. The provider has Codex-owned defaults for the pieces that
should stay consistent across users: the display `name`, Bedrock
`base_url`, and `wire_api`.
At the same time, users still need a way to choose the AWS credential
profile used by their local environment. This change makes
`amazon-bedrock` a partially modifiable built-in provider: code owns the
provider identity and endpoint defaults, while user config can set
`model_providers.amazon-bedrock.aws.profile`.
For example:
```toml
model_provider = "amazon-bedrock"
[model_providers.amazon-bedrock.aws]
profile = "codex-bedrock"
```
## What Changed
- Added `amazon-bedrock` to the built-in model provider map with:
- `name = "Amazon Bedrock"`
- `base_url = "https://bedrock-mantle.us-east-1.api.aws/v1"`
- `wire_api = "responses"`
- Added AWS provider auth config with a profile-only shape:
`model_providers.<id>.aws.profile`.
- Kept AWS auth config restricted to `amazon-bedrock`; custom providers
that set `aws` are rejected.
- Allowed `model_providers.amazon-bedrock` through reserved-provider
validation so it can act as a partial override.
- During config loading, only `aws.profile` is copied from the
user-provided `amazon-bedrock` entry onto the built-in provider. Other
Bedrock provider fields remain hard-coded by the built-in definition.
- Updated the generated config schema for the new provider AWS profile
config.
## Summary
- Add `codex-model-provider` as the runtime home for model-provider
behavior that does not belong in `codex-core`, `codex-login`, or
`codex-api`.
- The new crate wraps configured `ModelProviderInfo` in a
`ModelProvider` trait object that can resolve the API provider config,
provider-scoped auth manager, and request auth provider for each call.
- This centralizes provider auth behavior in one place today, and gives
us an extension point for future provider-specific auth, model listing,
request setup, and related runtime behavior.
## Tests
Ran tests manually to make sure that provider auth under different
configs still work as expected.
---------
Co-authored-by: pakrym-oai <pakrym@openai.com>
## Summary
This PR replaces the legacy network allow/deny list model with explicit
rule maps for domains and unix sockets across managed requirements,
permissions profiles, the network proxy config, and the app server
protocol.
Concretely, it:
- introduces typed domain (`allow` / `deny`) and unix socket permission
(`allow` / `none`) entries instead of separate `allowed_domains`,
`denied_domains`, and `allow_unix_sockets` lists
- updates config loading, managed requirements merging, and exec-policy
overlays to read and upsert rule entries consistently
- exposes the new shape through protocol/schema outputs, debug surfaces,
and app-server config APIs
- rejects the legacy list-based keys and updates docs/tests to reflect
the new config format
## Why
The previous representation split related network policy across multiple
parallel lists, which made merging and overriding rules harder to reason
about. Moving to explicit keyed permission maps gives us a single source
of truth per host/socket entry, makes allow/deny precedence clearer, and
gives protocol consumers access to the full rule state instead of
derived projections only.
## Backward Compatibility
### Backward compatible
- Managed requirements still accept the legacy
`experimental_network.allowed_domains`,
`experimental_network.denied_domains`, and
`experimental_network.allow_unix_sockets` fields. They are normalized
into the new canonical `domains` and `unix_sockets` maps internally.
- App-server v2 still deserializes legacy `allowedDomains`,
`deniedDomains`, and `allowUnixSockets` payloads, so older clients can
continue reading managed network requirements.
- App-server v2 responses still populate `allowedDomains`,
`deniedDomains`, and `allowUnixSockets` as legacy compatibility views
derived from the canonical maps.
- `managed_allowed_domains_only` keeps the same behavior after
normalization. Legacy managed allowlists still participate in the same
enforcement path as canonical `domains` entries.
### Not backward compatible
- Permissions profiles under `[permissions.<profile>.network]` no longer
accept the legacy list-based keys. Those configs must use the canonical
`[domains]` and `[unix_sockets]` tables instead of `allowed_domains`,
`denied_domains`, or `allow_unix_sockets`.
- Managed `experimental_network` config cannot mix canonical and legacy
forms in the same block. For example, `domains` cannot be combined with
`allowed_domains` or `denied_domains`, and `unix_sockets` cannot be
combined with `allow_unix_sockets`.
- The canonical format can express explicit `"none"` entries for unix
sockets, but those entries do not round-trip through the legacy
compatibility fields because the legacy fields only represent allow/deny
lists.
## Testing
`/target/debug/codex sandbox macos --log-denials /bin/zsh -c 'curl
https://www.example.com' ` gives 200 with config
```
[permissions.workspace.network.domains]
"www.example.com" = "allow"
```
and fails when set to deny: `curl: (56) CONNECT tunnel failed, response
403`.
Also tested backward compatibility path by verifying that adding the
following to `/etc/codex/requirements.toml` works:
```
[experimental_network]
allowed_domains = ["www.example.com"]
```
built from #14256. PR description from @etraut-openai:
This PR addresses a hole in [PR
11802](https://github.com/openai/codex/pull/11802). The previous PR
assumed that app server clients would respond to token refresh failures
by presenting the user with an error ("you must log in again") and then
not making further attempts to call network endpoints using the expired
token. While they do present the user with this error, they don't
prevent further attempts to call network endpoints and can repeatedly
call `getAuthStatus(refreshToken=true)` resulting in many failed calls
to the token refresh endpoint.
There are three solutions I considered here:
1. Change the getAuthStatus app server call to return a null auth if the
caller specified "refreshToken" on input and the refresh attempt fails.
This will cause clients to immediately log out the user and return them
to the log in screen. This is a really bad user experience. It's also a
breaking change in the app server contract that could break third-party
clients.
2. Augment the getAuthStatus app server call to return an additional
field that indicates the state of "token could not be refreshed". This
is a non-breaking change to the app server API, but it requires
non-trivial changes for all clients to properly handle this new field
properly.
3. Change the getAuthStatus implementation to handle the case where a
token refresh fails by marking the AuthManager's in-memory access and
refresh tokens as "poisoned" so it they are no longer used. This is the
simplest fix that requires no client changes.
I chose option 3.
Here's Codex's explanation of this change:
When an app-server client asks `getAuthStatus(refreshToken=true)`, we
may try to refresh a stale ChatGPT access token. If that refresh fails
permanently (for example `refresh_token_reused`, expired, or revoked),
the old behavior was bad in two ways:
1. We kept the in-memory auth snapshot alive as if it were still usable.
2. Later auth checks could retry refresh again and again, creating a
storm of doomed `/oauth/token` requests and repeatedly surfacing the
same failure.
This is especially painful for app-server clients because they poll auth
status and can keep driving the refresh path without any real chance of
recovery.
This change makes permanent refresh failures terminal for the current
managed auth snapshot without changing the app-server API contract.
What changed:
- `AuthManager` now poisons the current managed auth snapshot in memory
after a permanent refresh failure, keyed to the unchanged `AuthDotJson`.
- Once poisoned, later refresh attempts for that same snapshot fail fast
locally without calling the auth service again.
- The poison is cleared automatically when auth materially changes, such
as a new login, logout, or reload of different auth state from storage.
- `getAuthStatus(includeToken=true)` now omits `authToken` after a
permanent refresh failure instead of handing out the stale cached bearer
token.
This keeps the current auth method visible to clients, avoids forcing an
immediate logout flow, and stops repeated refresh attempts for
credentials that cannot recover.
---------
Co-authored-by: Eric Traut <etraut@openai.com>
Follow up to #15357 by making proactive ChatGPT auth refresh depend on
the access token's JWT expiration instead of treating `last_refresh` age
as the primary source of truth.
## Summary
Fix a managed ChatGPT auth bug where a stale Codex process could
proactively refresh using an old in-memory refresh token even after
another process had already rotated auth on disk.
This changes the proactive `AuthManager::auth()` path to reuse the
existing guarded `refresh_token()` flow instead of calling the refresh
endpoint directly from cached auth state.
## Original Issue
Users reported repeated `codexd` log lines like:
```text
ERROR codex_core::auth: Failed to refresh token: error sending request for url (https://auth.openai.com/oauth/token)
```
In practice this showed up most often when multiple `codexd` processes
were left running. Killing the extra processes stopped the noise, which
suggested the issue was caused by stale auth state across processes
rather than invalid user credentials.
## Diagnosis
The bug was in the proactive refresh path used by `AuthManager::auth()`:
- Process A could refresh successfully, rotate refresh token `R0` to
`R1`, and persist the updated auth state plus `last_refresh` to disk.
- Process B could keep an older auth snapshot cached in memory, still
holding `R0` and the old `last_refresh`.
- Later, when Process B called `auth()`, it checked staleness from its
cached in-memory auth instead of first reloading from disk.
- Because that cached `last_refresh` was stale, Process B would
proactively call `/oauth/token` with stale refresh token `R0`.
- On failure, `auth()` logged the refresh error but kept returning the
same stale cached auth, so repeated `auth()` calls could keep retrying
with dead state.
This differed from the existing unauthorized-recovery flow, which
already did the safer thing: guarded reload from disk first, then
refresh only if the on-disk auth was unchanged.
## What Changed
- Switched proactive refresh in `AuthManager::auth()` to:
- do a pure staleness check on cached auth
- call `refresh_token()` when stale
- return the original cached auth on genuine refresh failure, preserving
existing outward behavior
- Removed the direct proactive refresh-from-cached-state path
- Added regression tests covering:
- stale cached auth with newer same-account auth already on disk
- the same scenario even when the refresh endpoint would fail if called
## Why This Fix
`refresh_token()` already contains the right cross-process safety
behavior:
- guarded reload from disk
- same-account verification
- skip-refresh when another process already changed auth
Reusing that path makes proactive refresh consistent with unauthorized
recovery and prevents stale processes from trying to refresh
already-rotated tokens.
## Testing
Test shape:
- create a fresh temp `CODEX_HOME` from `~/.codex/auth.json`
- force `last_refresh` to an old timestamp so proactive refresh is
required
- start two long-lived helper processes against the same auth file
- start `B` first so it caches stale auth and sleeps
- start `A` second so it refreshes first
- point both at a local mock `/oauth/token` server
- inspect whether `B` makes a second refresh request with the stale
in-memory token, or reloads the rotated token from disk
### Before the fix
The repro showed the bug clearly: the mock server saw two refreshes with
the same stale token, `A` rotated to a new token, and `B` still returned
the stale token instead of reloading from disk.
```text
POST /oauth/token refresh_token=rt_j6s0...
POST /oauth/token refresh_token=rt_j6s0...
B:cached_before=rt_j6s0...
B:cached_after=rt_j6s0...
B:returned=rt_j6s0...
A:cached_before=rt_j6s0...
A:cached_after=rotated-refresh-token-logged-run-v2
A:returned=rotated-refresh-token-logged-run-v2
```
### After the fix
After the fix, the mock server saw only one refresh request. `A`
refreshed once, and `B` started with the stale token but reloaded and
returned the rotated token.
```text
POST /oauth/token refresh_token=rt_j6s0...
B:cached_before=rt_j6s0...
B:cached_after=rotated-refresh-token-fix-branch
B:returned=rotated-refresh-token-fix-branch
A:cached_before=rt_j6s0...
A:cached_after=rotated-refresh-token-fix-branch
A:returned=rotated-refresh-token-fix-branch
```
This shows the new behavior: `A` refreshes once, then `B` reuses the
updated auth from disk instead of making a second refresh request with
the stale token.
## Summary
This PR fixes restricted filesystem permission profiles so Codex's
runtime-managed helper executables remain readable without requiring
explicit user configuration.
- add implicit readable roots for the configured `zsh` helper path and
the main execve wrapper
- allowlist the shared `$CODEX_HOME/tmp/arg0` root when the execve
wrapper lives there, so session-specific helper paths keep working
- dedupe injected paths and avoid adding duplicate read entries to the
sandbox policy
- add regression coverage for restricted read mode with helper
executable overrides
## Testing
before this change: got this error when executing a shell command via
zsh fork:
```
"sandbox error: sandbox denied exec error, exit code: 127, stdout: , stderr: /etc/zprofile:11: operation not permitted: /usr/libexec/path_helper\nzsh:1: operation not permitted: .codex/skills/proxy-a/scripts/fetch_example.sh\n"
```
saw this change went away after this change, meaning the readable roots
and injected correctly.
## Summary
This lets skill loading split `permissions.network` into two distinct
pieces:
- `permissions.network.enabled` still feeds the skill
`PermissionProfile` and remains the coarse gate for whether the skill
can use network access at all.
- `permissions.network.allowed_domains` and
`permissions.network.denied_domains` are lifted into a new
`SkillManagedNetworkOverride` so managed-network sessions can start
per-skill scoped proxies with the right domain overrides.
The change also updates `SkillMetadata` construction sites and adds
loader tests covering YAML parsing plus normalization of the network
gate vs. domain override fields.
## Follow-up
A PR that uses the network_override to spin up a skill-specific proxy if
network_override is not none.
## Summary
- add `skill_approval` to `RejectConfig` and the app-server v2
`AskForApproval::Reject` payload so skill-script prompts can be
configured independently from sandbox and rule-based prompts
- update Unix shell escalation to reject prompts based on the actual
decision source, keeping prefix rules tied to `rules`, unmatched command
fallbacks tied to `sandbox_approval`, and skill scripts tied to
`skill_approval`
- regenerate the affected protocol/config schemas and expand
unit/integration coverage for the new flag and skill approval behavior
## Summary
- distinguish reject-policy handling for prefix-rule approvals versus
sandbox approvals in Unix shell escalation
- keep prompting for skill-script execution when `rules=true` but
`sandbox_approval=false`, instead of denying the command up front
- add regression coverage for both skill-script reject-policy paths in
`codex-rs/core/tests/suite/skill_approval.rs`
## Summary
- Treat skill scripts with no permission profile, or an explicitly empty
one, as permissionless and run them with the turn's existing sandbox
instead of forcing an exec approval prompt.
- Keep the approval flow unchanged for skills that do declare additional
permissions.
- Update the skill approval tests to assert that permissionless skill
scripts do not prompt on either the initial run or a rerun.
## Why
Permissionless skills should inherit the current turn sandbox directly.
Prompting for exec approval in that case adds friction without granting
any additional capability.
## Summary
This PR:
1. fixes a deserialization mismatch for macOS automation permissions in
approval payloads by making core parsing accept both supported wire
shapes for bundle IDs.
2. added `#[serde(default)]` to `MacOsSeatbeltProfileExtensions` so
omitted fields deserialize to secure defaults.
## Why this change is needed
`MacOsAutomationPermission` uses `#[serde(try_from =
"MacOsAutomationPermissionDe")]`, so deserialization is controlled by
`MacOsAutomationPermissionDe`. After we aligned v2
`additionalPermissions.macos.automations` to the core shape, approval
payloads started including `{ "bundle_ids": [...] }` in some paths.
`MacOsAutomationPermissionDe` previously accepted only `"none" | "all"`
or a plain array, so object-shaped bundle IDs failed with `data did not
match any variant of untagged enum MacOsAutomationPermissionDe`. This
change restores compatibility by accepting both forms while preserving
existing normalization behavior (trim values and map empty bundle lists
to `None`).
## Validation
saw this error went away when running
```
cargo run -p codex-app-server-test-client -- \
--codex-bin ./target/debug/codex \
-c 'approval_policy="on-request"' \
-c 'features.shell_zsh_fork=true' \
-c 'zsh_path="/tmp/codex-zsh-fork/package/vendor/aarch64-apple-darwin/zsh/macos-15/zsh"' \
send-message-v2 --experimental-api \
'Use $apple-notes and run scripts/notes_info now.'
```
:
```
Error: failed to deserialize ServerRequest from JSONRPCRequest
Caused by:
data did not match any variant of untagged enum MacOsAutomationPermissionDe
```
## Summary
This PR removes legacy macOS permission model types from
`codex-rs/protocol/src/models.rs`:
- `MacOsPermissions`
- `MacOsPreferencesValue`
- `MacOsAutomationValue`
The protocol now relies on the current `MacOsSeatbeltProfileExtensions`
model for macOS permission data.
## Summary
This changes the Unix shell escalation path for skill-matched
executables to apply a skill's `PermissionProfile` as additive
permissions on top of the existing turn/request sandbox policy.
Previously, skill-matched executables compiled the skill permission
profile into a standalone sandbox policy and executed against that
replacement policy. Now they go through the same
`additional_permissions` merge path used elsewhere in shell sandbox
preparation.
## What Changed
- Changed `skill_escalation_execution()` to return
`EscalationPermissions::PermissionProfile(...)` for non-empty skill
permission profiles.
- Kept empty or missing skill permission profiles on the `TurnDefault`
path.
- Added tests covering the new additive skill-permission behavior.
- Added inline comments in `prepare_escalated_exec()` clarifying the
difference between additive permission merging and fully specified
replacement sandbox policies.
- Removed the now-unused skill permission compiler module after
switching this path away from standalone compiled skill sandbox
policies.
## Testing
- Ran `just fmt` in `codex-rs`
- Ran `cargo test -p codex-core`
`cargo test -p codex-core` still hits an unrelated existing failure:
`shell_snapshot::tests::snapshot_shell_does_not_inherit_stdin`
## Follow-up
This change intentionally does not merge skill-specific macOS seatbelt
profile extensions through the `additional_permissions` path yet.
Filesystem and network permissions now follow the additive merge path,
but seatbelt extension permissions still need separate handling in a
follow-up PR.
## Summary
Changes the permission profile shape from a bare network boolean to a
nested object.
Before:
```yaml
permissions:
network: true
```
After:
```yaml
permissions:
network:
enabled: true
```
This also updates the shared Rust and app-server protocol types so
`PermissionProfile.network` is no longer `Option<bool>`, but
`Option<NetworkPermissions>` with `enabled: Option<bool>`.
## What Changed
- Updated `PermissionProfile` in `codex-rs/protocol/src/models.rs`:
- `pub network: Option<bool>` -> `pub network:
Option<NetworkPermissions>`
- Added `NetworkPermissions` with:
- `pub enabled: Option<bool>`
- Changed emptiness semantics so `network` is only considered empty when
`enabled` is `None`
- Updated skill metadata parsing to accept `permissions.network.enabled`
- Updated core permission consumers to read
`network.enabled.unwrap_or(false)` where a concrete boolean is needed
- Updated app-server v2 protocol types and regenerated schema/TypeScript
outputs
- Updated docs to mention `additionalPermissions.network.enabled`
## Summary
`PermissionProfile.network` could not be preserved when additional or
compiled permissions resolved to
`SandboxPolicy::ReadOnly`, because `ReadOnly` had no network_access
field. This change makes read-only + network
enabled representable directly and threads that through the protocol,
app-server v2 mirror, and permission-
merging logic.
## What changed
- Added `network_access: bool` to `SandboxPolicy::ReadOnly` in the core
protocol and app-server v2 protocol.
- Kept backward compatibility by defaulting the new field to false, so
legacy read-only payloads still
deserialize unchanged.
- Updated `has_full_network_access()` and sandbox summaries to respect
read-only network access.
- Preserved PermissionProfile.network when:
- compiling skill permission profiles into sandbox policies
- normalizing additional permissions
- merging additional permissions into existing sandbox policies
- Updated the approval overlay to show network in the rendered
permission rule when requested.
- Regenerated app-server schema fixtures for the new v2 wire shape.
## Summary
This change removes the compiled permissions field from skill metadata
and keeps permission_profile as the single source of truth.
Skill loading no longer compiles skill permissions eagerly. Instead, the
zsh-fork skill escalation path compiles `skill.permission_profile` when
it needs to determine the sandbox to apply for a skill script.
## Behavior change
For skills that declare:
```
permissions: {}
```
we now treat that the same as having no skill permissions override,
instead of creating and using a default readonly sandbox. This change
makes the behavior more intuitive:
- only non-empty skill permission profiles affect sandboxing
- omitting permissions and writing permissions: {} now mean the same
thing
- skill metadata keeps a single permissions representation instead of
storing derived state too
Overall, this makes skill sandbox behavior easier to understand and more
predictable.
## Summary
This PR includes the session's local date and timezone in the
model-visible environment context and persists that data in
`TurnContextItem`.
## What changed
- captures the current local date and IANA timezone when building a turn
context, with a UTC fallback if the timezone lookup fails
- includes current_date and timezone in the serialized
<environment_context> payload
- stores those fields on TurnContextItem so they survive rollout/history
handling, subagent review threads, and resume flows
- treats date/timezone changes as environment updates, so prompt caching
and context refresh logic do not silently reuse stale time context
- updates tests to validate the new environment fields without depending
on a single hardcoded environment-context string
## test
built a local build and saw it in the rollout file:
```
{"timestamp":"2026-02-26T21:39:50.737Z","type":"response_item","payload":{"type":"message","role":"user","content":[{"type":"input_text","text":"<environment_context>\n <shell>zsh</shell>\n <current_date>2026-02-26</current_date>\n <timezone>America/Los_Angeles</timezone>\n</environment_context>"}]}}
```
This reverts commit https://github.com/openai/codex/pull/12633. We no
longer need this PR, because we favor sending normal exec command
approval server request with `additional_permissions` of skill
permissions instead
This reverts commit daf0f03ac8.
# External (non-OpenAI) Pull Request Requirements
Before opening this Pull Request, please read the dedicated
"Contributing" markdown file or your PR may be closed:
https://github.com/openai/codex/blob/main/docs/contributing.md
If your PR conforms to our contribution guidelines, replace this text
with a detailed and high quality description of your changes.
Include a link to a bug report or enhancement request.
## Summary
- Preserve each skill’s raw permissions block as a permission_profile on
SkillMetadata during skill loading.
- Keep compiling that same metadata into the existing runtime
Permissions object, so current enforcement
behavior stays intact.
- When zsh-fork intercepts execution of a script that belongs to a
skill, include the skill’s
permission_profile in the exec approval request.
- This lets approval UIs show the extra filesystem access the skill
declared when prompting for approval.
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.
Problem:
1. turn id is constructed in-memory;
2. on resuming threads, turn_id might not be unique;
3. client cannot no the boundary of a turn from rollout files easily.
This PR does three things:
1. persist `task_started` and `task_complete` events;
1. persist `turn_id` in rollout turn events;
5. generate turn_id as unique uuids instead of incrementing it in
memory.
This helps us resolve the issue of clients wanting to have unique turn
ids for resuming a thread, and knowing the boundry of each turn in
rollout files.
example debug logs
```
2026-02-11T00:32:10.746876Z DEBUG codex_app_server_protocol::protocol::thread_history: built turn from rollout items turn_index=8 turn=Turn { id: "019c4a07-d809-74c3-bc4b-fd9618487b4b", items: [UserMessage { id: "item-24", content: [Text { text: "hi", text_elements: [] }] }, AgentMessage { id: "item-25", text: "Hi. I’m in the workspace with your current changes loaded and ready. Send the next task and I’ll execute it end-to-end." }], status: Completed, error: None }
2026-02-11T00:32:10.746888Z DEBUG codex_app_server_protocol::protocol::thread_history: built turn from rollout items turn_index=9 turn=Turn { id: "019c4a18-1004-76c0-a0fb-a77610f6a9b8", items: [UserMessage { id: "item-26", content: [Text { text: "hello", text_elements: [] }] }, AgentMessage { id: "item-27", text: "Hello. Ready for the next change in `codex-rs`; I can continue from the current in-progress diff or start a new task." }], status: Completed, error: None }
2026-02-11T00:32:10.746899Z DEBUG codex_app_server_protocol::protocol::thread_history: built turn from rollout items turn_index=10 turn=Turn { id: "019c4a19-41f0-7db0-ad78-74f1503baeb8", items: [UserMessage { id: "item-28", content: [Text { text: "hello", text_elements: [] }] }, AgentMessage { id: "item-29", text: "Hello. Send the specific change you want in `codex-rs`, and I’ll implement it and run the required checks." }], status: Completed, error: None }
```
backward compatibility:
if you try to resume an old session without task_started and
task_complete event populated, the following happens:
- If you resume and do nothing: those reconstructed historical IDs can
differ next time you resume.
- If you resume and send a new turn: the new turn gets a fresh UUID from
live submission flow and is persisted, so that new turn’s ID is stable
on later resumes.
I think this behavior is fine, because we only care about deterministic
turn id once a turn is triggered.
Persist thread_dynamic_tools in sqlite and read first from it. Fall back
to rollout files if it's not found. Persist dynamic tools to both sqlite
and rollout files.
Saw that new sessions get populated to db correctly & old sessions get
backfilled correctly at startup:
```
celia@com-92114 codex-rs % sqlite3 ~/.codex/state.sqlite \ "select thread_id, position,name,description,input_schema from thread_dynamic_tools;"
019c0cad-ec0d-74b2-a787-e8b33a349117|0|geo_lookup|lookup a city|{"properties":{"city":{"type":"string"}},"required":["city"],"type":"object"}
....
019c10ca-aa4b-7620-ae40-c0919fbd7ea7|0|geo_lookup|lookup a city|{"properties":{"city":{"type":"string"}},"required":["city"],"type":"object"}
```
Add dynamic tools to rollout file for persistence & read from rollout on
resume. Ran a real example and spotted the following in the rollout
file:
```
{"timestamp":"2026-01-29T01:27:57.468Z","type":"session_meta","payload":{"id":"019c075d-3f0b-77e3-894e-c1c159b04b1e","timestamp":"2026-01-29T01:27:57.451Z","...."dynamic_tools":[{"name":"demo_tool","description":"Demo dynamic tool","inputSchema":{"additionalProperties":false,"properties":{"city":{"type":"string"}},"required":["city"],"type":"object"}}],"git":{"commit_hash":"ebc573f15c01b8af158e060cfedd401f043e9dfa","branch":"dev/cc/dynamic-tools","repository_url":"https://github.com/openai/codex.git"}}}
```
Fix flakiness of CI test:
https://github.com/openai/codex/actions/runs/20350530276/job/58473691434?pr=8282
This PR does two things:
1. move the flakiness test to use responses API instead of chat
completion API
2. make mcp_process agnostic to the order of
responses/notifications/requests that come in, by buffering messages not
read
Fix flakiness of CI tests:
https://github.com/openai/codex/actions/runs/20350530276/job/58473691443?pr=8282
This PR does two things:
1. test with responses API instead of chat completions API in
thread_resume tests;
2. have a new responses API fixture that mocks out arbitrary numbers of
responses API calls (including no calls) and have the same repeated
response.
Tested by CI
Add a dmg target that bundles the codex and codex responses api proxy
binaries for MacOS. this target is signed and notarized.
Verified by triggering a build here:
https://github.com/openai/codex/actions/runs/20318136302/job/58367155205.
Downloaded the artifact and verified that the dmg is signed and
notarized, and the codex binary contained works as expected.
Our previous design of cancellation endpoint is not idempotent, which
caused a bunch of flaky tests. Make app server just returned a not_found
status instead of throwing an error if the login id is not found. Keep
V1 endpoint behavior the same.
Make sure that config writes preserve comments and order of configs by
utilizing the ConfigEditsBuilder in core.
Tested by running a real example and made sure that nothing in the
config file changes other than the configs to edit.
When we are writing to config using `config/value/write` or
`config/batchWrite`, it always require a `config/read` before it right
now in order to get the correct file path to write to. make this
optional so we read from the default user config file if this is not
passed in.
Add a new endpoint that allows us to test multi-turn behavior.
Tested with running:
```
RUST_LOG=codex_app_server=debug CODEX_BIN=target/debug/codex \
cargo run -p codex-app-server-test-client -- \
send-follow-up-v2 "hello" "and now a follow-up question"
```
This reverts commit c2ec477d93.
# External (non-OpenAI) Pull Request Requirements
Before opening this Pull Request, please read the dedicated
"Contributing" markdown file or your PR may be closed:
https://github.com/openai/codex/blob/main/docs/contributing.md
If your PR conforms to our contribution guidelines, replace this text
with a detailed and high quality description of your changes.
Include a link to a bug report or enhancement request.
similar to logic in
`codex/codex-rs/exec/src/event_processor_with_jsonl_output.rs`.
translation of v1 -> v2 events:
`codex/event/task_complete` -> `turn/completed`
`codex/event/turn_aborted` -> `turn/completed` with `interrupted` status
`codex/event/error` -> `turn/completed` with `error` status
this PR also makes `items` field in `Turn` optional. For now, we only
populate it when we resume a thread, and leave it as None for all other
places until we properly rewrite core to keep track of items.
tested using the codex app server client. example new event:
```
< {
< "method": "turn/completed",
< "params": {
< "turn": {
< "id": "0",
< "items": [],
< "status": "interrupted"
< }
< }
< }
```
core event to app server event mapping:
1. `codex/event/reasoning_content_delta` ->
`item/reasoning/summaryTextDelta`.
2. `codex/event/reasoning_raw_content_delta` ->
`item/reasoning/textDelta`
3. `codex/event/agent_message_content_delta` →
`item/agentMessage/delta`.
4. `codex/event/agent_reasoning_section_break` ->
`item/reasoning/summaryPartAdded`.
Also added a change in core to pass down content index, summary index
and item id from events.
Tested with the `git checkout owen/app_server_test_client && cargo run
-p codex-app-server-test-client -- send-message-v2 "hello"` and verified
that new events are emitted correctly.
This one should be quite straightforward, as it's just a translation of
TurnItem events we already emit to ThreadItem that app-server exposes to
customers.
To test, cp my change to owen/app_server_test_client and do the
following:
```
cargo build -p codex-cli
RUST_LOG=codex_app_server=info CODEX_BIN=target/debug/codex cargo run -p codex-app-server-test-client -- send-message-v2 "hello"
```
example event before (still kept there for backward compatibility):
```
{
< "method": "codex/event/item_completed",
< "params": {
< "conversationId": "019a74cc-fad9-7ab3-83a3-f42827b7b074",
< "id": "0",
< "msg": {
< "item": {
< "Reasoning": {
< "id": "rs_03d183492e07e20a016913a936eb8c81a1a7671a103fee8afc",
< "raw_content": [],
< "summary_text": [
< "Hey! What would you like to work on? I can explore the repo, run specific tests, or implement a change. Let's keep it short and straightforward. There's no need for a lengthy introduction or elaborate planning, just a friendly greeting and an open offer to help. I want to make sure the user feels welcomed and understood right from the start. It's all about keeping the tone friendly and concise!"
< ]
< }
< },
< "thread_id": "019a74cc-fad9-7ab3-83a3-f42827b7b074",
< "turn_id": "0",
< "type": "item_completed"
< }
< }
< }
```
after (v2):
```
< {
< "method": "item/completed",
< "params": {
< "item": {
< "id": "rs_03d183492e07e20a016913a936eb8c81a1a7671a103fee8afc",
< "text": "Hey! What would you like to work on? I can explore the repo, run specific tests, or implement a change. Let's keep it short and straightforward. There's no need for a lengthy introduction or elaborate planning, just a friendly greeting and an open offer to help. I want to make sure the user feels welcomed and understood right from the start. It's all about keeping the tone friendly and concise!",
< "type": "reasoning"
< }
< }
< }
```
This PR does two things:
1. add a new function in core that maps the core-internal plan type to
the external plan type;
2. implement account/read that get account status (v2 of
`getAuthStatus`).
This PR implements `account/login/start` and `account/login/completed`.
Instead of having separate endpoints for login with chatgpt and api, we
have a single enum handling different login methods. For sync auth
methods like sign in with api key, we still send a `completed`
notification back to be compatible with the async login flow.
V2 for `account/updated` and `account/logout` for app server. correspond
to old `authStatusChange` and `LogoutChatGpt` respectively. Followup PRs
will make other v2 endpoints call `account/updated` instead of
`authStatusChange` too.
There's still some debate about whether we want to expose
`tools.view_image` or `feature.view_image` so those are left unchanged
for now, but this old `include_view_image_tool` config is good-to-go.
Also updated the doc to reflect that `view_image` tool is now by default
true.
This PR is a follow-up to #5591. It allows users to choose which auth
storage mode they want by using the new
`cli_auth_credentials_store_mode` config.
Follow-up PR to #5569. Add Keyring Support for Auth Storage in Codex CLI
as well as a hybrid mode (default to persisting in keychain but fall
back to file when unavailable.)
It also refactors out the keyringstore implementation from rmcp-client
[here](https://github.com/openai/codex/blob/main/codex-rs/rmcp-client/src/oauth.rs)
to a new keyring-store crate.
There will be a follow-up that picks the right credential mode depending
on the config, instead of hardcoding `AuthCredentialsStoreMode::File`.
This PR introduces a new `Auth Storage` abstraction layer that takes
care of read, write, and load of auth tokens based on the
AuthCredentialsStoreMode. It is similar to how we handle MCP client
oauth
[here](https://github.com/openai/codex/blob/main/codex-rs/rmcp-client/src/oauth.rs).
Instead of reading and writing directly from disk for auth tokens, Codex
CLI workflows now should instead use this auth storage using the public
helper functions.
This PR is just a refactor of the current code so the behavior stays the
same. We will add support for keyring and hybrid mode in follow-up PRs.
I have read the CLA Document and I hereby sign the CLA
Celia Chen